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+ <a href="batched__reduction_8h.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span>&#160;<span class="comment">/***************************************************************************************************</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span>&#160;<span class="comment">* Copyright (c) 2017-2019, NVIDIA CORPORATION. All rights reserved.</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span>&#160;<span class="comment">*</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span>&#160;<span class="comment">* Redistribution and use in source and binary forms, with or without modification, are permitted</span></div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span>&#160;<span class="comment">* provided that the following conditions are met:</span></div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span>&#160;<span class="comment">* * Redistributions of source code must retain the above copyright notice, this list of</span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span>&#160;<span class="comment">* conditions and the following disclaimer.</span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span>&#160;<span class="comment">* * Redistributions in binary form must reproduce the above copyright notice, this list of</span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span>&#160;<span class="comment">* conditions and the following disclaimer in the documentation and/or other materials</span></div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span>&#160;<span class="comment">* provided with the distribution.</span></div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span>&#160;<span class="comment">* * Neither the name of the NVIDIA CORPORATION nor the names of its contributors may be used</span></div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span>&#160;<span class="comment">* to endorse or promote products derived from this software without specific prior written</span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span>&#160;<span class="comment">* permission.</span></div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span>&#160;<span class="comment">*</span></div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span>&#160;<span class="comment">* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS &quot;AS IS&quot; AND ANY EXPRESS OR</span></div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span>&#160;<span class="comment">* IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND</span></div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span>&#160;<span class="comment">* FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL NVIDIA CORPORATION BE LIABLE</span></div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span>&#160;<span class="comment">* FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,</span></div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span>&#160;<span class="comment">* BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;</span></div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span>&#160;<span class="comment">* OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT,</span></div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span>&#160;<span class="comment">* STRICT LIABILITY, OR TOR (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE</span></div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span>&#160;<span class="comment">* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.</span></div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span>&#160;<span class="comment">*</span></div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span>&#160;<span class="comment">**************************************************************************************************/</span></div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span>&#160;<span class="preprocessor">#pragma once</span></div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span>&#160;</div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span>&#160;<span class="preprocessor">#if !defined(__CUDACC_RTC__)</span></div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span>&#160;<span class="preprocessor">#include &lt;cuda.h&gt;</span></div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span>&#160;<span class="preprocessor">#endif</span></div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span>&#160;</div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="coord_8h.html">cutlass/coord.h</a>&quot;</span></div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span>&#160;<span class="preprocessor">#include &quot;cutlass/util/platform.h&quot;</span></div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>&#160;<span class="preprocessor">#include &quot;cutlass/fragment.h&quot;</span></div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>&#160;</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>&#160;<span class="keyword">namespace </span><a class="code" href="namespacecutlass.html">cutlass</a> {</div><div class="line"><a name="l00040"></a><span class="lineno"><a class="line" href="namespacecutlass_1_1reduction.html"> 40</a></span>&#160;<span class="keyword">namespace </span>reduction {</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>&#160;</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>&#160;</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> batched_reduction_&gt;</div><div class="line"><a name="l00045"></a><span class="lineno"><a class="line" href="namespacecutlass_1_1reduction.html#a9665e8f438a7b290d6e2eb640d93045f"> 45</a></span>&#160;__global__ <a class="code" href="namespacecutlass_1_1reduction.html#a9665e8f438a7b290d6e2eb640d93045f">__launch_bounds__</a>(batched_reduction_::Traits::kThreads, 1) void batched_reduction_kernel(typename batched_reduction_::Params params) {</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>&#160; <span class="comment">// Construct the batched_reduction object</span></div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>&#160; batched_reduction_ batched_reduction(params);</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>&#160; batched_reduction.run();</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>&#160;}</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>&#160;</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> BatchedReductionTraits_&gt;</div><div class="line"><a name="l00052"></a><span class="lineno"><a class="line" href="structcutlass_1_1reduction_1_1BatchedReduction.html"> 52</a></span>&#160;<span class="keyword">struct </span><a class="code" href="structcutlass_1_1reduction_1_1BatchedReduction.html">BatchedReduction</a> {</div><div class="line"><a name="l00054"></a><span class="lineno"><a class="line" href="structcutlass_1_1reduction_1_1BatchedReduction.html#ae0c48344c7457f17429e6ae7a76dba37"> 54</a></span>&#160; <span class="keyword">typedef</span> <a class="code" href="structcutlass_1_1reduction_1_1BatchedReduction.html">BatchedReduction&lt;BatchedReductionTraits_&gt;</a> <a class="code" href="structcutlass_1_1reduction_1_1BatchedReduction.html#ae0c48344c7457f17429e6ae7a76dba37">This_</a>;</div><div class="line"><a name="l00056"></a><span class="lineno"><a class="line" href="structcutlass_1_1reduction_1_1BatchedReduction.html#aa50195fcf53f6d69ccfa37f44a524a99"> 56</a></span>&#160; <span class="keyword">typedef</span> BatchedReductionTraits_ <a class="code" href="structcutlass_1_1reduction_1_1BatchedReduction.html#aa50195fcf53f6d69ccfa37f44a524a99">Traits</a>;</div><div class="line"><a name="l00058"></a><span class="lineno"><a class="line" href="structcutlass_1_1reduction_1_1BatchedReduction.html#a213c6812458c008435ed3ea710fe2454"> 58</a></span>&#160; <span class="keyword">typedef</span> <span class="keyword">typename</span> Traits::Params <a class="code" href="structcutlass_1_1reduction_1_1BatchedReduction.html#a213c6812458c008435ed3ea710fe2454">Params</a>;</div><div class="line"><a name="l00060"></a><span class="lineno"><a class="line" href="structcutlass_1_1reduction_1_1BatchedReduction.html#a30605f35d51e4364fe80edb80eac5e80"> 60</a></span>&#160; <span class="keyword">typedef</span> <span class="keyword">typename</span> Traits::Functor <a class="code" href="structcutlass_1_1reduction_1_1BatchedReduction.html#a30605f35d51e4364fe80edb80eac5e80">Functor</a>;</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>&#160;</div><div class="line"><a name="l00063"></a><span class="lineno"><a class="line" href="structcutlass_1_1reduction_1_1BatchedReduction.html#a9d76da3dcf4d8ec0cfeb2134f73ea22b"> 63</a></span>&#160; CUTLASS_DEVICE <a class="code" href="structcutlass_1_1reduction_1_1BatchedReduction.html#a9d76da3dcf4d8ec0cfeb2134f73ea22b">BatchedReduction</a>(Params <span class="keyword">const</span> &amp;params_)</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>&#160; : <a class="code" href="structcutlass_1_1reduction_1_1BatchedReduction.html#a9c9d8378c735597f39927c6ab32519ef">params</a>(params_), <a class="code" href="structcutlass_1_1reduction_1_1BatchedReduction.html#a0f6b38c1b3a5800e6f29d9a2c6c1928d">functor</a>(params_.functorParams) {}</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>&#160; </div><div class="line"><a name="l00068"></a><span class="lineno"><a class="line" href="structcutlass_1_1reduction_1_1BatchedReduction.html#a4bfcdfd8f2edeb4fc7081443584d599b"> 68</a></span>&#160; CUTLASS_DEVICE <span class="keywordtype">void</span> <a class="code" href="structcutlass_1_1reduction_1_1BatchedReduction.html#a4bfcdfd8f2edeb4fc7081443584d599b">run</a>() {</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>&#160;<span class="preprocessor">#if (__CUDA_ARCH__ &gt;= 600)</span></div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>&#160; <span class="comment">// Swizzle the IDs of the block </span></div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>&#160; <span class="keyword">typename</span> Traits::BlockSwizzle block_swizzle;</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>&#160; <a class="code" href="structcutlass_1_1Coord.html">Coord&lt;3&gt;</a> threadblock_offset =</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>&#160; block_swizzle.get_threadblock_offset(make_Coord_from_shape&lt;Traits::SubTile&gt;());</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>&#160;</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>&#160; <span class="keywordtype">int</span> subTileSize = gridDim.x * Traits::SubTile::kW;</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>&#160; <span class="keywordtype">int</span> tileSize = <a class="code" href="structcutlass_1_1reduction_1_1BatchedReduction.html#a9c9d8378c735597f39927c6ab32519ef">params</a>.problem_size[1] * <a class="code" href="structcutlass_1_1reduction_1_1BatchedReduction.html#a9c9d8378c735597f39927c6ab32519ef">params</a>.problem_size[2];</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>&#160; <span class="keywordtype">int</span> subTileOffset = threadblock_offset[2] + threadIdx.x * Traits::ThreadShape::kW;</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>&#160;</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>&#160; <span class="keywordtype">int</span> subTileBase = 0;</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>&#160;</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>&#160; <span class="keyword">typename</span> Traits::ScalarA inRegs[Traits::maxInReg];</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>&#160; <span class="keyword">typename</span> Traits::ScalarAccum AccumRegs[Traits::maxOutReg];</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>&#160;<span class="preprocessor">#pragma unroll</span></div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">int</span> subTile = 0; subTile &lt; tileSize; subTile += subTileSize) {</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>&#160; <span class="keywordtype">int</span> tileOffset = subTileBase + subTileOffset;</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>&#160; <span class="comment">// Init AccumRegs</span></div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>&#160;<span class="preprocessor">#pragma unroll</span></div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; Traits::ThreadShape::kW; i++)</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>&#160; AccumRegs[i] = static_cast&lt;typename Traits::ScalarAccum&gt;(0.0f);</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>&#160; <span class="comment">// Fetch c0</span></div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>&#160; <span class="keyword">typename</span> Traits::ScalarAccum c0[Traits::ThreadShape::kW];</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>&#160;<span class="preprocessor">#pragma unroll</span></div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i&lt; Traits::ThreadShape::kW; i++)</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>&#160; c0[i] = static_cast&lt;typename Traits::ScalarAccum&gt;(<a class="code" href="structcutlass_1_1reduction_1_1BatchedReduction.html#a9c9d8378c735597f39927c6ab32519ef">params</a>.d_c[tileOffset + i]);</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>&#160;</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>&#160; <span class="comment">// Fetch partial sums from A</span></div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>&#160;<span class="preprocessor">#pragma unroll</span></div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">int</span> s = 0; s &lt; Traits::ReductionSize; s++) {</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>&#160; <span class="keywordtype">int</span> inRegOffset = s * Traits::ThreadShape::kW;</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>&#160; <span class="keywordtype">int</span> dOffset = (s * tileSize) + tileOffset;</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>&#160;<span class="preprocessor">#pragma unroll</span></div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i&lt; Traits::ThreadShape::kW; i++) {</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>&#160; inRegs[inRegOffset + i] = <a class="code" href="structcutlass_1_1reduction_1_1BatchedReduction.html#a9c9d8378c735597f39927c6ab32519ef">params</a>.d_a[dOffset + i];</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>&#160; }</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>&#160; }</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>&#160;</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>&#160; <span class="comment">// Accumulate</span></div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>&#160;<span class="preprocessor">#pragma unroll</span></div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">int</span> s = 0; s &lt; Traits::ReductionSize; s++) {</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>&#160; <span class="keywordtype">int</span> inRegOffset = s * Traits::ThreadShape::kW;</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>&#160;<span class="preprocessor">#pragma unroll</span></div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; Traits::ThreadShape::kW; i++) {</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>&#160; <span class="comment">//AccumRegs[i] = cuFma(params.alpha, inRegs[inRegOffset + i], AccumRegs[i]);</span></div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>&#160; <span class="comment">//AccumRegs[i] = params.alpha * inRegs[inRegOffset + i] + AccumRegs[i];</span></div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>&#160; AccumRegs[i] = <span class="keyword">static_cast&lt;</span>typename Traits::ScalarAccum<span class="keyword">&gt;</span>(inRegs[inRegOffset + i]) + AccumRegs[i];</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>&#160; }</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>&#160; }</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>&#160; <span class="comment">// calling functor</span></div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>&#160; functor_caller&lt;Traits::ThreadShapeMultiple2&gt;(AccumRegs, c0, AccumRegs);</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>&#160;</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>&#160; <span class="comment">// Store AccumRegs to D</span></div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>&#160;<span class="preprocessor">#pragma unroll</span></div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; Traits::ThreadShape::kW; i++) {</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>&#160; <a class="code" href="structcutlass_1_1reduction_1_1BatchedReduction.html#a9c9d8378c735597f39927c6ab32519ef">params</a>.d_d[tileOffset + i] = <span class="keyword">static_cast&lt;</span>typename Traits::ScalarD<span class="keyword">&gt;</span>(AccumRegs[i]);</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>&#160; }</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>&#160;</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>&#160; <span class="comment">// Advance sub-tile pointer</span></div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>&#160; subTileBase += subTileSize;</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>&#160; } <span class="comment">// end for loop</span></div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>&#160;<span class="preprocessor">#endif //#if (__CUDA_ARCH__ &gt;= 600)</span></div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span>&#160; }</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>&#160;</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>&#160; <span class="keyword">template</span>&lt;<span class="keywordtype">bool</span> ThreadShapeMultiple2&gt;</div><div class="line"><a name="l00134"></a><span class="lineno"><a class="line" href="structcutlass_1_1reduction_1_1BatchedReduction.html#a7c1d173cbe3abd93bd7bd4c4bf0e0d26"> 134</a></span>&#160; CUTLASS_DEVICE <span class="keywordtype">void</span> <a class="code" href="structcutlass_1_1reduction_1_1BatchedReduction.html#a7c1d173cbe3abd93bd7bd4c4bf0e0d26">functor_caller</a>(<span class="keyword">typename</span> Traits::ScalarAccum <span class="keyword">const</span> *accum, <span class="keyword">typename</span> Traits::ScalarAccum <span class="keyword">const</span> *old, <span class="keyword">typename</span> Traits::ScalarAccum *output) {</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>&#160; <span class="keywordflow">if</span> (ThreadShapeMultiple2 == <span class="keyword">true</span>) {</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>&#160;<span class="preprocessor">#pragma unroll</span></div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; Traits::ThreadShape::kW / 2; i++) {</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span>&#160; <a class="code" href="structcutlass_1_1reduction_1_1BatchedReduction.html#a0f6b38c1b3a5800e6f29d9a2c6c1928d">functor</a>.template evaluate&lt;typename Traits::ScalarAccum, typename Traits::ScalarAccum, 2&gt;(&amp;accum[2 * i], &amp;old[2 * i], &amp;output[2 * i]);</div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>&#160; }</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>&#160; }</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>&#160; <span class="keywordflow">else</span> {</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>&#160;<span class="preprocessor">#pragma unroll</span></div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; Traits::ThreadShape::kW; i++) {</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>&#160; <a class="code" href="structcutlass_1_1reduction_1_1BatchedReduction.html#a0f6b38c1b3a5800e6f29d9a2c6c1928d">functor</a>.template evaluate&lt;typename Traits::ScalarAccum, typename Traits::ScalarAccum, 1&gt;(&amp;accum[i], &amp;old[i], &amp;output[i]);</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>&#160; }</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>&#160; }</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>&#160; }</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span>&#160;</div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>&#160; <span class="comment">//</span></div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>&#160; <span class="comment">// Static function members</span></div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>&#160; <span class="comment">//</span></div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span>&#160;<span class="preprocessor">#if !defined(__CUDACC_RTC__)</span></div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span>&#160; <span class="keyword">static</span> __host__ cudaError_t <a class="code" href="structcutlass_1_1reduction_1_1BatchedReduction.html#ab059393ac467ac365bd0b45c200befdf">launch</a>(Params <span class="keyword">const</span>&amp; <a class="code" href="structcutlass_1_1reduction_1_1BatchedReduction.html#a9c9d8378c735597f39927c6ab32519ef">params</a>,</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>&#160; cudaStream_t stream = cudaStreamDefault) {</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>&#160; <span class="comment">// Setup the grid. </span></div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span>&#160; <span class="keyword">typename</span> Traits::BlockSwizzle block_swizzle;</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>&#160; dim3 grid = block_swizzle.get_grid_layout(params.problem_size,</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>&#160; make_Coord_from_shape&lt;typename Traits::OutputTile&gt;());</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>&#160; </div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span>&#160; dim3 block;</div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span>&#160; block.x = Traits::kThreads;</div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span>&#160; batched_reduction_kernel&lt;This_&gt;&lt;&lt;&lt;grid, block, 0, stream&gt;&gt;&gt;(<a class="code" href="structcutlass_1_1reduction_1_1BatchedReduction.html#a9c9d8378c735597f39927c6ab32519ef">params</a>);</div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span>&#160; <span class="keywordflow">return</span> cudaGetLastError();</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>&#160; }</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span>&#160;<span class="preprocessor">#endif</span></div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>&#160;</div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span>&#160; <span class="comment">//</span></div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>&#160; <span class="comment">// Data members</span></div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span>&#160; <span class="comment">//</span></div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span>&#160;</div><div class="line"><a name="l00173"></a><span class="lineno"><a class="line" href="structcutlass_1_1reduction_1_1BatchedReduction.html#a9c9d8378c735597f39927c6ab32519ef"> 173</a></span>&#160; Params <span class="keyword">const</span>&amp; <a class="code" href="structcutlass_1_1reduction_1_1BatchedReduction.html#a9c9d8378c735597f39927c6ab32519ef">params</a>;</div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span>&#160; <span class="comment">// The functor.</span></div><div class="line"><a name="l00175"></a><span class="lineno"><a class="line" href="structcutlass_1_1reduction_1_1BatchedReduction.html#a0f6b38c1b3a5800e6f29d9a2c6c1928d"> 175</a></span>&#160; Functor <a class="code" href="structcutlass_1_1reduction_1_1BatchedReduction.html#a0f6b38c1b3a5800e6f29d9a2c6c1928d">functor</a>;</div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span>&#160;};</div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span>&#160;</div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span>&#160;} <span class="comment">// namespace reduction</span></div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span>&#160;} <span class="comment">// namespace cutlass</span></div><div class="ttc" id="namespacecutlass_html"><div class="ttname"><a href="namespacecutlass.html">cutlass</a></div><div class="ttdef"><b>Definition:</b> aligned_buffer.h:35</div></div>
102
+ <div class="ttc" id="structcutlass_1_1reduction_1_1BatchedReduction_html_a9c9d8378c735597f39927c6ab32519ef"><div class="ttname"><a href="structcutlass_1_1reduction_1_1BatchedReduction.html#a9c9d8378c735597f39927c6ab32519ef">cutlass::reduction::BatchedReduction::params</a></div><div class="ttdeci">Params const &amp; params</div><div class="ttdoc">The params. </div><div class="ttdef"><b>Definition:</b> batched_reduction.h:173</div></div>
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+ <div class="ttc" id="namespacecutlass_1_1reduction_html_a9665e8f438a7b290d6e2eb640d93045f"><div class="ttname"><a href="namespacecutlass_1_1reduction.html#a9665e8f438a7b290d6e2eb640d93045f">cutlass::reduction::__launch_bounds__</a></div><div class="ttdeci">__global__ __launch_bounds__(batched_reduction_::Traits::kThreads, 1) void batched_reduction_kernel(typename batched_reduction_</div><div class="ttdef"><b>Definition:</b> batched_reduction.h:45</div></div>
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+ <div class="ttc" id="coord_8h_html"><div class="ttname"><a href="coord_8h.html">coord.h</a></div><div class="ttdoc">A Coord is a coordinate of arbitrary rank into a tensor or matrix. </div></div>
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+ <div class="ttc" id="structcutlass_1_1reduction_1_1BatchedReduction_html_a4bfcdfd8f2edeb4fc7081443584d599b"><div class="ttname"><a href="structcutlass_1_1reduction_1_1BatchedReduction.html#a4bfcdfd8f2edeb4fc7081443584d599b">cutlass::reduction::BatchedReduction::run</a></div><div class="ttdeci">CUTLASS_DEVICE void run()</div><div class="ttdef"><b>Definition:</b> batched_reduction.h:68</div></div>
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+ <div class="ttc" id="structcutlass_1_1reduction_1_1BatchedReduction_html_ae0c48344c7457f17429e6ae7a76dba37"><div class="ttname"><a href="structcutlass_1_1reduction_1_1BatchedReduction.html#ae0c48344c7457f17429e6ae7a76dba37">cutlass::reduction::BatchedReduction::This_</a></div><div class="ttdeci">BatchedReduction&lt; BatchedReductionTraits_ &gt; This_</div><div class="ttdoc">This class. </div><div class="ttdef"><b>Definition:</b> batched_reduction.h:54</div></div>
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+ <div class="ttc" id="structcutlass_1_1reduction_1_1BatchedReduction_html_a0f6b38c1b3a5800e6f29d9a2c6c1928d"><div class="ttname"><a href="structcutlass_1_1reduction_1_1BatchedReduction.html#a0f6b38c1b3a5800e6f29d9a2c6c1928d">cutlass::reduction::BatchedReduction::functor</a></div><div class="ttdeci">Functor functor</div><div class="ttdef"><b>Definition:</b> batched_reduction.h:175</div></div>
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+ <div class="ttc" id="structcutlass_1_1reduction_1_1BatchedReduction_html"><div class="ttname"><a href="structcutlass_1_1reduction_1_1BatchedReduction.html">cutlass::reduction::BatchedReduction</a></div><div class="ttdef"><b>Definition:</b> batched_reduction.h:52</div></div>
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+ <div class="ttc" id="structcutlass_1_1Coord_html"><div class="ttname"><a href="structcutlass_1_1Coord.html">cutlass::Coord&lt; 3 &gt;</a></div></div>
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+ <div class="ttc" id="structcutlass_1_1reduction_1_1BatchedReduction_html_a9d76da3dcf4d8ec0cfeb2134f73ea22b"><div class="ttname"><a href="structcutlass_1_1reduction_1_1BatchedReduction.html#a9d76da3dcf4d8ec0cfeb2134f73ea22b">cutlass::reduction::BatchedReduction::BatchedReduction</a></div><div class="ttdeci">CUTLASS_DEVICE BatchedReduction(Params const &amp;params_)</div><div class="ttdoc">ctor </div><div class="ttdef"><b>Definition:</b> batched_reduction.h:63</div></div>
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+ <div class="ttc" id="structcutlass_1_1reduction_1_1BatchedReduction_html_a213c6812458c008435ed3ea710fe2454"><div class="ttname"><a href="structcutlass_1_1reduction_1_1BatchedReduction.html#a213c6812458c008435ed3ea710fe2454">cutlass::reduction::BatchedReduction::Params</a></div><div class="ttdeci">Traits::Params Params</div><div class="ttdoc">Params. </div><div class="ttdef"><b>Definition:</b> batched_reduction.h:58</div></div>
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+ <div class="ttc" id="structcutlass_1_1reduction_1_1BatchedReduction_html_a7c1d173cbe3abd93bd7bd4c4bf0e0d26"><div class="ttname"><a href="structcutlass_1_1reduction_1_1BatchedReduction.html#a7c1d173cbe3abd93bd7bd4c4bf0e0d26">cutlass::reduction::BatchedReduction::functor_caller</a></div><div class="ttdeci">CUTLASS_DEVICE void functor_caller(typename Traits::ScalarAccum const *accum, typename Traits::ScalarAccum const *old, typename Traits::ScalarAccum *output)</div><div class="ttdef"><b>Definition:</b> batched_reduction.h:134</div></div>
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+ <div class="ttc" id="structcutlass_1_1reduction_1_1BatchedReduction_html_a30605f35d51e4364fe80edb80eac5e80"><div class="ttname"><a href="structcutlass_1_1reduction_1_1BatchedReduction.html#a30605f35d51e4364fe80edb80eac5e80">cutlass::reduction::BatchedReduction::Functor</a></div><div class="ttdeci">Traits::Functor Functor</div><div class="ttdoc">functor </div><div class="ttdef"><b>Definition:</b> batched_reduction.h:60</div></div>
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+ <div class="ttc" id="structcutlass_1_1reduction_1_1BatchedReduction_html_aa50195fcf53f6d69ccfa37f44a524a99"><div class="ttname"><a href="structcutlass_1_1reduction_1_1BatchedReduction.html#aa50195fcf53f6d69ccfa37f44a524a99">cutlass::reduction::BatchedReduction::Traits</a></div><div class="ttdeci">BatchedReductionTraits_ Traits</div><div class="ttdoc">The traits. </div><div class="ttdef"><b>Definition:</b> batched_reduction.h:56</div></div>
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+ <div class="ttc" id="structcutlass_1_1reduction_1_1BatchedReduction_html_ab059393ac467ac365bd0b45c200befdf"><div class="ttname"><a href="structcutlass_1_1reduction_1_1BatchedReduction.html#ab059393ac467ac365bd0b45c200befdf">cutlass::reduction::BatchedReduction::launch</a></div><div class="ttdeci">static __host__ cudaError_t launch(Params const &amp;params, cudaStream_t stream=cudaStreamDefault)</div><div class="ttdoc">Launch the kernel. </div><div class="ttdef"><b>Definition:</b> batched_reduction.h:154</div></div>
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+ <ul>
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+ <li class="navelem"><a class="el" href="namespacecutlass.html">cutlass</a></li><li class="navelem"><a class="el" href="namespacecutlass_1_1gemm.html">gemm</a></li><li class="navelem"><a class="el" href="namespacecutlass_1_1gemm_1_1warp.html">warp</a></li><li class="navelem"><a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html">MmaTensorOp</a></li> </ul>
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+ <div class="title">cutlass::gemm::warp::MmaTensorOp&lt; Shape_, ElementA_, LayoutA_, ElementB_, LayoutB_, ElementC_, LayoutC_, Policy_, PartitionsK_, AccumulatorsInRowMajor, PartitionsN_, Enable &gt; Member List</div> </div>
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+ </div><!--header-->
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+ <div class="contents">
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+
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+ <p>This is the complete list of members for <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html">cutlass::gemm::warp::MmaTensorOp&lt; Shape_, ElementA_, LayoutA_, ElementB_, LayoutB_, ElementC_, LayoutC_, Policy_, PartitionsK_, AccumulatorsInRowMajor, PartitionsN_, Enable &gt;</a>, including all inherited members.</p>
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+ <table class="directory">
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+ <tr class="even"><td class="entry"><a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#aacab39db92cb1e6c081d4475a7984c8f">ElementA</a> typedef</td><td class="entry"><a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html">cutlass::gemm::warp::MmaTensorOp&lt; Shape_, ElementA_, LayoutA_, ElementB_, LayoutB_, ElementC_, LayoutC_, Policy_, PartitionsK_, AccumulatorsInRowMajor, PartitionsN_, Enable &gt;</a></td><td class="entry"></td></tr>
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+ <tr><td class="entry"><a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#a5b4f3c2bc511330a4e41078bf08b430c">ElementB</a> typedef</td><td class="entry"><a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html">cutlass::gemm::warp::MmaTensorOp&lt; Shape_, ElementA_, LayoutA_, ElementB_, LayoutB_, ElementC_, LayoutC_, Policy_, PartitionsK_, AccumulatorsInRowMajor, PartitionsN_, Enable &gt;</a></td><td class="entry"></td></tr>
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+ <tr class="even"><td class="entry"><a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#a48cc72d8223f19a7c8995e845124025d">ElementC</a> typedef</td><td class="entry"><a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html">cutlass::gemm::warp::MmaTensorOp&lt; Shape_, ElementA_, LayoutA_, ElementB_, LayoutB_, ElementC_, LayoutC_, Policy_, PartitionsK_, AccumulatorsInRowMajor, PartitionsN_, Enable &gt;</a></td><td class="entry"></td></tr>
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+ <tr><td class="entry"><a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#ae7958be3c77c61ee500688bba2195b1a">FragmentA</a> typedef</td><td class="entry"><a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html">cutlass::gemm::warp::MmaTensorOp&lt; Shape_, ElementA_, LayoutA_, ElementB_, LayoutB_, ElementC_, LayoutC_, Policy_, PartitionsK_, AccumulatorsInRowMajor, PartitionsN_, Enable &gt;</a></td><td class="entry"></td></tr>
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+ <tr class="even"><td class="entry"><a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#a268f27ae31f2e1a4e8a2e734ec1c1816">FragmentB</a> typedef</td><td class="entry"><a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html">cutlass::gemm::warp::MmaTensorOp&lt; Shape_, ElementA_, LayoutA_, ElementB_, LayoutB_, ElementC_, LayoutC_, Policy_, PartitionsK_, AccumulatorsInRowMajor, PartitionsN_, Enable &gt;</a></td><td class="entry"></td></tr>
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+ <tr><td class="entry"><a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#ae03fe3d58f3d96e875055e7721548bab">FragmentC</a> typedef</td><td class="entry"><a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html">cutlass::gemm::warp::MmaTensorOp&lt; Shape_, ElementA_, LayoutA_, ElementB_, LayoutB_, ElementC_, LayoutC_, Policy_, PartitionsK_, AccumulatorsInRowMajor, PartitionsN_, Enable &gt;</a></td><td class="entry"></td></tr>
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+ <tr class="even"><td class="entry"><a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#a794384bbf37bce5504232a862dd1e089">IteratorA</a> typedef</td><td class="entry"><a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html">cutlass::gemm::warp::MmaTensorOp&lt; Shape_, ElementA_, LayoutA_, ElementB_, LayoutB_, ElementC_, LayoutC_, Policy_, PartitionsK_, AccumulatorsInRowMajor, PartitionsN_, Enable &gt;</a></td><td class="entry"></td></tr>
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+ <tr><td class="entry"><a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#a83f46087d7f39e4e039e74cbb79e3b89">IteratorB</a> typedef</td><td class="entry"><a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html">cutlass::gemm::warp::MmaTensorOp&lt; Shape_, ElementA_, LayoutA_, ElementB_, LayoutB_, ElementC_, LayoutC_, Policy_, PartitionsK_, AccumulatorsInRowMajor, PartitionsN_, Enable &gt;</a></td><td class="entry"></td></tr>
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+ <tr class="even"><td class="entry"><a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#a40ea7a332afaa4e6476020a7357ed541">IteratorC</a> typedef</td><td class="entry"><a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html">cutlass::gemm::warp::MmaTensorOp&lt; Shape_, ElementA_, LayoutA_, ElementB_, LayoutB_, ElementC_, LayoutC_, Policy_, PartitionsK_, AccumulatorsInRowMajor, PartitionsN_, Enable &gt;</a></td><td class="entry"></td></tr>
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+ <tr><td class="entry"><a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#a9e73c525ef6835bd6500f714166a7c43">kPartitionsK</a></td><td class="entry"><a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html">cutlass::gemm::warp::MmaTensorOp&lt; Shape_, ElementA_, LayoutA_, ElementB_, LayoutB_, ElementC_, LayoutC_, Policy_, PartitionsK_, AccumulatorsInRowMajor, PartitionsN_, Enable &gt;</a></td><td class="entry"><span class="mlabel">static</span></td></tr>
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+ <tr class="even"><td class="entry"><a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#ac47c26a237de7990a53df77a4535141b">kPartitionsN</a></td><td class="entry"><a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html">cutlass::gemm::warp::MmaTensorOp&lt; Shape_, ElementA_, LayoutA_, ElementB_, LayoutB_, ElementC_, LayoutC_, Policy_, PartitionsK_, AccumulatorsInRowMajor, PartitionsN_, Enable &gt;</a></td><td class="entry"><span class="mlabel">static</span></td></tr>
117
+ <tr><td class="entry"><a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#a51960b3e3cdde83bc7321b1607b78302">kThreadCount</a></td><td class="entry"><a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html">cutlass::gemm::warp::MmaTensorOp&lt; Shape_, ElementA_, LayoutA_, ElementB_, LayoutB_, ElementC_, LayoutC_, Policy_, PartitionsK_, AccumulatorsInRowMajor, PartitionsN_, Enable &gt;</a></td><td class="entry"><span class="mlabel">static</span></td></tr>
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+ <tr class="even"><td class="entry"><a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#a8ea4f03edb1809d4a2a07c05f22b8398">LayoutA</a> typedef</td><td class="entry"><a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html">cutlass::gemm::warp::MmaTensorOp&lt; Shape_, ElementA_, LayoutA_, ElementB_, LayoutB_, ElementC_, LayoutC_, Policy_, PartitionsK_, AccumulatorsInRowMajor, PartitionsN_, Enable &gt;</a></td><td class="entry"></td></tr>
119
+ <tr><td class="entry"><a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#af94b734ca46b1e68a273b35f49155e16">LayoutB</a> typedef</td><td class="entry"><a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html">cutlass::gemm::warp::MmaTensorOp&lt; Shape_, ElementA_, LayoutA_, ElementB_, LayoutB_, ElementC_, LayoutC_, Policy_, PartitionsK_, AccumulatorsInRowMajor, PartitionsN_, Enable &gt;</a></td><td class="entry"></td></tr>
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+ <tr class="even"><td class="entry"><a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#a77dea454b02646c21c7e9d3f340b9bdb">LayoutC</a> typedef</td><td class="entry"><a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html">cutlass::gemm::warp::MmaTensorOp&lt; Shape_, ElementA_, LayoutA_, ElementB_, LayoutB_, ElementC_, LayoutC_, Policy_, PartitionsK_, AccumulatorsInRowMajor, PartitionsN_, Enable &gt;</a></td><td class="entry"></td></tr>
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+ <tr><td class="entry"><a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#a2eddba2b1644d2df5ade4de535b95ed7">mma</a></td><td class="entry"><a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html">cutlass::gemm::warp::MmaTensorOp&lt; Shape_, ElementA_, LayoutA_, ElementB_, LayoutB_, ElementC_, LayoutC_, Policy_, PartitionsK_, AccumulatorsInRowMajor, PartitionsN_, Enable &gt;</a></td><td class="entry"></td></tr>
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+ <tr class="even"><td class="entry"><a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#ae344dbb59b9234254768238bee17f2d7">MmaTensorOp</a>()</td><td class="entry"><a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html">cutlass::gemm::warp::MmaTensorOp&lt; Shape_, ElementA_, LayoutA_, ElementB_, LayoutB_, ElementC_, LayoutC_, Policy_, PartitionsK_, AccumulatorsInRowMajor, PartitionsN_, Enable &gt;</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
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+ <tr><td class="entry"><a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#ac7b9462528c81aa23995760c8c104f47">operator()</a>(FragmentC &amp;D, FragmentA const &amp;A, FragmentB const &amp;B, FragmentC const &amp;C, int const &amp;partitionN_idx=0) const </td><td class="entry"><a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html">cutlass::gemm::warp::MmaTensorOp&lt; Shape_, ElementA_, LayoutA_, ElementB_, LayoutB_, ElementC_, LayoutC_, Policy_, PartitionsK_, AccumulatorsInRowMajor, PartitionsN_, Enable &gt;</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
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+ <tr class="even"><td class="entry"><a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#a2663baf282d4a7e9549cd52ffbf3cc02">OperatorClass</a> typedef</td><td class="entry"><a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html">cutlass::gemm::warp::MmaTensorOp&lt; Shape_, ElementA_, LayoutA_, ElementB_, LayoutB_, ElementC_, LayoutC_, Policy_, PartitionsK_, AccumulatorsInRowMajor, PartitionsN_, Enable &gt;</a></td><td class="entry"></td></tr>
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+ <tr><td class="entry"><a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#aca53ae2c2f98f6b1e735b332904aa9aa">Policy</a> typedef</td><td class="entry"><a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html">cutlass::gemm::warp::MmaTensorOp&lt; Shape_, ElementA_, LayoutA_, ElementB_, LayoutB_, ElementC_, LayoutC_, Policy_, PartitionsK_, AccumulatorsInRowMajor, PartitionsN_, Enable &gt;</a></td><td class="entry"></td></tr>
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+ <tr class="even"><td class="entry"><a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#ac876fbcde91b3cd490432e7c8002bc60">Shape</a> typedef</td><td class="entry"><a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html">cutlass::gemm::warp::MmaTensorOp&lt; Shape_, ElementA_, LayoutA_, ElementB_, LayoutB_, ElementC_, LayoutC_, Policy_, PartitionsK_, AccumulatorsInRowMajor, PartitionsN_, Enable &gt;</a></td><td class="entry"></td></tr>
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sglang_repo/sgl-kernel/3rdparty/flashinfer/3rdparty/cutlass/docs/classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileAccessIterator2dThreadTile_3_01Shape__41009dfccf282d1422aafb23cf1e3e4a.html ADDED
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+ </iframe>
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+
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+ <div id="nav-path" class="navpath">
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+ <ul>
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+ <li class="navelem"><a class="el" href="namespacecutlass.html">cutlass</a></li><li class="navelem"><a class="el" href="namespacecutlass_1_1transform.html">transform</a></li><li class="navelem"><a class="el" href="namespacecutlass_1_1transform_1_1threadblock.html">threadblock</a></li><li class="navelem"><a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileAccessIterator2dThreadTile_3_01Shape__7327fa15996bcb8502cdfcc192350fe1.html">PredicatedTileAccessIterator2dThreadTile&lt; Shape_, Element_, layout::RowMajor, AdvanceRank, ThreadMap_, AccessType_ &gt;</a></li> </ul>
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+ </div>
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+ </div><!-- top -->
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+ <div class="header">
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+ <div class="headertitle">
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+ <div class="title">cutlass::transform::threadblock::PredicatedTileAccessIterator2dThreadTile&lt; Shape_, Element_, layout::RowMajor, AdvanceRank, ThreadMap_, AccessType_ &gt; Member List</div> </div>
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+ </div><!--header-->
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+ <div class="contents">
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+
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+ <p>This is the complete list of members for <a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileAccessIterator2dThreadTile_3_01Shape__7327fa15996bcb8502cdfcc192350fe1.html">cutlass::transform::threadblock::PredicatedTileAccessIterator2dThreadTile&lt; Shape_, Element_, layout::RowMajor, AdvanceRank, ThreadMap_, AccessType_ &gt;</a>, including all inherited members.</p>
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+ <table class="directory">
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+ <tr class="even"><td class="entry"><a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileAccessIterator2dThreadTile_3_01Shape__7327fa15996bcb8502cdfcc192350fe1.html#aa3d5086a2911532ded1e57720409901b">AccessType</a> typedef</td><td class="entry"><a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileAccessIterator2dThreadTile_3_01Shape__7327fa15996bcb8502cdfcc192350fe1.html">cutlass::transform::threadblock::PredicatedTileAccessIterator2dThreadTile&lt; Shape_, Element_, layout::RowMajor, AdvanceRank, ThreadMap_, AccessType_ &gt;</a></td><td class="entry"></td></tr>
107
+ <tr><td class="entry"><a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileAccessIterator2dThreadTile_3_01Shape__7327fa15996bcb8502cdfcc192350fe1.html#aeac1b798dcdf8d1d5143451a5d8e43d5">add_pointer_offset</a>(LongIndex pointer_offset)</td><td class="entry"><a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileAccessIterator2dThreadTile_3_01Shape__7327fa15996bcb8502cdfcc192350fe1.html">cutlass::transform::threadblock::PredicatedTileAccessIterator2dThreadTile&lt; Shape_, Element_, layout::RowMajor, AdvanceRank, ThreadMap_, AccessType_ &gt;</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
108
+ <tr class="even"><td class="entry"><a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileAccessIterator2dThreadTile_3_01Shape__7327fa15996bcb8502cdfcc192350fe1.html#a1098663d934675c22a41373dd7351def">add_tile_offset</a>(TensorCoord const &amp;tile_offset)</td><td class="entry"><a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileAccessIterator2dThreadTile_3_01Shape__7327fa15996bcb8502cdfcc192350fe1.html">cutlass::transform::threadblock::PredicatedTileAccessIterator2dThreadTile&lt; Shape_, Element_, layout::RowMajor, AdvanceRank, ThreadMap_, AccessType_ &gt;</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
109
+ <tr><td class="entry"><a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileAccessIterator2dThreadTile_3_01Shape__7327fa15996bcb8502cdfcc192350fe1.html#abc85cc801d0e933dfb026a9c266674e2">clear_mask</a>()</td><td class="entry"><a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileAccessIterator2dThreadTile_3_01Shape__7327fa15996bcb8502cdfcc192350fe1.html">cutlass::transform::threadblock::PredicatedTileAccessIterator2dThreadTile&lt; Shape_, Element_, layout::RowMajor, AdvanceRank, ThreadMap_, AccessType_ &gt;</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
110
+ <tr class="even"><td class="entry"><a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileAccessIterator2dThreadTile_3_01Shape__7327fa15996bcb8502cdfcc192350fe1.html#af39b57506c5217cdc1553e302d502186">Element</a> typedef</td><td class="entry"><a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileAccessIterator2dThreadTile_3_01Shape__7327fa15996bcb8502cdfcc192350fe1.html">cutlass::transform::threadblock::PredicatedTileAccessIterator2dThreadTile&lt; Shape_, Element_, layout::RowMajor, AdvanceRank, ThreadMap_, AccessType_ &gt;</a></td><td class="entry"></td></tr>
111
+ <tr><td class="entry"><a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileAccessIterator2dThreadTile_3_01Shape__7327fa15996bcb8502cdfcc192350fe1.html#ae3e559443dd5f78da8b73a0b35766f1a">enable_mask</a>()</td><td class="entry"><a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileAccessIterator2dThreadTile_3_01Shape__7327fa15996bcb8502cdfcc192350fe1.html">cutlass::transform::threadblock::PredicatedTileAccessIterator2dThreadTile&lt; Shape_, Element_, layout::RowMajor, AdvanceRank, ThreadMap_, AccessType_ &gt;</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
112
+ <tr class="even"><td class="entry"><a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileAccessIterator2dThreadTile_3_01Shape__7327fa15996bcb8502cdfcc192350fe1.html#ab27ea2be4e2c962ffa8b72bd9d4ba935">get</a>() const </td><td class="entry"><a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileAccessIterator2dThreadTile_3_01Shape__7327fa15996bcb8502cdfcc192350fe1.html">cutlass::transform::threadblock::PredicatedTileAccessIterator2dThreadTile&lt; Shape_, Element_, layout::RowMajor, AdvanceRank, ThreadMap_, AccessType_ &gt;</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
113
+ <tr><td class="entry"><a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileAccessIterator2dThreadTile_3_01Shape__7327fa15996bcb8502cdfcc192350fe1.html#a0bc8cfc65e89e57bf9146d48763dc7b5">get_mask</a>(Mask &amp;mask)</td><td class="entry"><a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileAccessIterator2dThreadTile_3_01Shape__7327fa15996bcb8502cdfcc192350fe1.html">cutlass::transform::threadblock::PredicatedTileAccessIterator2dThreadTile&lt; Shape_, Element_, layout::RowMajor, AdvanceRank, ThreadMap_, AccessType_ &gt;</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
114
+ <tr class="even"><td class="entry"><a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileAccessIterator2dThreadTile_3_01Shape__7327fa15996bcb8502cdfcc192350fe1.html#a89554e5c07581d02000ee5eb8db043c1">Index</a> typedef</td><td class="entry"><a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileAccessIterator2dThreadTile_3_01Shape__7327fa15996bcb8502cdfcc192350fe1.html">cutlass::transform::threadblock::PredicatedTileAccessIterator2dThreadTile&lt; Shape_, Element_, layout::RowMajor, AdvanceRank, ThreadMap_, AccessType_ &gt;</a></td><td class="entry"></td></tr>
115
+ <tr><td class="entry"><a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileAccessIterator2dThreadTile_3_01Shape__7327fa15996bcb8502cdfcc192350fe1.html#a7c4e6d66d164e7d8c3bd6735b3b0e338">kAdvanceRank</a></td><td class="entry"><a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileAccessIterator2dThreadTile_3_01Shape__7327fa15996bcb8502cdfcc192350fe1.html">cutlass::transform::threadblock::PredicatedTileAccessIterator2dThreadTile&lt; Shape_, Element_, layout::RowMajor, AdvanceRank, ThreadMap_, AccessType_ &gt;</a></td><td class="entry"><span class="mlabel">static</span></td></tr>
116
+ <tr class="even"><td class="entry"><a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileAccessIterator2dThreadTile_3_01Shape__7327fa15996bcb8502cdfcc192350fe1.html#a02967da59cb489f75bdb919a3dab6588">Layout</a> typedef</td><td class="entry"><a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileAccessIterator2dThreadTile_3_01Shape__7327fa15996bcb8502cdfcc192350fe1.html">cutlass::transform::threadblock::PredicatedTileAccessIterator2dThreadTile&lt; Shape_, Element_, layout::RowMajor, AdvanceRank, ThreadMap_, AccessType_ &gt;</a></td><td class="entry"></td></tr>
117
+ <tr><td class="entry"><a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileAccessIterator2dThreadTile_3_01Shape__7327fa15996bcb8502cdfcc192350fe1.html#affe1f1064aaf7d829f7b06c4ac933544">LongIndex</a> typedef</td><td class="entry"><a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileAccessIterator2dThreadTile_3_01Shape__7327fa15996bcb8502cdfcc192350fe1.html">cutlass::transform::threadblock::PredicatedTileAccessIterator2dThreadTile&lt; Shape_, Element_, layout::RowMajor, AdvanceRank, ThreadMap_, AccessType_ &gt;</a></td><td class="entry"></td></tr>
118
+ <tr class="even"><td class="entry"><a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileAccessIterator2dThreadTile_3_01Shape__7327fa15996bcb8502cdfcc192350fe1.html#ac8b5b1def7e2de1da7faf02fbf04e2ea">Mask</a> typedef</td><td class="entry"><a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileAccessIterator2dThreadTile_3_01Shape__7327fa15996bcb8502cdfcc192350fe1.html">cutlass::transform::threadblock::PredicatedTileAccessIterator2dThreadTile&lt; Shape_, Element_, layout::RowMajor, AdvanceRank, ThreadMap_, AccessType_ &gt;</a></td><td class="entry"></td></tr>
119
+ <tr><td class="entry"><a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileAccessIterator2dThreadTile_3_01Shape__7327fa15996bcb8502cdfcc192350fe1.html#a3bd6652eb4a036086479e0d501432d4c">NonConstPointer</a> typedef</td><td class="entry"><a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileAccessIterator2dThreadTile_3_01Shape__7327fa15996bcb8502cdfcc192350fe1.html">cutlass::transform::threadblock::PredicatedTileAccessIterator2dThreadTile&lt; Shape_, Element_, layout::RowMajor, AdvanceRank, ThreadMap_, AccessType_ &gt;</a></td><td class="entry"></td></tr>
120
+ <tr class="even"><td class="entry"><a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileAccessIterator2dThreadTile_3_01Shape__7327fa15996bcb8502cdfcc192350fe1.html#aa8ea4f4cf66de36f0d72717540d229cc">operator++</a>()</td><td class="entry"><a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileAccessIterator2dThreadTile_3_01Shape__7327fa15996bcb8502cdfcc192350fe1.html">cutlass::transform::threadblock::PredicatedTileAccessIterator2dThreadTile&lt; Shape_, Element_, layout::RowMajor, AdvanceRank, ThreadMap_, AccessType_ &gt;</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
121
+ <tr><td class="entry"><a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileAccessIterator2dThreadTile_3_01Shape__7327fa15996bcb8502cdfcc192350fe1.html#af4aaf0df9b95f857d2190259c6ef7456">operator++</a>(int)</td><td class="entry"><a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileAccessIterator2dThreadTile_3_01Shape__7327fa15996bcb8502cdfcc192350fe1.html">cutlass::transform::threadblock::PredicatedTileAccessIterator2dThreadTile&lt; Shape_, Element_, layout::RowMajor, AdvanceRank, ThreadMap_, AccessType_ &gt;</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
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+ <tr class="even"><td class="entry"><a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileAccessIterator2dThreadTile_3_01Shape__7327fa15996bcb8502cdfcc192350fe1.html#ad6092b73dd2ef54f61c2c1baa911f9c5">Pointer</a> typedef</td><td class="entry"><a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileAccessIterator2dThreadTile_3_01Shape__7327fa15996bcb8502cdfcc192350fe1.html">cutlass::transform::threadblock::PredicatedTileAccessIterator2dThreadTile&lt; Shape_, Element_, layout::RowMajor, AdvanceRank, ThreadMap_, AccessType_ &gt;</a></td><td class="entry"></td></tr>
123
+ <tr><td class="entry"><a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileAccessIterator2dThreadTile_3_01Shape__7327fa15996bcb8502cdfcc192350fe1.html#ae2cf64f40d954803ad851128c785dc07">PredicatedTileAccessIterator2dThreadTile</a>(Params const &amp;params, Pointer pointer, TensorCoord extent, int thread_id, TensorCoord const &amp;threadblock_offset)</td><td class="entry"><a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileAccessIterator2dThreadTile_3_01Shape__7327fa15996bcb8502cdfcc192350fe1.html">cutlass::transform::threadblock::PredicatedTileAccessIterator2dThreadTile&lt; Shape_, Element_, layout::RowMajor, AdvanceRank, ThreadMap_, AccessType_ &gt;</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
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+ <tr class="even"><td class="entry"><a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileAccessIterator2dThreadTile_3_01Shape__7327fa15996bcb8502cdfcc192350fe1.html#a6735ad678e1efcd3949e36e65a50f9eb">PredicatedTileAccessIterator2dThreadTile</a>(Params const &amp;params, Pointer pointer, TensorCoord extent, int thread_id)</td><td class="entry"><a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileAccessIterator2dThreadTile_3_01Shape__7327fa15996bcb8502cdfcc192350fe1.html">cutlass::transform::threadblock::PredicatedTileAccessIterator2dThreadTile&lt; Shape_, Element_, layout::RowMajor, AdvanceRank, ThreadMap_, AccessType_ &gt;</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
125
+ <tr><td class="entry"><a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileAccessIterator2dThreadTile_3_01Shape__7327fa15996bcb8502cdfcc192350fe1.html#af66656191a551c9d83ab5f4a024a220d">set_iteration_index</a>(int index)</td><td class="entry"><a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileAccessIterator2dThreadTile_3_01Shape__7327fa15996bcb8502cdfcc192350fe1.html">cutlass::transform::threadblock::PredicatedTileAccessIterator2dThreadTile&lt; Shape_, Element_, layout::RowMajor, AdvanceRank, ThreadMap_, AccessType_ &gt;</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
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+ <tr class="even"><td class="entry"><a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileAccessIterator2dThreadTile_3_01Shape__7327fa15996bcb8502cdfcc192350fe1.html#a5138a9a366e5ae0dcf3c2f3f835826c3">set_mask</a>(Mask const &amp;mask)</td><td class="entry"><a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileAccessIterator2dThreadTile_3_01Shape__7327fa15996bcb8502cdfcc192350fe1.html">cutlass::transform::threadblock::PredicatedTileAccessIterator2dThreadTile&lt; Shape_, Element_, layout::RowMajor, AdvanceRank, ThreadMap_, AccessType_ &gt;</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
127
+ <tr><td class="entry"><a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileAccessIterator2dThreadTile_3_01Shape__7327fa15996bcb8502cdfcc192350fe1.html#ac085ff9b6adacf6ba1c5991f17a07621">Shape</a> typedef</td><td class="entry"><a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileAccessIterator2dThreadTile_3_01Shape__7327fa15996bcb8502cdfcc192350fe1.html">cutlass::transform::threadblock::PredicatedTileAccessIterator2dThreadTile&lt; Shape_, Element_, layout::RowMajor, AdvanceRank, ThreadMap_, AccessType_ &gt;</a></td><td class="entry"></td></tr>
128
+ <tr class="even"><td class="entry"><a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileAccessIterator2dThreadTile_3_01Shape__7327fa15996bcb8502cdfcc192350fe1.html#aa641697e67f63cb98d31526105fd2cf0">TensorCoord</a> typedef</td><td class="entry"><a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileAccessIterator2dThreadTile_3_01Shape__7327fa15996bcb8502cdfcc192350fe1.html">cutlass::transform::threadblock::PredicatedTileAccessIterator2dThreadTile&lt; Shape_, Element_, layout::RowMajor, AdvanceRank, ThreadMap_, AccessType_ &gt;</a></td><td class="entry"></td></tr>
129
+ <tr><td class="entry"><a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileAccessIterator2dThreadTile_3_01Shape__7327fa15996bcb8502cdfcc192350fe1.html#a0ac3713365d792f57f8a6e2ccda39365">TensorRef</a> typedef</td><td class="entry"><a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileAccessIterator2dThreadTile_3_01Shape__7327fa15996bcb8502cdfcc192350fe1.html">cutlass::transform::threadblock::PredicatedTileAccessIterator2dThreadTile&lt; Shape_, Element_, layout::RowMajor, AdvanceRank, ThreadMap_, AccessType_ &gt;</a></td><td class="entry"></td></tr>
130
+ <tr class="even"><td class="entry"><a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileAccessIterator2dThreadTile_3_01Shape__7327fa15996bcb8502cdfcc192350fe1.html#a813d382d7295e126b4fcffc356bc9b76">TensorView</a> typedef</td><td class="entry"><a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileAccessIterator2dThreadTile_3_01Shape__7327fa15996bcb8502cdfcc192350fe1.html">cutlass::transform::threadblock::PredicatedTileAccessIterator2dThreadTile&lt; Shape_, Element_, layout::RowMajor, AdvanceRank, ThreadMap_, AccessType_ &gt;</a></td><td class="entry"></td></tr>
131
+ <tr><td class="entry"><a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileAccessIterator2dThreadTile_3_01Shape__7327fa15996bcb8502cdfcc192350fe1.html#adabe08512db83a0248d282fcd250eeb0">ThreadMap</a> typedef</td><td class="entry"><a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileAccessIterator2dThreadTile_3_01Shape__7327fa15996bcb8502cdfcc192350fe1.html">cutlass::transform::threadblock::PredicatedTileAccessIterator2dThreadTile&lt; Shape_, Element_, layout::RowMajor, AdvanceRank, ThreadMap_, AccessType_ &gt;</a></td><td class="entry"></td></tr>
132
+ <tr class="even"><td class="entry"><a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileAccessIterator2dThreadTile_3_01Shape__7327fa15996bcb8502cdfcc192350fe1.html#ae9d4e095f7008e41aa971d9a5f92ab8c">UnderlyingIterator</a> typedef</td><td class="entry"><a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileAccessIterator2dThreadTile_3_01Shape__7327fa15996bcb8502cdfcc192350fe1.html">cutlass::transform::threadblock::PredicatedTileAccessIterator2dThreadTile&lt; Shape_, Element_, layout::RowMajor, AdvanceRank, ThreadMap_, AccessType_ &gt;</a></td><td class="entry"></td></tr>
133
+ <tr><td class="entry"><a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileAccessIterator2dThreadTile_3_01Shape__7327fa15996bcb8502cdfcc192350fe1.html#adb5537726f507544df0167a6fcd0fcd6">valid</a>()</td><td class="entry"><a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileAccessIterator2dThreadTile_3_01Shape__7327fa15996bcb8502cdfcc192350fe1.html">cutlass::transform::threadblock::PredicatedTileAccessIterator2dThreadTile&lt; Shape_, Element_, layout::RowMajor, AdvanceRank, ThreadMap_, AccessType_ &gt;</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
134
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sglang_repo/sgl-kernel/3rdparty/flashinfer/3rdparty/cutlass/docs/classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileIterator_3_01Shape___00_01Element___00f5d8ee719cad9052f71bb9bd0fa63021.html ADDED
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+ <li class="navelem"><a class="el" href="namespacecutlass.html">cutlass</a></li><li class="navelem"><a class="el" href="namespacecutlass_1_1transform.html">transform</a></li><li class="navelem"><a class="el" href="namespacecutlass_1_1transform_1_1threadblock.html">threadblock</a></li><li class="navelem"><a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileIterator_3_01Shape___00_01Element___00f6b3a9dfab5e7c72d5233f7e5e6e3b9b.html">PredicatedTileIterator&lt; Shape_, Element_, layout::ColumnMajorInterleaved&lt; InterleavedK &gt;, AdvanceRank, ThreadMap_, AccessSize &gt;</a></li><li class="navelem"><a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileIterator_3_01Shape___00_01Element___00ebd1a63351e1085d0b718582ec7b06c8.html">Params</a></li> </ul>
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+ <div class="title">cutlass::transform::threadblock::PredicatedTileIterator&lt; Shape_, Element_, layout::ColumnMajorInterleaved&lt; InterleavedK &gt;, AdvanceRank, ThreadMap_, AccessSize &gt;::Params Member List</div> </div>
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+ <p>This is the complete list of members for <a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileIterator_3_01Shape___00_01Element___00ebd1a63351e1085d0b718582ec7b06c8.html">cutlass::transform::threadblock::PredicatedTileIterator&lt; Shape_, Element_, layout::ColumnMajorInterleaved&lt; InterleavedK &gt;, AdvanceRank, ThreadMap_, AccessSize &gt;::Params</a>, including all inherited members.</p>
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+ <table class="directory">
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+ <tr class="even"><td class="entry"><a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileIterator_3_01Shape___00_01Element___00ebd1a63351e1085d0b718582ec7b06c8.html#ae36baf85b0cc499418c5c0c6622e2b8a">Params</a>()</td><td class="entry"><a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileIterator_3_01Shape___00_01Element___00ebd1a63351e1085d0b718582ec7b06c8.html">cutlass::transform::threadblock::PredicatedTileIterator&lt; Shape_, Element_, layout::ColumnMajorInterleaved&lt; InterleavedK &gt;, AdvanceRank, ThreadMap_, AccessSize &gt;::Params</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
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+ <tr><td class="entry"><a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileIterator_3_01Shape___00_01Element___00ebd1a63351e1085d0b718582ec7b06c8.html#a4787959c38114875acb60e554141860b">Params</a>(Layout const &amp;layout)</td><td class="entry"><a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileIterator_3_01Shape___00_01Element___00ebd1a63351e1085d0b718582ec7b06c8.html">cutlass::transform::threadblock::PredicatedTileIterator&lt; Shape_, Element_, layout::ColumnMajorInterleaved&lt; InterleavedK &gt;, AdvanceRank, ThreadMap_, AccessSize &gt;::Params</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
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+ <a href="default__epilogue__complex__tensor__op_8h.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span>&#160;<span class="comment">/***************************************************************************************************</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span>&#160;<span class="comment"> * Copyright (c) 2017-2019, NVIDIA CORPORATION. All rights reserved.</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span>&#160;<span class="comment"> * Redistribution and use in source and binary forms, with or without modification, are permitted</span></div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span>&#160;<span class="comment"> * provided that the following conditions are met:</span></div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span>&#160;<span class="comment"> * * Redistributions of source code must retain the above copyright notice, this list of</span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span>&#160;<span class="comment"> * conditions and the following disclaimer.</span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span>&#160;<span class="comment"> * * Redistributions in binary form must reproduce the above copyright notice, this list of</span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span>&#160;<span class="comment"> * conditions and the following disclaimer in the documentation and/or other materials</span></div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span>&#160;<span class="comment"> * provided with the distribution.</span></div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span>&#160;<span class="comment"> * * Neither the name of the NVIDIA CORPORATION nor the names of its contributors may be used</span></div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span>&#160;<span class="comment"> * to endorse or promote products derived from this software without specific prior written</span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span>&#160;<span class="comment"> * permission.</span></div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span>&#160;<span class="comment"> * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS &quot;AS IS&quot; AND ANY EXPRESS OR</span></div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span>&#160;<span class="comment"> * IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND</span></div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span>&#160;<span class="comment"> * FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. 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href="numeric__types_8h.html">cutlass/numeric_types.h</a>&quot;</span></div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="array_8h.html">cutlass/array.h</a>&quot;</span></div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>&#160;</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="include_2cutlass_2gemm_2gemm_8h.html">cutlass/gemm/gemm.h</a>&quot;</span></div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>&#160;</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="linear__combination_8h.html">cutlass/epilogue/thread/linear_combination.h</a>&quot;</span></div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="conversion__op_8h.html">cutlass/epilogue/thread/conversion_op.h</a>&quot;</span></div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="reduction__op_8h.html">cutlass/epilogue/thread/reduction_op.h</a>&quot;</span></div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>&#160;</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="regular__tile__iterator__pitch__linear_8h.html">cutlass/transform/threadblock/regular_tile_iterator_pitch_linear.h</a>&quot;</span></div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>&#160;</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="fragment__iterator__complex__tensor__op_8h.html">cutlass/epilogue/warp/fragment_iterator_complex_tensor_op.h</a>&quot;</span></div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="tile__iterator__tensor__op_8h.html">cutlass/epilogue/warp/tile_iterator_tensor_op.h</a>&quot;</span></div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="default__thread__map__tensor__op_8h.html">cutlass/epilogue/threadblock/default_thread_map_tensor_op.h</a>&quot;</span></div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="epilogue_2threadblock_2predicated__tile__iterator_8h.html">cutlass/epilogue/threadblock/predicated_tile_iterator.h</a>&quot;</span></div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="shared__load__iterator_8h.html">cutlass/epilogue/threadblock/shared_load_iterator.h</a>&quot;</span></div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>&#160;</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="epilogue_8h.html">cutlass/epilogue/threadblock/epilogue.h</a>&quot;</span></div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>&#160;</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>&#160;</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>&#160;<span class="keyword">namespace </span><a class="code" href="namespacecutlass.html">cutlass</a> {</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>&#160;<span class="keyword">namespace </span>epilogue {</div><div class="line"><a name="l00059"></a><span class="lineno"><a class="line" href="namespacecutlass_1_1epilogue_1_1threadblock.html"> 59</a></span>&#160;<span class="keyword">namespace </span>threadblock {</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>&#160;</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>&#160;</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>&#160;<span class="keyword">template</span> &lt;</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>&#160; <span class="keyword">typename</span> Shape_,</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>&#160; <span class="keyword">typename</span> WarpMmaTensorOp_,</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>&#160; <span class="keywordtype">int</span> PartitionsK,</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>&#160; <span class="keyword">typename</span> OutputOp_,</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>&#160; <span class="keywordtype">int</span> ElementsPerAccess</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>&#160;&gt;</div><div class="line"><a name="l00071"></a><span class="lineno"><a class="line" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html"> 71</a></span>&#160;<span class="keyword">struct </span><a class="code" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html">DefaultEpilogueComplexTensorOp</a> {</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>&#160;</div><div class="line"><a name="l00073"></a><span class="lineno"><a class="line" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a3103ac8f979c182f26c3b80ce15643f6"> 73</a></span>&#160; <span class="keyword">using</span> <a class="code" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a3103ac8f979c182f26c3b80ce15643f6">Shape</a> = Shape_;</div><div class="line"><a name="l00074"></a><span class="lineno"><a class="line" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a9323e876327a9bfe0f277b78c787ec01"> 74</a></span>&#160; <span class="keyword">using</span> <a class="code" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a9323e876327a9bfe0f277b78c787ec01">WarpMmaTensorOp</a> = WarpMmaTensorOp_;</div><div class="line"><a name="l00075"></a><span class="lineno"><a class="line" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a6a7770417159c242d8252998aebfa96e"> 75</a></span>&#160; <span class="keyword">static</span> <span class="keywordtype">int</span> <span class="keyword">const</span> <a class="code" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a6a7770417159c242d8252998aebfa96e">kPartitionsK</a> = PartitionsK;</div><div class="line"><a name="l00076"></a><span class="lineno"><a class="line" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a517049715fcabdb536f278604477829e"> 76</a></span>&#160; <span class="keyword">using</span> <a class="code" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a517049715fcabdb536f278604477829e">OutputOp</a> = OutputOp_;</div><div class="line"><a name="l00077"></a><span class="lineno"><a class="line" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#afc3c42f94722a38fbf23436fc16320e5"> 77</a></span>&#160; <span class="keyword">static</span> <span class="keywordtype">int</span> <span class="keyword">const</span> <a class="code" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#afc3c42f94722a38fbf23436fc16320e5">kElementsPerAccess</a> = ElementsPerAccess;</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>&#160;</div><div class="line"><a name="l00079"></a><span class="lineno"><a class="line" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a1021107776d67cf428dfd799bbaaa02f"> 79</a></span>&#160; <span class="keyword">using</span> <a class="code" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a1021107776d67cf428dfd799bbaaa02f">ElementOutput</a> = <span class="keyword">typename</span> OutputOp::ElementOutput;</div><div class="line"><a name="l00080"></a><span class="lineno"><a class="line" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a89a49a6d25f358cffe669ece2abe2f11"> 80</a></span>&#160; <span class="keyword">using</span> <a class="code" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a89a49a6d25f358cffe669ece2abe2f11">LayoutC</a> = <span class="keyword">typename</span> WarpMmaTensorOp::LayoutC;</div><div class="line"><a name="l00081"></a><span class="lineno"><a class="line" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a43ad144aa28bab769fa744744eb0321a"> 81</a></span>&#160; <span class="keyword">using</span> <a class="code" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a43ad144aa28bab769fa744744eb0321a">ElementAccumulator</a> = <span class="keyword">typename</span> WarpMmaTensorOp::ElementC;</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>&#160;</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>&#160; <span class="comment">//</span></div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>&#160; <span class="comment">// Thread map</span></div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>&#160; <span class="comment">//</span></div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>&#160;</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>&#160; <span class="keyword">using</span> <a class="code" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#adb357c79d059162f558cfeab52484fca">OutputTileThreadMap</a> = <span class="keyword">typename</span> <a class="code" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapTensorOp.html">cutlass::epilogue::threadblock::DefaultThreadMapTensorOp</a>&lt;</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>&#160; <a class="code" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a3103ac8f979c182f26c3b80ce15643f6">Shape</a>,</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>&#160; <span class="keyword">typename</span> WarpMmaTensorOp::Shape,</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>&#160; <a class="code" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a6a7770417159c242d8252998aebfa96e">kPartitionsK</a>,</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>&#160; <a class="code" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a1021107776d67cf428dfd799bbaaa02f">ElementOutput</a>,</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>&#160; kElementsPerAccess</div><div class="line"><a name="l00093"></a><span class="lineno"><a class="line" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#adb357c79d059162f558cfeab52484fca"> 93</a></span>&#160; &gt;::Type;</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>&#160;</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>&#160; <span class="keyword">using</span> <a class="code" href="classcutlass_1_1epilogue_1_1threadblock_1_1PredicatedTileIterator.html">OutputTileIterator</a> = <a class="code" href="classcutlass_1_1epilogue_1_1threadblock_1_1PredicatedTileIterator.html">cutlass::epilogue::threadblock::PredicatedTileIterator</a>&lt;</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>&#160; <a class="code" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#adb357c79d059162f558cfeab52484fca">OutputTileThreadMap</a>,</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>&#160; ElementOutput</div><div class="line"><a name="l00098"></a><span class="lineno"><a class="line" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#ab421b49d591111d62eac560f8b96c10a"> 98</a></span>&#160; &gt;;</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>&#160;</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>&#160; <span class="keyword">using</span> <a class="code" href="classcutlass_1_1epilogue_1_1warp_1_1FragmentIteratorComplexTensorOp.html">AccumulatorFragmentIterator</a> = <a class="code" href="classcutlass_1_1epilogue_1_1warp_1_1FragmentIteratorComplexTensorOp.html">cutlass::epilogue::warp::FragmentIteratorComplexTensorOp</a>&lt;</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>&#160; <span class="keyword">typename</span> WarpMmaTensorOp::Shape,</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>&#160; <span class="keyword">typename</span> WarpMmaTensorOp::Policy::Operator::Shape,</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>&#160; <span class="keyword">typename</span> WarpMmaTensorOp::Policy::Operator::ElementC,</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>&#160; <span class="keyword">typename</span> WarpMmaTensorOp::Policy::Operator::FragmentC,</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>&#160; <a class="code" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a89a49a6d25f358cffe669ece2abe2f11">LayoutC</a></div><div class="line"><a name="l00106"></a><span class="lineno"><a class="line" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a9c88165210cc6535336db0e5043fa10f"> 106</a></span>&#160; &gt;;</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>&#160;</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>&#160; <span class="keyword">using</span> <a class="code" href="classcutlass_1_1epilogue_1_1warp_1_1TileIteratorTensorOp.html">WarpTileIterator</a> = <a class="code" href="classcutlass_1_1epilogue_1_1warp_1_1TileIteratorTensorOp.html">cutlass::epilogue::warp::TileIteratorTensorOp</a>&lt;</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>&#160; <span class="keyword">typename</span> WarpMmaTensorOp::Shape,</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>&#160; <span class="keyword">typename</span> WarpMmaTensorOp::Policy::Operator::Shape,</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>&#160; <a class="code" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a43ad144aa28bab769fa744744eb0321a">ElementAccumulator</a>,</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>&#160; <a class="code" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a89a49a6d25f358cffe669ece2abe2f11">LayoutC</a></div><div class="line"><a name="l00113"></a><span class="lineno"><a class="line" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#ac41f55deccd93d0ca21c75bd1b311658"> 113</a></span>&#160; &gt;;</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>&#160;</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>&#160; <span class="keyword">using</span> <a class="code" href="classcutlass_1_1epilogue_1_1threadblock_1_1SharedLoadIterator.html">SharedLoadIterator</a> = <a class="code" href="classcutlass_1_1epilogue_1_1threadblock_1_1SharedLoadIterator.html">cutlass::epilogue::threadblock::SharedLoadIterator</a>&lt;</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>&#160; <span class="keyword">typename</span> OutputTileThreadMap::CompactedThreadMap,</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>&#160; ElementAccumulator</div><div class="line"><a name="l00118"></a><span class="lineno"><a class="line" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#af85ee3278368759b9876c07124b09ffd"> 118</a></span>&#160; &gt;;</div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>&#160;</div><div class="line"><a name="l00121"></a><span class="lineno"><a class="line" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a6685913f5820773e1b26ea2eb76866cd"> 121</a></span>&#160; <span class="keyword">using</span> <a class="code" href="structcutlass_1_1MatrixShape.html">Padding</a> = <a class="code" href="structcutlass_1_1MatrixShape.html">cutlass::MatrixShape&lt;0, 0&gt;</a>;</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>&#160;</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>&#160; <span class="comment">//</span></div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>&#160; <span class="comment">// Define the epilogue</span></div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>&#160; <span class="comment">//</span></div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>&#160; <span class="keyword">using</span> <a class="code" href="classcutlass_1_1epilogue_1_1threadblock_1_1Epilogue.html">Epilogue</a> = <a class="code" href="classcutlass_1_1epilogue_1_1threadblock_1_1Epilogue.html">cutlass::epilogue::threadblock::Epilogue</a>&lt;</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>&#160; <a class="code" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a3103ac8f979c182f26c3b80ce15643f6">Shape</a>,</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>&#160; <a class="code" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a9323e876327a9bfe0f277b78c787ec01">WarpMmaTensorOp</a>,</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>&#160; <a class="code" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a6a7770417159c242d8252998aebfa96e">kPartitionsK</a>,</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>&#160; <a class="code" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#ab421b49d591111d62eac560f8b96c10a">OutputTileIterator</a>,</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span>&#160; <a class="code" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a9c88165210cc6535336db0e5043fa10f">AccumulatorFragmentIterator</a>,</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>&#160; <a class="code" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#ac41f55deccd93d0ca21c75bd1b311658">WarpTileIterator</a>,</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>&#160; <a class="code" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#af85ee3278368759b9876c07124b09ffd">SharedLoadIterator</a>,</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>&#160; <a class="code" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a517049715fcabdb536f278604477829e">OutputOp</a>,</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>&#160; <a class="code" href="structcutlass_1_1MatrixShape.html">Padding</a></div><div class="line"><a name="l00136"></a><span class="lineno"><a class="line" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#ae035b28fb369d5eafa086e1fcb8b6b0f"> 136</a></span>&#160; &gt;;</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>&#160;};</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span>&#160;</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>&#160;</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>&#160;} <span class="comment">// namespace threadblock</span></div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>&#160;} <span class="comment">// namespace epilogue</span></div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>&#160;} <span class="comment">// namespace cutlass</span></div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>&#160;</div><div class="ttc" id="default__thread__map__tensor__op_8h_html"><div class="ttname"><a href="default__thread__map__tensor__op_8h.html">default_thread_map_tensor_op.h</a></div></div>
102
+ <div class="ttc" id="structcutlass_1_1MatrixShape_html"><div class="ttname"><a href="structcutlass_1_1MatrixShape.html">cutlass::MatrixShape</a></div><div class="ttdoc">Describes the size of a matrix tile. </div><div class="ttdef"><b>Definition:</b> matrix_shape.h:42</div></div>
103
+ <div class="ttc" id="regular__tile__iterator__pitch__linear_8h_html"><div class="ttname"><a href="regular__tile__iterator__pitch__linear_8h.html">regular_tile_iterator_pitch_linear.h</a></div><div class="ttdoc">Templates implementing loading of tiles from pitch-linear rank=2 tensors. </div></div>
104
+ <div class="ttc" id="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp_html_a1021107776d67cf428dfd799bbaaa02f"><div class="ttname"><a href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a1021107776d67cf428dfd799bbaaa02f">cutlass::epilogue::threadblock::DefaultEpilogueComplexTensorOp::ElementOutput</a></div><div class="ttdeci">typename OutputOp::ElementOutput ElementOutput</div><div class="ttdef"><b>Definition:</b> default_epilogue_complex_tensor_op.h:79</div></div>
105
+ <div class="ttc" id="namespacecutlass_html"><div class="ttname"><a href="namespacecutlass.html">cutlass</a></div><div class="ttdef"><b>Definition:</b> aligned_buffer.h:35</div></div>
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+ <div class="ttc" id="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp_html_a6a7770417159c242d8252998aebfa96e"><div class="ttname"><a href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a6a7770417159c242d8252998aebfa96e">cutlass::epilogue::threadblock::DefaultEpilogueComplexTensorOp::kPartitionsK</a></div><div class="ttdeci">static int const kPartitionsK</div><div class="ttdef"><b>Definition:</b> default_epilogue_complex_tensor_op.h:75</div></div>
107
+ <div class="ttc" id="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp_html_a89a49a6d25f358cffe669ece2abe2f11"><div class="ttname"><a href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a89a49a6d25f358cffe669ece2abe2f11">cutlass::epilogue::threadblock::DefaultEpilogueComplexTensorOp::LayoutC</a></div><div class="ttdeci">typename WarpMmaTensorOp::LayoutC LayoutC</div><div class="ttdef"><b>Definition:</b> default_epilogue_complex_tensor_op.h:80</div></div>
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+ <div class="ttc" id="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp_html_adb357c79d059162f558cfeab52484fca"><div class="ttname"><a href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#adb357c79d059162f558cfeab52484fca">cutlass::epilogue::threadblock::DefaultEpilogueComplexTensorOp::OutputTileThreadMap</a></div><div class="ttdeci">typename cutlass::epilogue::threadblock::DefaultThreadMapTensorOp&lt; Shape, typename WarpMmaTensorOp::Shape, kPartitionsK, ElementOutput, kElementsPerAccess &gt;::Type OutputTileThreadMap</div><div class="ttdef"><b>Definition:</b> default_epilogue_complex_tensor_op.h:93</div></div>
109
+ <div class="ttc" id="epilogue_2threadblock_2predicated__tile__iterator_8h_html"><div class="ttname"><a href="epilogue_2threadblock_2predicated__tile__iterator_8h.html">predicated_tile_iterator.h</a></div><div class="ttdoc">Epilogue for threadblock scoped GEMMs using Tensor Ops. </div></div>
110
+ <div class="ttc" id="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp_html_ac41f55deccd93d0ca21c75bd1b311658"><div class="ttname"><a href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#ac41f55deccd93d0ca21c75bd1b311658">cutlass::epilogue::threadblock::DefaultEpilogueComplexTensorOp::WarpTileIterator</a></div><div class="ttdeci">cutlass::epilogue::warp::TileIteratorTensorOp&lt; typename WarpMmaTensorOp::Shape, typename WarpMmaTensorOp::Policy::Operator::Shape, ElementAccumulator, LayoutC &gt; WarpTileIterator</div><div class="ttdef"><b>Definition:</b> default_epilogue_complex_tensor_op.h:113</div></div>
111
+ <div class="ttc" id="include_2cutlass_2gemm_2gemm_8h_html"><div class="ttname"><a href="include_2cutlass_2gemm_2gemm_8h.html">gemm.h</a></div><div class="ttdoc">Defines common types used for all GEMM-like operators. </div></div>
112
+ <div class="ttc" id="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp_html_afc3c42f94722a38fbf23436fc16320e5"><div class="ttname"><a href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#afc3c42f94722a38fbf23436fc16320e5">cutlass::epilogue::threadblock::DefaultEpilogueComplexTensorOp::kElementsPerAccess</a></div><div class="ttdeci">static int const kElementsPerAccess</div><div class="ttdef"><b>Definition:</b> default_epilogue_complex_tensor_op.h:77</div></div>
113
+ <div class="ttc" id="conversion__op_8h_html"><div class="ttname"><a href="conversion__op_8h.html">conversion_op.h</a></div><div class="ttdoc">Functor performing conversion operations used by epilogues. </div></div>
114
+ <div class="ttc" id="fragment__iterator__complex__tensor__op_8h_html"><div class="ttname"><a href="fragment__iterator__complex__tensor__op_8h.html">fragment_iterator_complex_tensor_op.h</a></div><div class="ttdoc">This defines a &quot;fragment&quot; iterator for visiting the fragments of an accumulator tile that participate...</div></div>
115
+ <div class="ttc" id="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp_html_af85ee3278368759b9876c07124b09ffd"><div class="ttname"><a href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#af85ee3278368759b9876c07124b09ffd">cutlass::epilogue::threadblock::DefaultEpilogueComplexTensorOp::SharedLoadIterator</a></div><div class="ttdeci">cutlass::epilogue::threadblock::SharedLoadIterator&lt; typename OutputTileThreadMap::CompactedThreadMap, ElementAccumulator &gt; SharedLoadIterator</div><div class="ttdef"><b>Definition:</b> default_epilogue_complex_tensor_op.h:118</div></div>
116
+ <div class="ttc" id="array_8h_html"><div class="ttname"><a href="array_8h.html">array.h</a></div><div class="ttdoc">Statically sized array of elements that accommodates all CUTLASS-supported numeric types and is safe ...</div></div>
117
+ <div class="ttc" id="linear__combination_8h_html"><div class="ttname"><a href="linear__combination_8h.html">linear_combination.h</a></div><div class="ttdoc">Functor performing linear combination operations used by epilogues. </div></div>
118
+ <div class="ttc" id="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp_html"><div class="ttname"><a href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html">cutlass::epilogue::threadblock::DefaultEpilogueComplexTensorOp</a></div><div class="ttdoc">Defines sensible defaults for epilogues for TensorOps. </div><div class="ttdef"><b>Definition:</b> default_epilogue_complex_tensor_op.h:71</div></div>
119
+ <div class="ttc" id="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp_html_a3103ac8f979c182f26c3b80ce15643f6"><div class="ttname"><a href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a3103ac8f979c182f26c3b80ce15643f6">cutlass::epilogue::threadblock::DefaultEpilogueComplexTensorOp::Shape</a></div><div class="ttdeci">Shape_ Shape</div><div class="ttdef"><b>Definition:</b> default_epilogue_complex_tensor_op.h:73</div></div>
120
+ <div class="ttc" id="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp_html_a9323e876327a9bfe0f277b78c787ec01"><div class="ttname"><a href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a9323e876327a9bfe0f277b78c787ec01">cutlass::epilogue::threadblock::DefaultEpilogueComplexTensorOp::WarpMmaTensorOp</a></div><div class="ttdeci">WarpMmaTensorOp_ WarpMmaTensorOp</div><div class="ttdef"><b>Definition:</b> default_epilogue_complex_tensor_op.h:74</div></div>
121
+ <div class="ttc" id="classcutlass_1_1epilogue_1_1warp_1_1FragmentIteratorComplexTensorOp_html"><div class="ttname"><a href="classcutlass_1_1epilogue_1_1warp_1_1FragmentIteratorComplexTensorOp.html">cutlass::epilogue::warp::FragmentIteratorComplexTensorOp</a></div><div class="ttdef"><b>Definition:</b> fragment_iterator_complex_tensor_op.h:61</div></div>
122
+ <div class="ttc" id="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp_html_a9c88165210cc6535336db0e5043fa10f"><div class="ttname"><a href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a9c88165210cc6535336db0e5043fa10f">cutlass::epilogue::threadblock::DefaultEpilogueComplexTensorOp::AccumulatorFragmentIterator</a></div><div class="ttdeci">cutlass::epilogue::warp::FragmentIteratorComplexTensorOp&lt; typename WarpMmaTensorOp::Shape, typename WarpMmaTensorOp::Policy::Operator::Shape, typename WarpMmaTensorOp::Policy::Operator::ElementC, typename WarpMmaTensorOp::Policy::Operator::FragmentC, LayoutC &gt; AccumulatorFragmentIterator</div><div class="ttdef"><b>Definition:</b> default_epilogue_complex_tensor_op.h:106</div></div>
123
+ <div class="ttc" id="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapTensorOp_html"><div class="ttname"><a href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapTensorOp.html">cutlass::epilogue::threadblock::DefaultThreadMapTensorOp</a></div><div class="ttdoc">Defines the optimal thread map for TensorOp accumulator layouts. </div><div class="ttdef"><b>Definition:</b> default_thread_map_tensor_op.h:52</div></div>
124
+ <div class="ttc" id="numeric__types_8h_html"><div class="ttname"><a href="numeric__types_8h.html">numeric_types.h</a></div><div class="ttdoc">Top-level include for all CUTLASS numeric types. </div></div>
125
+ <div class="ttc" id="classcutlass_1_1epilogue_1_1warp_1_1TileIteratorTensorOp_html"><div class="ttname"><a href="classcutlass_1_1epilogue_1_1warp_1_1TileIteratorTensorOp.html">cutlass::epilogue::warp::TileIteratorTensorOp</a></div><div class="ttdoc">Template for reading and writing tiles of accumulators to shared memory. </div><div class="ttdef"><b>Definition:</b> tile_iterator_tensor_op.h:52</div></div>
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+ <div class="ttc" id="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp_html_ab421b49d591111d62eac560f8b96c10a"><div class="ttname"><a href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#ab421b49d591111d62eac560f8b96c10a">cutlass::epilogue::threadblock::DefaultEpilogueComplexTensorOp::OutputTileIterator</a></div><div class="ttdeci">cutlass::epilogue::threadblock::PredicatedTileIterator&lt; OutputTileThreadMap, ElementOutput &gt; OutputTileIterator</div><div class="ttdef"><b>Definition:</b> default_epilogue_complex_tensor_op.h:98</div></div>
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+ <div class="ttc" id="shared__load__iterator_8h_html"><div class="ttname"><a href="shared__load__iterator_8h.html">shared_load_iterator.h</a></div><div class="ttdoc">Epilogue for threadblock scoped GEMMs using Tensor Ops. </div></div>
128
+ <div class="ttc" id="tile__iterator__tensor__op_8h_html"><div class="ttname"><a href="tile__iterator__tensor__op_8h.html">tile_iterator_tensor_op.h</a></div></div>
129
+ <div class="ttc" id="classcutlass_1_1epilogue_1_1threadblock_1_1Epilogue_html"><div class="ttname"><a href="classcutlass_1_1epilogue_1_1threadblock_1_1Epilogue.html">cutlass::epilogue::threadblock::Epilogue</a></div><div class="ttdoc">Epilogue operator without splitk. </div><div class="ttdef"><b>Definition:</b> epilogue.h:74</div></div>
130
+ <div class="ttc" id="epilogue_8h_html"><div class="ttname"><a href="epilogue_8h.html">epilogue.h</a></div><div class="ttdoc">Epilogue for threadblock scoped GEMMs using Tensor Ops. </div></div>
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+ <div class="ttc" id="classcutlass_1_1epilogue_1_1threadblock_1_1PredicatedTileIterator_html"><div class="ttname"><a href="classcutlass_1_1epilogue_1_1threadblock_1_1PredicatedTileIterator.html">cutlass::epilogue::threadblock::PredicatedTileIterator</a></div><div class="ttdef"><b>Definition:</b> epilogue/threadblock/predicated_tile_iterator.h:65</div></div>
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+ <div class="ttc" id="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp_html_a43ad144aa28bab769fa744744eb0321a"><div class="ttname"><a href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a43ad144aa28bab769fa744744eb0321a">cutlass::epilogue::threadblock::DefaultEpilogueComplexTensorOp::ElementAccumulator</a></div><div class="ttdeci">typename WarpMmaTensorOp::ElementC ElementAccumulator</div><div class="ttdef"><b>Definition:</b> default_epilogue_complex_tensor_op.h:81</div></div>
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+ <div class="ttc" id="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp_html_a517049715fcabdb536f278604477829e"><div class="ttname"><a href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a517049715fcabdb536f278604477829e">cutlass::epilogue::threadblock::DefaultEpilogueComplexTensorOp::OutputOp</a></div><div class="ttdeci">OutputOp_ OutputOp</div><div class="ttdef"><b>Definition:</b> default_epilogue_complex_tensor_op.h:76</div></div>
134
+ <div class="ttc" id="classcutlass_1_1epilogue_1_1threadblock_1_1SharedLoadIterator_html"><div class="ttname"><a href="classcutlass_1_1epilogue_1_1threadblock_1_1SharedLoadIterator.html">cutlass::epilogue::threadblock::SharedLoadIterator</a></div><div class="ttdef"><b>Definition:</b> shared_load_iterator.h:61</div></div>
135
+ <div class="ttc" id="reduction__op_8h_html"><div class="ttname"><a href="reduction__op_8h.html">reduction_op.h</a></div><div class="ttdoc">Functor performing reduction operations used by epilogues. </div></div>
136
+ <div class="ttc" id="cutlass_8h_html"><div class="ttname"><a href="cutlass_8h.html">cutlass.h</a></div><div class="ttdoc">Basic include for CUTLASS. </div></div>
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+ </div><!-- fragment --></div><!-- contents -->
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+ <!-- start footer part -->
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+ </a> 1.8.11
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+ <a href="device_2tensor__compare_8h.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span>&#160;<span class="comment">/***************************************************************************************************</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span>&#160;<span class="comment"> * Copyright (c) 2017-2019, NVIDIA CORPORATION. All rights reserved.</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span>&#160;<span class="comment"> * Redistribution and use in source and binary forms, with or without modification, are permitted</span></div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span>&#160;<span class="comment"> * provided that the following conditions are met:</span></div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span>&#160;<span class="comment"> * * Redistributions of source code must retain the above copyright notice, this list of</span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span>&#160;<span class="comment"> * conditions and the following disclaimer.</span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span>&#160;<span class="comment"> * * Redistributions in binary form must reproduce the above copyright notice, this list of</span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span>&#160;<span class="comment"> * conditions and the following disclaimer in the documentation and/or other materials</span></div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span>&#160;<span class="comment"> * provided with the distribution.</span></div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span>&#160;<span class="comment"> * * Neither the name of the NVIDIA CORPORATION nor the names of its contributors may be used</span></div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span>&#160;<span class="comment"> * to endorse or promote products derived from this software without specific prior written</span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span>&#160;<span class="comment"> * permission.</span></div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span>&#160;<span class="comment"> * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS &quot;AS IS&quot; AND ANY EXPRESS OR</span></div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span>&#160;<span class="comment"> * IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND</span></div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span>&#160;<span class="comment"> * FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL NVIDIA CORPORATION BE LIABLE</span></div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span>&#160;<span class="comment"> * FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,</span></div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span>&#160;<span class="comment"> * BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;</span></div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span>&#160;<span class="comment"> * OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT,</span></div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span>&#160;<span class="comment"> * STRICT LIABILITY, OR TOR (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE</span></div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span>&#160;<span class="comment"> * OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.</span></div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span>&#160;<span class="comment"> **************************************************************************************************/</span></div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span>&#160;<span class="comment">/* \file</span></div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span>&#160;<span class="comment"> \brief Defines host-side elementwise operations on TensorView.</span></div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span>&#160;<span class="comment">*/</span></div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span>&#160;</div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span>&#160;<span class="preprocessor">#pragma once</span></div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span>&#160;<span class="comment">// Standard Library includes</span></div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span>&#160;<span class="preprocessor">#include &lt;utility&gt;</span></div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span>&#160;</div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span>&#160;<span class="comment">// Cutlass includes</span></div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="cutlass_8h.html">cutlass/cutlass.h</a>&quot;</span></div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="relatively__equal_8h.html">cutlass/relatively_equal.h</a>&quot;</span></div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span>&#160;</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="distribution_8h.html">cutlass/util/distribution.h</a>&quot;</span></div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>&#160;</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="device_2tensor__foreach_8h.html">tensor_foreach.h</a>&quot;</span></div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>&#160;</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>&#160;<span class="keyword">namespace </span><a class="code" href="namespacecutlass.html">cutlass</a> {</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>&#160;<span class="keyword">namespace </span>reference {</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>&#160;<span class="keyword">namespace </span>device {</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>&#160;</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>&#160;</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>&#160;<span class="keyword">namespace </span>kernel {</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>&#160;</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Element&gt;</div><div class="line"><a name="l00050"></a><span class="lineno"><a class="line" href="namespacecutlass_1_1reference_1_1device_1_1kernel.html#a4595ede72eddace3c973c7f0f74b001d"> 50</a></span>&#160;__global__ <span class="keywordtype">void</span> <a class="code" href="namespacecutlass_1_1reference_1_1device_1_1kernel.html#a4595ede72eddace3c973c7f0f74b001d">BlockCompareEqual</a>(</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>&#160; <span class="keywordtype">int</span> *equal, </div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>&#160; Element <span class="keyword">const</span> *ptr_A,</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>&#160; Element <span class="keyword">const</span> *ptr_B,</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>&#160; <span class="keywordtype">size_t</span> capacity) {</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>&#160;</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>&#160; <span class="keywordtype">size_t</span> idx = threadIdx.x + blockDim.x * blockIdx.x;</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>&#160;</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>&#160; <span class="keywordflow">for</span> (; idx &lt; capacity; idx += gridDim.x * blockDim.x) {</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>&#160; <span class="keywordflow">if</span> (ptr_A[idx] != ptr_B[idx]) {</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>&#160; *equal = 0;</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>&#160; <span class="keywordflow">return</span>;</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>&#160; }</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>&#160; }</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>&#160;}</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>&#160;</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Element&gt;</div><div class="line"><a name="l00067"></a><span class="lineno"><a class="line" href="namespacecutlass_1_1reference_1_1device_1_1kernel.html#a6da13fb683d56d6973af0a97a4023677"> 67</a></span>&#160;__global__ <span class="keywordtype">void</span> <a class="code" href="namespacecutlass_1_1reference_1_1device_1_1kernel.html#a6da13fb683d56d6973af0a97a4023677">BlockCompareRelativelyEqual</a>(</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>&#160; <span class="keywordtype">int</span> *equal, </div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>&#160; Element <span class="keyword">const</span> *ptr_A,</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>&#160; Element <span class="keyword">const</span> *ptr_B,</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>&#160; <span class="keywordtype">size_t</span> capacity,</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>&#160; Element epsilon,</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>&#160; Element nonzero_floor) {</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>&#160;</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>&#160; <span class="keywordtype">size_t</span> idx = threadIdx.x + blockDim.x * blockIdx.x;</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>&#160;</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>&#160; <span class="keywordflow">for</span> (; idx &lt; capacity; idx += gridDim.x * blockDim.x) {</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>&#160;</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>&#160; Element a = ptr_A[idx];</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>&#160; Element b = ptr_B[idx];</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>&#160;</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>&#160; <span class="keywordflow">if</span> (!<a class="code" href="namespacecutlass.html#aebc97e25721b38692159a6d50d545fe0">relatively_equal</a>(a, b, epsilon, nonzero_floor)) {</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>&#160; *equal = 0;</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>&#160; <span class="keywordflow">return</span>;</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>&#160; }</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>&#160; }</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>&#160;}</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>&#160;</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>&#160;} <span class="comment">// namespace kernel</span></div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>&#160;</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>&#160;</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>&#160;</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Element&gt;</div><div class="line"><a name="l00096"></a><span class="lineno"><a class="line" href="namespacecutlass_1_1reference_1_1device.html#aad19927d67f15b89e66560cb77f2a813"> 96</a></span>&#160;<span class="keywordtype">bool</span> <a class="code" href="namespacecutlass_1_1reference_1_1device_1_1kernel.html#a4595ede72eddace3c973c7f0f74b001d">BlockCompareEqual</a>(</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>&#160; Element <span class="keyword">const</span> *ptr_A,</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>&#160; Element <span class="keyword">const</span> *ptr_B,</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>&#160; <span class="keywordtype">size_t</span> capacity,</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>&#160; <span class="keywordtype">int</span> grid_size = 0, </div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>&#160; <span class="keywordtype">int</span> block_size = 0) {</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>&#160;</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>&#160; <span class="keywordtype">int</span> equal_flag = 1;</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>&#160; <span class="keywordtype">int</span> *device_equal_flag = <span class="keyword">nullptr</span>;</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>&#160;</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>&#160; <span class="keywordflow">if</span> (cudaMalloc((<span class="keywordtype">void</span> **)&amp;device_equal_flag, <span class="keyword">sizeof</span>(<span class="keywordtype">int</span>)) != cudaSuccess) {</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>&#160; <span class="keywordflow">throw</span> std::runtime_error(<span class="stringliteral">&quot;Failed to allocate device flag.&quot;</span>);</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>&#160; }</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>&#160;</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>&#160; <span class="keywordflow">if</span> (cudaMemcpy(</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>&#160; device_equal_flag, </div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>&#160; &amp;equal_flag, </div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>&#160; <span class="keyword">sizeof</span>(<span class="keywordtype">int</span>), </div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>&#160; cudaMemcpyHostToDevice) != cudaSuccess) {</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>&#160;</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>&#160; <span class="keywordflow">throw</span> std::runtime_error(<span class="stringliteral">&quot;Failed to copy equality flag to device.&quot;</span>);</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>&#160; }</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>&#160;</div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>&#160; <span class="keywordflow">if</span> (!grid_size || !block_size) {</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>&#160;</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>&#160; <span class="comment">// if grid_size or block_size are zero, query occupancy using the CUDA Occupancy API</span></div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>&#160; cudaError_t result = cudaOccupancyMaxPotentialBlockSize(</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>&#160; &amp;grid_size,</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>&#160; &amp;block_size,</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>&#160; reinterpret_cast&lt;void const *&gt;(kernel::BlockCompareEqual&lt;Element&gt;));</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>&#160;</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>&#160; <span class="keywordflow">if</span> (result != cudaSuccess) {</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>&#160; <span class="keywordflow">throw</span> std::runtime_error(<span class="stringliteral">&quot;Failed to query occupancy.&quot;</span>);</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>&#160; }</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>&#160;</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span>&#160; <span class="comment">// Limit block size. This has the effect of increasing the number of items processed by a</span></div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>&#160; <span class="comment">// single thread and reduces the impact of initialization overhead.</span></div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>&#160; block_size = (block_size &lt; 128 ? block_size : 128);</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>&#160; }</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>&#160;</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>&#160; dim3 grid(grid_size, 1, 1);</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>&#160; dim3 block(block_size, 1, 1);</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span>&#160;</div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>&#160; kernel::BlockCompareEqual&lt;Element&gt;&lt;&lt;&lt; grid, block &gt;&gt;&gt;(device_equal_flag, ptr_A, ptr_B, capacity);</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>&#160;</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>&#160; <span class="keywordflow">if</span> (cudaMemcpy(</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>&#160; &amp;equal_flag, </div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>&#160; device_equal_flag,</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>&#160; <span class="keyword">sizeof</span>(<span class="keywordtype">int</span>), </div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>&#160; cudaMemcpyDeviceToHost) != cudaSuccess) {</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>&#160; </div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>&#160; cudaFree(device_equal_flag);</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span>&#160;</div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>&#160; <span class="keywordflow">throw</span> std::runtime_error(<span class="stringliteral">&quot;Failed to copy equality flag from device.&quot;</span>);</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>&#160; }</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>&#160;</div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span>&#160; cudaFree(device_equal_flag);</div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span>&#160;</div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span>&#160; <span class="keywordflow">return</span> equal_flag;</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>&#160;}</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>&#160;</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>&#160;</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Element&gt;</div><div class="line"><a name="l00161"></a><span class="lineno"><a class="line" href="namespacecutlass_1_1reference_1_1device.html#a286d24a9faabc0be18f96e1069dca23e"> 161</a></span>&#160;<span class="keywordtype">bool</span> <a class="code" href="namespacecutlass_1_1reference_1_1device_1_1kernel.html#a6da13fb683d56d6973af0a97a4023677">BlockCompareRelativelyEqual</a>(</div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span>&#160; Element <span class="keyword">const</span> *ptr_A,</div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span>&#160; Element <span class="keyword">const</span> *ptr_B,</div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span>&#160; <span class="keywordtype">size_t</span> capacity,</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>&#160; Element epsilon,</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span>&#160; Element nonzero_floor,</div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>&#160; <span class="keywordtype">int</span> grid_size = 0, </div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span>&#160; <span class="keywordtype">int</span> block_size = 0) {</div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>&#160;</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span>&#160; <span class="keywordtype">int</span> equal_flag = 1;</div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span>&#160; <span class="keywordtype">int</span> *device_equal_flag = <span class="keyword">nullptr</span>;</div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span>&#160;</div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span>&#160; <span class="keywordflow">if</span> (cudaMalloc((<span class="keywordtype">void</span> **)&amp;device_equal_flag, <span class="keyword">sizeof</span>(<span class="keywordtype">int</span>)) != cudaSuccess) {</div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span>&#160; <span class="keywordflow">throw</span> std::runtime_error(<span class="stringliteral">&quot;Failed to allocate device flag.&quot;</span>);</div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span>&#160; }</div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span>&#160;</div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span>&#160; <span class="keywordflow">if</span> (cudaMemcpy(</div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span>&#160; device_equal_flag, </div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span>&#160; &amp;equal_flag, </div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span>&#160; <span class="keyword">sizeof</span>(<span class="keywordtype">int</span>), </div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span>&#160; cudaMemcpyHostToDevice) != cudaSuccess) {</div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span>&#160;</div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span>&#160; <span class="keywordflow">throw</span> std::runtime_error(<span class="stringliteral">&quot;Failed to copy equality flag to device.&quot;</span>);</div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span>&#160; }</div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span>&#160;</div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span>&#160; <span class="keywordflow">if</span> (!grid_size || !block_size) {</div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span>&#160;</div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span>&#160; <span class="comment">// if grid_size or block_size are zero, query occupancy using the CUDA Occupancy API</span></div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span>&#160; cudaError_t result = cudaOccupancyMaxPotentialBlockSize(</div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span>&#160; &amp;grid_size,</div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span>&#160; &amp;block_size,</div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span>&#160; reinterpret_cast&lt;void const *&gt;(kernel::BlockCompareRelativelyEqual&lt;Element&gt;));</div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span>&#160;</div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span>&#160; <span class="keywordflow">if</span> (result != cudaSuccess) {</div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span>&#160; <span class="keywordflow">throw</span> std::runtime_error(<span class="stringliteral">&quot;Failed to query occupancy.&quot;</span>);</div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span>&#160; }</div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span>&#160;</div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span>&#160; <span class="comment">// Limit block size. This has the effect of increasing the number of items processed by a</span></div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span>&#160; <span class="comment">// single thread and reduces the impact of initialization overhead.</span></div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span>&#160; block_size = (block_size &lt; 128 ? block_size : 128);</div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span>&#160; }</div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span>&#160;</div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span>&#160; dim3 grid(grid_size, 1, 1);</div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span>&#160; dim3 block(block_size, 1, 1);</div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span>&#160;</div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span>&#160; kernel::BlockCompareRelativelyEqual&lt;Element&gt;&lt;&lt;&lt; grid, block &gt;&gt;&gt;(</div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span>&#160; device_equal_flag, </div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span>&#160; ptr_A, </div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span>&#160; ptr_B, </div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span>&#160; capacity, </div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span>&#160; epsilon, </div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span>&#160; nonzero_floor</div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span>&#160; );</div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span>&#160;</div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span>&#160; <span class="keywordflow">if</span> (cudaMemcpy(</div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span>&#160; &amp;equal_flag, </div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span>&#160; device_equal_flag,</div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span>&#160; <span class="keyword">sizeof</span>(<span class="keywordtype">int</span>), </div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span>&#160; cudaMemcpyDeviceToHost) != cudaSuccess) {</div><div class="line"><a name="l00220"></a><span class="lineno"> 220</span>&#160; </div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span>&#160; cudaFree(device_equal_flag);</div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span>&#160;</div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span>&#160; <span class="keywordflow">throw</span> std::runtime_error(<span class="stringliteral">&quot;Failed to copy equality flag from device.&quot;</span>);</div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span>&#160; }</div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span>&#160;</div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span>&#160; cudaFree(device_equal_flag);</div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span>&#160;</div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span>&#160; <span class="keywordflow">return</span> equal_flag;</div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span>&#160;}</div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span>&#160;</div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span>&#160;</div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span>&#160;} <span class="comment">// device</span></div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span>&#160;} <span class="comment">// reference</span></div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span>&#160;} <span class="comment">// cutlass</span></div><div class="ttc" id="namespacecutlass_html"><div class="ttname"><a href="namespacecutlass.html">cutlass</a></div><div class="ttdef"><b>Definition:</b> aligned_buffer.h:35</div></div>
102
+ <div class="ttc" id="namespacecutlass_1_1reference_1_1device_1_1kernel_html_a6da13fb683d56d6973af0a97a4023677"><div class="ttname"><a href="namespacecutlass_1_1reference_1_1device_1_1kernel.html#a6da13fb683d56d6973af0a97a4023677">cutlass::reference::device::kernel::BlockCompareRelativelyEqual</a></div><div class="ttdeci">__global__ void BlockCompareRelativelyEqual(int *equal, Element const *ptr_A, Element const *ptr_B, size_t capacity, Element epsilon, Element nonzero_floor)</div><div class="ttdef"><b>Definition:</b> device/tensor_compare.h:67</div></div>
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+ <div class="ttc" id="device_2tensor__foreach_8h_html"><div class="ttname"><a href="device_2tensor__foreach_8h.html">tensor_foreach.h</a></div></div>
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+ <div class="ttc" id="relatively__equal_8h_html"><div class="ttname"><a href="relatively__equal_8h.html">relatively_equal.h</a></div></div>
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+ <div class="ttc" id="namespacecutlass_1_1reference_1_1device_1_1kernel_html_a4595ede72eddace3c973c7f0f74b001d"><div class="ttname"><a href="namespacecutlass_1_1reference_1_1device_1_1kernel.html#a4595ede72eddace3c973c7f0f74b001d">cutlass::reference::device::kernel::BlockCompareEqual</a></div><div class="ttdeci">__global__ void BlockCompareEqual(int *equal, Element const *ptr_A, Element const *ptr_B, size_t capacity)</div><div class="ttdef"><b>Definition:</b> device/tensor_compare.h:50</div></div>
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+ <div class="ttc" id="distribution_8h_html"><div class="ttname"><a href="distribution_8h.html">distribution.h</a></div><div class="ttdoc">This header contains a class to parametrize a statistical distribution function. </div></div>
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+ <h3>cutlass &rarr; platform Relation</h3><table class="dirtab"><tr class="dirtab"><th class="dirtab">File in include/cutlass</th><th class="dirtab">Includes file in include/cutlass/platform</th></tr><tr class="dirtab"><td class="dirtab"><a class="el" href="array__subbyte_8h.html">array_subbyte.h</a></td><td class="dirtab"><a class="el" href="platform_8h.html">platform.h</a></td></tr><tr class="dirtab"><td class="dirtab"><a class="el" href="dir_9aa36bd9cfad59a1f88859a38871c977.html">gemm</a>&#160;/&#160;<a class="el" href="dir_ffb18c781d484e5d1c680f712f01a439.html">threadblock</a>&#160;/&#160;<a class="el" href="default__gemv__core_8h.html">default_gemv_core.h</a></td><td class="dirtab"><a class="el" href="platform_8h.html">platform.h</a></td></tr><tr class="dirtab"><td class="dirtab"><a class="el" href="dir_9aa36bd9cfad59a1f88859a38871c977.html">gemm</a>&#160;/&#160;<a class="el" href="dir_ffb18c781d484e5d1c680f712f01a439.html">threadblock</a>&#160;/&#160;<a class="el" href="default__mma__core__sm75_8h.html">default_mma_core_sm75.h</a></td><td class="dirtab"><a class="el" href="platform_8h.html">platform.h</a></td></tr><tr class="dirtab"><td class="dirtab"><a class="el" href="integer__subbyte_8h.html">integer_subbyte.h</a></td><td class="dirtab"><a class="el" href="platform_8h.html">platform.h</a></td></tr><tr class="dirtab"><td class="dirtab"><a class="el" href="dir_9aa36bd9cfad59a1f88859a38871c977.html">gemm</a>&#160;/&#160;<a class="el" href="dir_5182a53bfc5d70ef5651acc985c58dc3.html">warp</a>&#160;/&#160;<a class="el" href="mma__tensor__op__tile__iterator_8h.html">mma_tensor_op_tile_iterator.h</a></td><td class="dirtab"><a class="el" href="platform_8h.html">platform.h</a></td></tr><tr class="dirtab"><td class="dirtab"><a class="el" href="dir_9aa36bd9cfad59a1f88859a38871c977.html">gemm</a>&#160;/&#160;<a class="el" href="dir_5182a53bfc5d70ef5651acc985c58dc3.html">warp</a>&#160;/&#160;<a class="el" href="mma__tensor__op__tile__iterator__sm70_8h.html">mma_tensor_op_tile_iterator_sm70.h</a></td><td class="dirtab"><a class="el" href="platform_8h.html">platform.h</a></td></tr><tr class="dirtab"><td class="dirtab"><a class="el" href="predicate__vector_8h.html">predicate_vector.h</a></td><td class="dirtab"><a class="el" href="platform_8h.html">platform.h</a></td></tr><tr class="dirtab"><td class="dirtab"><a class="el" href="tensor__ref_8h.html">tensor_ref.h</a></td><td class="dirtab"><a class="el" href="platform_8h.html">platform.h</a></td></tr></table></div><!-- contents -->
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+ <table cellspacing="0" cellpadding="0">
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+ <tbody>
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+ <td id="projectlogo"><img alt="Logo" src="cutlass-logo-small.png"/></td>
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+ <td id="projectalign" style="padding-left: 0.5em;">
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+ <div id="projectname">CUTLASS
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+ </div>
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+ <div id="projectbrief">CUDA Templates for Linear Algebra Subroutines and Solvers</div>
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+ </td>
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+ </tr>
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+ </tbody>
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+ </table>
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+ </div>
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+ <!-- end header part -->
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+ <!-- Generated by Doxygen 1.8.11 -->
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+ <ul class="tablist">
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+ <li><a href="index.html"><span>Main&#160;Page</span></a></li>
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+ <li><a href="modules.html"><span>Modules</span></a></li>
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+ <li><a href="namespaces.html"><span>Namespaces</span></a></li>
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+ <li class="current"><a href="annotated.html"><span>Classes</span></a></li>
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+ <li><a href="files.html"><span>Files</span></a></li>
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+ <div id="navrow2" class="tabs2">
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+ <ul class="tablist">
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+ <li><a href="annotated.html"><span>Class&#160;List</span></a></li>
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+ <li><a href="classes.html"><span>Class&#160;Index</span></a></li>
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+ <li><a href="inherits.html"><span>Class&#160;Hierarchy</span></a></li>
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+ <li class="current"><a href="functions.html"><span>Class&#160;Members</span></a></li>
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+ </ul>
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+ <div id="navrow3" class="tabs2">
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+ <ul class="tablist">
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+ <li><a href="functions.html"><span>All</span></a></li>
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+ <li class="current"><a href="functions_func.html"><span>Functions</span></a></li>
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+ <li><a href="functions_vars.html"><span>Variables</span></a></li>
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+ <li><a href="functions_type.html"><span>Typedefs</span></a></li>
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+ <li><a href="functions_enum.html"><span>Enumerations</span></a></li>
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+ <li><a href="functions_eval.html"><span>Enumerator</span></a></li>
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+ </ul>
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+ </div>
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+ <div id="navrow4" class="tabs3">
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+ <ul class="tablist">
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+ <li><a href="functions_func.html#index_a"><span>a</span></a></li>
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+ <li><a href="functions_func_b.html#index_b"><span>b</span></a></li>
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+ <li><a href="functions_func_c.html#index_c"><span>c</span></a></li>
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+ <li><a href="functions_func_d.html#index_d"><span>d</span></a></li>
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+ <li><a href="functions_func_e.html#index_e"><span>e</span></a></li>
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+ <li><a href="functions_func_f.html#index_f"><span>f</span></a></li>
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+ <li><a href="functions_func_g.html#index_g"><span>g</span></a></li>
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+ <li><a href="functions_func_h.html#index_h"><span>h</span></a></li>
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+ <li><a href="functions_func_i.html#index_i"><span>i</span></a></li>
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+ <li><a href="functions_func_k.html#index_k"><span>k</span></a></li>
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+ <li class="current"><a href="functions_func_l.html#index_l"><span>l</span></a></li>
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+ <li><a href="functions_func_m.html#index_m"><span>m</span></a></li>
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+ <li><a href="functions_func_n.html#index_n"><span>n</span></a></li>
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+ <li><a href="functions_func_o.html#index_o"><span>o</span></a></li>
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+ <li><a href="functions_func_p.html#index_p"><span>p</span></a></li>
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+ <li><a href="functions_func_q.html#index_q"><span>q</span></a></li>
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+ <li><a href="functions_func_r.html#index_r"><span>r</span></a></li>
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+ <li><a href="functions_func_s.html#index_s"><span>s</span></a></li>
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+ <li><a href="functions_func_t.html#index_t"><span>t</span></a></li>
110
+ <li><a href="functions_func_u.html#index_u"><span>u</span></a></li>
111
+ <li><a href="functions_func_v.html#index_v"><span>v</span></a></li>
112
+ <li><a href="functions_func_w.html#index_w"><span>w</span></a></li>
113
+ <li><a href="functions_func_0x7e.html#index_0x7e"><span>~</span></a></li>
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+ </ul>
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+ </div>
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+ </div><!-- top -->
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+ <!-- window showing the filter options -->
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+ <div id="MSearchSelectWindow"
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+ onmouseover="return searchBox.OnSearchSelectShow()"
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+
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+ <!-- iframe showing the search results (closed by default) -->
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+ <div id="MSearchResultsWindow">
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+ <iframe src="javascript:void(0)" frameborder="0"
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+ name="MSearchResults" id="MSearchResults">
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+ </iframe>
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+ </div>
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+
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+ <div class="contents">
132
+ &#160;
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+
134
+ <h3><a class="anchor" id="index_l"></a>- l -</h3><ul>
135
+ <li>launch()
136
+ : <a class="el" href="structcutlass_1_1reduction_1_1BatchedReduction.html#ab059393ac467ac365bd0b45c200befdf">cutlass::reduction::BatchedReduction&lt; BatchedReductionTraits_ &gt;</a>
137
+ </li>
138
+ <li>layout()
139
+ : <a class="el" href="classcutlass_1_1HostTensor.html#a9b78ff4fb7f317809b8cb8f70c557bea">cutlass::HostTensor&lt; Element_, Layout_ &gt;</a>
140
+ , <a class="el" href="classcutlass_1_1TensorRef.html#a7771fcd932e36c51c15572305f5b5520">cutlass::TensorRef&lt; Element_, Layout_ &gt;</a>
141
+ , <a class="el" href="classcutlass_1_1thread_1_1Matrix.html#a23134a82ceae2601f3d6694a02271877">cutlass::thread::Matrix&lt; Element, Rows, Columns, Layout &gt;</a>
142
+ </li>
143
+ <li>layout_id()
144
+ : <a class="el" href="structcutlass_1_1layout_1_1GeneralMatrix.html#ac49a8ab921f16e8b1411b67e33f0f8e9">cutlass::layout::GeneralMatrix</a>
145
+ </li>
146
+ <li>LayoutA()
147
+ : <a class="el" href="classcutlass_1_1gemm_1_1threadblock_1_1MmaBase_1_1SharedStorage.html#a3bc08d3813f427f3ae64b3b321651061">cutlass::gemm::threadblock::MmaBase&lt; Shape_, Policy_, Stages, Enable &gt;::SharedStorage</a>
148
+ </li>
149
+ <li>LayoutB()
150
+ : <a class="el" href="classcutlass_1_1gemm_1_1threadblock_1_1MmaBase_1_1SharedStorage.html#a8ecf7b0286e1a9f35debbe5a08b080f6">cutlass::gemm::threadblock::MmaBase&lt; Shape_, Policy_, Stages, Enable &gt;::SharedStorage</a>
151
+ </li>
152
+ <li>LinearCombination()
153
+ : <a class="el" href="classcutlass_1_1epilogue_1_1thread_1_1LinearCombination.html#aaeaf8ed9b2ea6256ea8d322985d9bb27">cutlass::epilogue::thread::LinearCombination&lt; ElementOutput_, Count, ElementAccumulator_, ElementCompute_, Round &gt;</a>
154
+ </li>
155
+ <li>LinearCombinationClamp()
156
+ : <a class="el" href="classcutlass_1_1epilogue_1_1thread_1_1LinearCombinationClamp.html#a19519a5bdbd6d3f3bc8efa9756ad55b7">cutlass::epilogue::thread::LinearCombinationClamp&lt; ElementOutput_, Count, ElementAccumulator_, ElementCompute_, Round &gt;</a>
157
+ </li>
158
+ <li>LinearCombinationRelu()
159
+ : <a class="el" href="classcutlass_1_1epilogue_1_1thread_1_1LinearCombinationRelu.html#ae060fd9c16f95f086ff7f784ce40a7e2">cutlass::epilogue::thread::LinearCombinationRelu&lt; ElementOutput_, Count, ElementAccumulator_, ElementCompute_, Round &gt;</a>
160
+ , <a class="el" href="classcutlass_1_1epilogue_1_1thread_1_1LinearCombinationRelu_3_01ElementOutput___00_01Count_00_01int_00_01float_00_01Round_01_4.html#acca75dd2a19169f68aaaa9b84ffbb8b1">cutlass::epilogue::thread::LinearCombinationRelu&lt; ElementOutput_, Count, int, float, Round &gt;</a>
161
+ </li>
162
+ <li>load()
163
+ : <a class="el" href="classcutlass_1_1epilogue_1_1threadblock_1_1InterleavedPredicatedTileIterator.html#adb3577ad7dba393626952f76c4aae465">cutlass::epilogue::threadblock::InterleavedPredicatedTileIterator&lt; ThreadMap_, Element_, InterleavedK &gt;</a>
164
+ , <a class="el" href="classcutlass_1_1epilogue_1_1threadblock_1_1PredicatedTileIterator.html#a6994f682b05a9eac3e1e83e9717136d0">cutlass::epilogue::threadblock::PredicatedTileIterator&lt; ThreadMap_, Element_ &gt;</a>
165
+ , <a class="el" href="classcutlass_1_1epilogue_1_1threadblock_1_1SharedLoadIterator.html#acc9440f6242ee064cb6e48f9387d73ad">cutlass::epilogue::threadblock::SharedLoadIterator&lt; ThreadMap_, Element_, MaxAlignment &gt;</a>
166
+ , <a class="el" href="classcutlass_1_1epilogue_1_1warp_1_1FragmentIteratorComplexTensorOp_3_01WarpShape___00_01Operato8cf03c624cf3210c71b7cbd580b080f8.html#ad97f38185da47d8af981397b23f07cd7">cutlass::epilogue::warp::FragmentIteratorComplexTensorOp&lt; WarpShape_, OperatorShape_, OperatorElementC_, OperatorFragmentC_, layout::RowMajor &gt;</a>
167
+ , <a class="el" href="classcutlass_1_1epilogue_1_1warp_1_1FragmentIteratorSimt_3_01WarpShape___00_01Operator___00_01la3f2abc523201c1b0228df99119ab88e1.html#a3bceefc9751d04598e063af41674549c">cutlass::epilogue::warp::FragmentIteratorSimt&lt; WarpShape_, Operator_, layout::RowMajor, MmaSimtPolicy_ &gt;</a>
168
+ , <a class="el" href="classcutlass_1_1epilogue_1_1warp_1_1FragmentIteratorTensorOp_3_01WarpShape___00_01OperatorShape_e459aab140a2ce78336e584f95886726.html#a24161390822e4b5880f73fccb50826c0">cutlass::epilogue::warp::FragmentIteratorTensorOp&lt; WarpShape_, OperatorShape_, OperatorElementC_, OperatorFragmentC_, layout::ColumnMajorInterleaved&lt; InterleavedK &gt; &gt;</a>
169
+ , <a class="el" href="classcutlass_1_1epilogue_1_1warp_1_1FragmentIteratorTensorOp_3_01WarpShape___00_01OperatorShape_5e78dabe303f20d76b00c600aab61eda.html#aeb486b8f0cfa33ae7b64cb88c199f312">cutlass::epilogue::warp::FragmentIteratorTensorOp&lt; WarpShape_, OperatorShape_, OperatorElementC_, OperatorFragmentC_, layout::RowMajor &gt;</a>
170
+ , <a class="el" href="classcutlass_1_1epilogue_1_1warp_1_1FragmentIteratorVoltaTensorOp_3_01WarpShape___00_01gemm_1_1Gdb805a2dc5571ac3b66e0fe6ffdcede2.html#a13b3d46be4c12bec05be608e2fae1dcd">cutlass::epilogue::warp::FragmentIteratorVoltaTensorOp&lt; WarpShape_, gemm::GemmShape&lt; 32, 32, 4 &gt;, float, layout::RowMajor &gt;</a>
171
+ , <a class="el" href="classcutlass_1_1epilogue_1_1warp_1_1FragmentIteratorVoltaTensorOp_3_01WarpShape___00_01gemm_1_1G16e08718cffa0989cce3fe8dbc4b075b.html#a5a5121d6ae4256b7928fde6e8be74e6a">cutlass::epilogue::warp::FragmentIteratorVoltaTensorOp&lt; WarpShape_, gemm::GemmShape&lt; 32, 32, 4 &gt;, half_t, layout::RowMajor &gt;</a>
172
+ , <a class="el" href="classcutlass_1_1epilogue_1_1warp_1_1FragmentIteratorWmmaTensorOp_3_01WarpShape___00_01OperatorShfdb1f120c6797383663f9fd11d0fc599.html#a0829df04fbd9717fe92e1ef85bc00080">cutlass::epilogue::warp::FragmentIteratorWmmaTensorOp&lt; WarpShape_, OperatorShape_, OperatorElementC_, OperatorFragmentC_, layout::RowMajor &gt;</a>
173
+ , <a class="el" href="classcutlass_1_1epilogue_1_1warp_1_1TileIteratorSimt_3_01WarpShape___00_01Operator___00_01Elemenf2bd262ed3e202b25d5802d83965bf3b.html#adc0257e19f8d1c6d3cfd8ef52d952f71">cutlass::epilogue::warp::TileIteratorSimt&lt; WarpShape_, Operator_, Element_, layout::RowMajor, MmaSimtPolicy_ &gt;</a>
174
+ , <a class="el" href="classcutlass_1_1epilogue_1_1warp_1_1TileIteratorTensorOp_3_01WarpShape___00_01OperatorShape___003cbb32beb84b4984cb7853662096d289.html#a4e473670fd9c4fc7004db274ba89c9c5">cutlass::epilogue::warp::TileIteratorTensorOp&lt; WarpShape_, OperatorShape_, Element_, layout::RowMajor &gt;</a>
175
+ , <a class="el" href="classcutlass_1_1epilogue_1_1warp_1_1TileIteratorVoltaTensorOp_3_01WarpShape___00_01gemm_1_1GemmS2fe0c60b727c738c622c18fc3dd76644.html#ad7e957c4c7d02063f8b4c5eaeac92995">cutlass::epilogue::warp::TileIteratorVoltaTensorOp&lt; WarpShape_, gemm::GemmShape&lt; 32, 32, 4 &gt;, float, layout::RowMajor &gt;</a>
176
+ , <a class="el" href="classcutlass_1_1epilogue_1_1warp_1_1TileIteratorVoltaTensorOp_3_01WarpShape___00_01gemm_1_1GemmSa0ceeeddc22575876eb977da7f5416a8.html#a7e2587da22e6d5273fcd33e43a76ff97">cutlass::epilogue::warp::TileIteratorVoltaTensorOp&lt; WarpShape_, gemm::GemmShape&lt; 32, 32, 4 &gt;, half_t, layout::RowMajor &gt;</a>
177
+ , <a class="el" href="classcutlass_1_1epilogue_1_1warp_1_1TileIteratorWmmaTensorOp_3_01WarpShape___00_01OperatorShape_fd6a91cd8bbd07ecd1344326b830e3a4.html#a71aad93445a7ff852d1b7cea2ec072a3">cutlass::epilogue::warp::TileIteratorWmmaTensorOp&lt; WarpShape_, OperatorShape_, OperatorFragment_, layout::RowMajor &gt;</a>
178
+ , <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaSimtTileIterator_3_01Shape___00_01Operand_1_1kA_00_01Element_67ca7e11a38e38f2c51b84767654a90f.html#a0111eeea429f29160247851e4ae652ac">cutlass::gemm::warp::MmaSimtTileIterator&lt; Shape_, Operand::kA, Element_, layout::ColumnMajor, Policy_, PartitionsK, PartitionGroupSize &gt;</a>
179
+ , <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaSimtTileIterator_3_01Shape___00_01Operand_1_1kA_00_01Element_f0ce904a9294556f15e1cc9cf7c99a93.html#adf3b2739ff83898c5517d4cc97b9be16">cutlass::gemm::warp::MmaSimtTileIterator&lt; Shape_, Operand::kA, Element_, layout::ColumnMajorInterleaved&lt; 4 &gt;, Policy_, PartitionsK, PartitionGroupSize &gt;</a>
180
+ , <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaSimtTileIterator_3_01Shape___00_01Operand_1_1kB_00_01Element_ea0a4e7ce3cd5d25cabf79383efdf4d9.html#ab62b7c647469f2ffa9a0c3233e2cd097">cutlass::gemm::warp::MmaSimtTileIterator&lt; Shape_, Operand::kB, Element_, layout::RowMajor, Policy_, PartitionsK, PartitionGroupSize &gt;</a>
181
+ , <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaSimtTileIterator_3_01Shape___00_01Operand_1_1kB_00_01Element_ada156b62fcbdce47009c5bf1321c92c.html#a2638399250c9a7378034d976b0d097e1">cutlass::gemm::warp::MmaSimtTileIterator&lt; Shape_, Operand::kB, Element_, layout::RowMajorInterleaved&lt; 4 &gt;, Policy_, PartitionsK, PartitionGroupSize &gt;</a>
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+ , <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaSimtTileIterator_3_01Shape___00_01Operand_1_1kC_00_01Element_4ccafbc821b3a55cd532602442a74031.html#a932ef3ae031def8ffce70ceef15a486e">cutlass::gemm::warp::MmaSimtTileIterator&lt; Shape_, Operand::kC, Element_, layout::ColumnMajor, Policy_ &gt;</a>
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+ , <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaSimtTileIterator_3_01Shape___00_01Operand_1_1kC_00_01Element_8f92ea79e85febb67169c4b2d94b1b20.html#a51328ce852255e58465a5f835e79363f">cutlass::gemm::warp::MmaSimtTileIterator&lt; Shape_, Operand::kC, Element_, layout::RowMajor, Policy_ &gt;</a>
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+ , <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#aaeee8d14c95678428d8d2ba36e76b9d0">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::ColumnMajor, InstructionShape_, OpDelta_ &gt;</a>
185
+ , <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a0e1da365b37245f7cddf42b140cfcfed">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::ColumnMajorInterleaved&lt; InterleavedN &gt;, InstructionShape_, OpDelta_ &gt;</a>
186
+ , <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a233b7f950eb27053b5c596dbd0ee7eb6">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::RowMajor, InstructionShape_, OpDelta_ &gt;</a>
187
+ , <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#a3d83eeb065bda5634f6d739c1584bee0">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::ColumnMajorTensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, int(128/sizeof(Element_))&gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;</a>
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+ , <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#a5bf6f7434406ae011baad51c8f6134d7">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::ColumnMajorTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;</a>
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+ , <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#ae6d98630ac77ae55f55281d7a9055b66">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::RowMajorTensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, int(128/sizeof(Element_))&gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;</a>
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+ , <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#a13030898f2eaab4b5d4136ff0932d649">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::RowMajorTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;</a>
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+ , <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a1be13f61b06e0f27e27b0b54349cac5c">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::TensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, 64 &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;</a>
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+ , <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#a33b7e2083273b6ecaacf7a98045e5ad7">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::TensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;</a>
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+ , <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaVoltaTensorOpAccumulatorTileIterator.html#a6d13731e2bfa90431aac91e05f66915c">cutlass::gemm::warp::MmaVoltaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, Layout_, InstructionShape_, OpDelta_ &gt;</a>
194
+ , <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaVoltaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operan0d3248553e52cd61ed8a2b3b12a20343.html#aa44f01f44b93015d1b5ff71490704978">cutlass::gemm::warp::MmaVoltaTensorOpMultiplicandTileIterator&lt; Shape_, Operand::kA, Element_, cutlass::layout::ColumnMajorVoltaTensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value &gt;, InstructionShape_, OpDelta_, 32 &gt;</a>
195
+ , <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaVoltaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operan34be8e21a40af3ebd2dc3dff460dca72.html#af63f1ab82c68bd2eeed4639e3e2b0290">cutlass::gemm::warp::MmaVoltaTensorOpMultiplicandTileIterator&lt; Shape_, Operand::kA, Element_, cutlass::layout::VoltaTensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value &gt;, InstructionShape_, OpDelta_, 32 &gt;</a>
196
+ , <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaVoltaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand734577b7e54a074d143aba59828c2f2.html#a6c04618a770059846c166c51f11800a4">cutlass::gemm::warp::MmaVoltaTensorOpMultiplicandTileIterator&lt; Shape_, Operand::kB, Element_, cutlass::layout::RowMajorVoltaTensorOpMultiplicandBCongruous&lt; sizeof_bits&lt; Element_ &gt;::value &gt;, InstructionShape_, OpDelta_, 32 &gt;</a>
197
+ , <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaVoltaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operan16c56cdc2dda5eeb996af8ec0242d501.html#a256ae965418e83d9274896065c8e9694">cutlass::gemm::warp::MmaVoltaTensorOpMultiplicandTileIterator&lt; Shape_, Operand::kB, Element_, cutlass::layout::VoltaTensorOpMultiplicandBCongruous&lt; sizeof_bits&lt; Element_ &gt;::value &gt;, InstructionShape_, OpDelta_, 32 &gt;</a>
198
+ , <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaVoltaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operan5a221944f4a0e16ccab77ba684856942.html#a483350b04218a200d8323f87fb0a8ad4">cutlass::gemm::warp::MmaVoltaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::ColumnMajorVoltaTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, KBlock &gt;, InstructionShape_, OpDelta_, 32 &gt;</a>
199
+ , <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaVoltaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operandcc9821c435540895138bc9af495f321.html#abd0486af7ec0d3c8e50418fe614b0d4f">cutlass::gemm::warp::MmaVoltaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::RowMajorVoltaTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, KBlock &gt;, InstructionShape_, OpDelta_, 32 &gt;</a>
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+ , <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaVoltaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operana2f40b28f0d2286b84d86f7238d67b52.html#a6f70a3f52ce4e700ddec23b4d0279e28">cutlass::gemm::warp::MmaVoltaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::VoltaTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, KBlock &gt;, InstructionShape_, OpDelta_, 32 &gt;</a>
201
+ , <a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileIterator2dThreadTile_3_01Shape___00_0165b39a630d10785a3558406f9adb99b9.html#aaa2ee3db6431b7340e3bb2c347344a9c">cutlass::transform::threadblock::PredicatedTileIterator2dThreadTile&lt; Shape_, Element_, layout::ColumnMajor, AdvanceRank, ThreadMap_, Transpose_ &gt;</a>
202
+ , <a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileIterator2dThreadTile_3_01Shape___00_017a517f3c73efd795ab05059cc9b111e1.html#a858a49a0b14d760b3d8d1edf74426183">cutlass::transform::threadblock::PredicatedTileIterator2dThreadTile&lt; Shape_, Element_, layout::PitchLinear, AdvanceRank, ThreadMap_, Transpose_ &gt;</a>
203
+ , <a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileIterator2dThreadTile_3_01Shape___00_013671177d6219bfeb0e1b4dc4c1b5bf11.html#ae399724b445824fda856949817f712c7">cutlass::transform::threadblock::PredicatedTileIterator2dThreadTile&lt; Shape_, Element_, layout::RowMajor, AdvanceRank, ThreadMap_, Transpose_ &gt;</a>
204
+ , <a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileIterator_3_01Shape___00_01Element___0068b3e874b5d93d11f0fa902c7f1d11d9.html#aa313dc3b60cef1df563ba4d78649f936">cutlass::transform::threadblock::PredicatedTileIterator&lt; Shape_, Element_, layout::ColumnMajor, AdvanceRank, ThreadMap_, AccessSize &gt;</a>
205
+ , <a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileIterator_3_01Shape___00_01Element___00f6b3a9dfab5e7c72d5233f7e5e6e3b9b.html#a09f33899cad1084651ac9a558a701a4e">cutlass::transform::threadblock::PredicatedTileIterator&lt; Shape_, Element_, layout::ColumnMajorInterleaved&lt; InterleavedK &gt;, AdvanceRank, ThreadMap_, AccessSize &gt;</a>
206
+ , <a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileIterator_3_01Shape___00_01Element___00e7c2c404e7aedfe60ad56bb5571306a1.html#abe79a4ca57e8ad8adbd88c703c75da80">cutlass::transform::threadblock::PredicatedTileIterator&lt; Shape_, Element_, layout::PitchLinear, AdvanceRank, ThreadMap_, AccessSize &gt;</a>
207
+ , <a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileIterator_3_01Shape___00_01Element___0041ea81994f8af0d4d071fdb9e66b5ff0.html#a608521f07cd7929c312891b6765d4a0e">cutlass::transform::threadblock::PredicatedTileIterator&lt; Shape_, Element_, layout::RowMajor, AdvanceRank, ThreadMap_, AccessSize &gt;</a>
208
+ , <a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileIterator_3_01Shape___00_01Element___00d670f969180a8d182dffb356ebcc957e.html#a9f98ff9fa96941ccd8ce149fbaa620f9">cutlass::transform::threadblock::PredicatedTileIterator&lt; Shape_, Element_, layout::RowMajorInterleaved&lt; InterleavedK &gt;, AdvanceRank, ThreadMap_, AccessSize &gt;</a>
209
+ , <a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1RegularTileIterator2dThreadTile_3_01Shape___00_01Eleb60d066756d1c18f05fceee6a27bdb8a.html#afd93ba5d114cd1c818d0f79597232e1d">cutlass::transform::threadblock::RegularTileIterator2dThreadTile&lt; Shape_, Element_, layout::ColumnMajorInterleaved&lt; 4 &gt;, AdvanceRank, ThreadMap_, Alignment &gt;</a>
210
+ , <a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1RegularTileIterator2dThreadTile_3_01Shape___00_01Ele76ed82829532ae1c17f4c78158f036c7.html#acc23e8bf2f97aa296343ad342998a4b6">cutlass::transform::threadblock::RegularTileIterator2dThreadTile&lt; Shape_, Element_, layout::PitchLinear, AdvanceRank, ThreadMap_, Alignment &gt;</a>
211
+ , <a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1RegularTileIterator2dThreadTile_3_01Shape___00_01Ele654c8f6161ae5340f040397a4e2e045c.html#afd716c418b782174c8a9889c18773d39">cutlass::transform::threadblock::RegularTileIterator2dThreadTile&lt; Shape_, Element_, layout::RowMajorInterleaved&lt; 4 &gt;, AdvanceRank, ThreadMap_, Alignment &gt;</a>
212
+ , <a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1RegularTileIterator_3_01Shape___00_01Element___00_011d3637dbd8bc58bcb020b51bf57fbfc0.html#a52146adf93a143916d527a153a3d9cb4">cutlass::transform::threadblock::RegularTileIterator&lt; Shape_, Element_, layout::ColumnMajor, AdvanceRank, ThreadMap_, Alignment &gt;</a>
213
+ , <a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1RegularTileIterator_3_01Shape___00_01Element___00_017982f81d4ef592e19c8427de2ea933a3.html#a94f074eab8510f8446a295698b734b01">cutlass::transform::threadblock::RegularTileIterator&lt; Shape_, Element_, layout::ColumnMajorTensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, int(128/sizeof(Element_))&gt;, AdvanceRank, ThreadMap_, Alignment &gt;</a>
214
+ , <a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1RegularTileIterator_3_01Shape___00_01Element___00_010889a732373c350de9b9a9f6c13cd761.html#a4ea359aced646d688f18c71aa4f39deb">cutlass::transform::threadblock::RegularTileIterator&lt; Shape_, Element_, layout::ColumnMajorTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, AdvanceRank, ThreadMap_, Alignment &gt;</a>
215
+ , <a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1RegularTileIterator_3_01Shape___00_01Element___00_01187f8574e1fe9d7d5e8fbf09bd834bf0.html#ade707a7b9bf2408919c6b00c1325e05c">cutlass::transform::threadblock::RegularTileIterator&lt; Shape_, Element_, layout::ColumnMajorVoltaTensorOpMultiplicandBCongruous&lt; sizeof_bits&lt; Element_ &gt;::value &gt;, AdvanceRank, ThreadMap_, Alignment &gt;</a>
216
+ , <a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1RegularTileIterator_3_01Shape___00_01Element___00_01793f74bfd8f116a827948ab01a37349a.html#aa1f14dc11456354f18d325d6002340c3">cutlass::transform::threadblock::RegularTileIterator&lt; Shape_, Element_, layout::ColumnMajorVoltaTensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value &gt;, AdvanceRank, ThreadMap_, Alignment &gt;</a>
217
+ , <a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1RegularTileIterator_3_01Shape___00_01Element___00_01bd31b3810c1fedf2e7e5959ff92b5d3d.html#ab436d46f4dc62169f7be2201ba62d3e1">cutlass::transform::threadblock::RegularTileIterator&lt; Shape_, Element_, layout::ColumnMajorVoltaTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Shape_::kRow &gt;, AdvanceRank, ThreadMap_, Alignment &gt;</a>
218
+ , <a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1RegularTileIterator_3_01Shape___00_01Element___00_0184a89653916f5d51ab59d1b386989a17.html#a66796895c463231ee0bd9fa34bc74aec">cutlass::transform::threadblock::RegularTileIterator&lt; Shape_, Element_, layout::PitchLinear, AdvanceRank, ThreadMap_, Alignment &gt;</a>
219
+ , <a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1RegularTileIterator_3_01Shape___00_01Element___00_0149454d361ea5885cf5166a920b5145df.html#ada36f68ddee26776788ff3b4a882364b">cutlass::transform::threadblock::RegularTileIterator&lt; Shape_, Element_, layout::RowMajor, AdvanceRank, ThreadMap_, Alignment &gt;</a>
220
+ , <a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1RegularTileIterator_3_01Shape___00_01Element___00_01c20d35180520077a5a09b1e33543c1a5.html#a8c35417d1631a9340bc6c94fd6a6b5d5">cutlass::transform::threadblock::RegularTileIterator&lt; Shape_, Element_, layout::RowMajorTensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, int(128/sizeof(Element_))&gt;, AdvanceRank, ThreadMap_, Alignment &gt;</a>
221
+ , <a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1RegularTileIterator_3_01Shape___00_01Element___00_01a31b454d9c930525c1e9ca406a514f40.html#aa3330bb8ca6828a81600649e7824e80a">cutlass::transform::threadblock::RegularTileIterator&lt; Shape_, Element_, layout::RowMajorTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, AdvanceRank, ThreadMap_, Alignment &gt;</a>
222
+ , <a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1RegularTileIterator_3_01Shape___00_01Element___00_0104ad31bd559a88cc418ae1cab7492ed5.html#a8c7eb83b3252ae487bf8e0fa623c40fa">cutlass::transform::threadblock::RegularTileIterator&lt; Shape_, Element_, layout::RowMajorVoltaTensorOpMultiplicandBCongruous&lt; sizeof_bits&lt; Element_ &gt;::value &gt;, AdvanceRank, ThreadMap_, Alignment &gt;</a>
223
+ , <a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1RegularTileIterator_3_01Shape___00_01Element___00_01f6f6511b5033cad31083644ac69c54d8.html#ac23159bd969188e7a0bf7be74c36b4a2">cutlass::transform::threadblock::RegularTileIterator&lt; Shape_, Element_, layout::RowMajorVoltaTensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value &gt;, AdvanceRank, ThreadMap_, Alignment &gt;</a>
224
+ , <a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1RegularTileIterator_3_01Shape___00_01Element___00_01b3fa5720e807697de61b9f937b269cd0.html#a203d5f66d31cf121a4f74ad2bed6d660">cutlass::transform::threadblock::RegularTileIterator&lt; Shape_, Element_, layout::RowMajorVoltaTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Shape_::kColumn &gt;, AdvanceRank, ThreadMap_, Alignment &gt;</a>
225
+ , <a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1RegularTileIterator_3_01Shape___00_01Element___00_01efd5013a2503d6567e2bf6b40c97360c.html#a136e0012cdb6111b47e49e2ba64ac737">cutlass::transform::threadblock::RegularTileIterator&lt; Shape_, Element_, layout::TensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, int(128/sizeof(Element_))&gt;, AdvanceRank, ThreadMap_, Alignment &gt;</a>
226
+ , <a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1RegularTileIterator_3_01Shape___00_01Element___00_0197fef2242a3454a7d1cebe61aee28b43.html#a11a408f8f9bc815fbe91cfff58badb3a">cutlass::transform::threadblock::RegularTileIterator&lt; Shape_, Element_, layout::TensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, AdvanceRank, ThreadMap_, Alignment &gt;</a>
227
+ , <a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1RegularTileIterator_3_01Shape___00_01Element___00_01a75d2cd74e722d6ad6a3b41aabfd432d.html#a7c7a6e45610678358635f91be8f81798">cutlass::transform::threadblock::RegularTileIterator&lt; Shape_, Element_, layout::VoltaTensorOpMultiplicandBCongruous&lt; sizeof_bits&lt; Element_ &gt;::value &gt;, AdvanceRank, ThreadMap_, Alignment &gt;</a>
228
+ , <a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1RegularTileIterator_3_01Shape___00_01Element___00_01f96bbeb63e6d4ce4a2551279de3a9f0e.html#adab44e485f531c6caa8c812d4b6a6946">cutlass::transform::threadblock::RegularTileIterator&lt; Shape_, Element_, layout::VoltaTensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value &gt;, AdvanceRank, ThreadMap_, Alignment &gt;</a>
229
+ , <a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1RegularTileIterator_3_01Shape___00_01Element___00_01dbd6b8468d5bd787308d2f615a24d123.html#a4980f583fe480dcec46ace1c91049c8a">cutlass::transform::threadblock::RegularTileIterator&lt; Shape_, Element_, layout::VoltaTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Shape_::kContiguous &gt;, AdvanceRank, ThreadMap_, Alignment &gt;</a>
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+ </li>
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+ <li>load_with_byte_offset()
232
+ : <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#a5a76314f07d7a5ddeed7a566228acc4d">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::ColumnMajor, InstructionShape_, OpDelta_ &gt;</a>
233
+ , <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#aae461549926e9f040e3376d709122682">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::ColumnMajorInterleaved&lt; InterleavedN &gt;, InstructionShape_, OpDelta_ &gt;</a>
234
+ , <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a7f9e9b46f9dc826b7f677bcd17bcfe66">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::RowMajor, InstructionShape_, OpDelta_ &gt;</a>
235
+ , <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#a6ebdb3095e18ac34da6e7947fc050d26">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::ColumnMajorTensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, int(128/sizeof(Element_))&gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;</a>
236
+ , <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#a0b3b6e84e68211479165f6bfce96421d">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::ColumnMajorTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;</a>
237
+ , <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#aaf694dd4b0520ff3430a012777f350bc">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::RowMajorTensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, int(128/sizeof(Element_))&gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;</a>
238
+ , <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#a58c1c86c36a821bdbba0e7bbe59e79ec">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::RowMajorTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;</a>
239
+ , <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#af8c5a6fe57db046155a8145fe386dbc1">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::TensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, 64 &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;</a>
240
+ , <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#aa851acf5c1e2a7ffa24526eebb347c1f">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::TensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;</a>
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+ , <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaVoltaTensorOpAccumulatorTileIterator.html#adefa4a6e04cd3e1ed22e514602d7269e">cutlass::gemm::warp::MmaVoltaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, Layout_, InstructionShape_, OpDelta_ &gt;</a>
242
+ , <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaVoltaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operan0d3248553e52cd61ed8a2b3b12a20343.html#af527f0fc64c4b200a82e8826db791423">cutlass::gemm::warp::MmaVoltaTensorOpMultiplicandTileIterator&lt; Shape_, Operand::kA, Element_, cutlass::layout::ColumnMajorVoltaTensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value &gt;, InstructionShape_, OpDelta_, 32 &gt;</a>
243
+ , <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaVoltaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operan34be8e21a40af3ebd2dc3dff460dca72.html#af86e30cc649534cdc5b754d6cb7177f2">cutlass::gemm::warp::MmaVoltaTensorOpMultiplicandTileIterator&lt; Shape_, Operand::kA, Element_, cutlass::layout::VoltaTensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value &gt;, InstructionShape_, OpDelta_, 32 &gt;</a>
244
+ , <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaVoltaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand734577b7e54a074d143aba59828c2f2.html#a246717a0cb4bbde1e32becac3835b89c">cutlass::gemm::warp::MmaVoltaTensorOpMultiplicandTileIterator&lt; Shape_, Operand::kB, Element_, cutlass::layout::RowMajorVoltaTensorOpMultiplicandBCongruous&lt; sizeof_bits&lt; Element_ &gt;::value &gt;, InstructionShape_, OpDelta_, 32 &gt;</a>
245
+ , <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaVoltaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operan16c56cdc2dda5eeb996af8ec0242d501.html#ac07ec8d44816b9482b29bee13a48c862">cutlass::gemm::warp::MmaVoltaTensorOpMultiplicandTileIterator&lt; Shape_, Operand::kB, Element_, cutlass::layout::VoltaTensorOpMultiplicandBCongruous&lt; sizeof_bits&lt; Element_ &gt;::value &gt;, InstructionShape_, OpDelta_, 32 &gt;</a>
246
+ , <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaVoltaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operan5a221944f4a0e16ccab77ba684856942.html#ab665c36434c159d203fc7585252fa90c">cutlass::gemm::warp::MmaVoltaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::ColumnMajorVoltaTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, KBlock &gt;, InstructionShape_, OpDelta_, 32 &gt;</a>
247
+ , <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaVoltaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operandcc9821c435540895138bc9af495f321.html#a47cd238e52ec513ba4483b49acada849">cutlass::gemm::warp::MmaVoltaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::RowMajorVoltaTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, KBlock &gt;, InstructionShape_, OpDelta_, 32 &gt;</a>
248
+ , <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaVoltaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operana2f40b28f0d2286b84d86f7238d67b52.html#a83f492a80d5df1170a5d3f3cb3bf9783">cutlass::gemm::warp::MmaVoltaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::VoltaTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, KBlock &gt;, InstructionShape_, OpDelta_, 32 &gt;</a>
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+ </li>
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+ <li>load_with_pointer_offset()
251
+ : <a class="el" href="classcutlass_1_1epilogue_1_1threadblock_1_1SharedLoadIterator.html#a54ab974e2fbeb22d335d55618b3c7b3f">cutlass::epilogue::threadblock::SharedLoadIterator&lt; ThreadMap_, Element_, MaxAlignment &gt;</a>
252
+ , <a class="el" href="classcutlass_1_1epilogue_1_1warp_1_1TileIteratorSimt_3_01WarpShape___00_01Operator___00_01Elemenf2bd262ed3e202b25d5802d83965bf3b.html#a91fa2b56deb9d9e4a5d58c0103198559">cutlass::epilogue::warp::TileIteratorSimt&lt; WarpShape_, Operator_, Element_, layout::RowMajor, MmaSimtPolicy_ &gt;</a>
253
+ , <a class="el" href="classcutlass_1_1epilogue_1_1warp_1_1TileIteratorTensorOp_3_01WarpShape___00_01OperatorShape___003cbb32beb84b4984cb7853662096d289.html#a3b35869528032ca52eb9e37d61265209">cutlass::epilogue::warp::TileIteratorTensorOp&lt; WarpShape_, OperatorShape_, Element_, layout::RowMajor &gt;</a>
254
+ , <a class="el" href="classcutlass_1_1epilogue_1_1warp_1_1TileIteratorVoltaTensorOp_3_01WarpShape___00_01gemm_1_1GemmS2fe0c60b727c738c622c18fc3dd76644.html#a069840dd91f3a78de3ae9b10d5d8a9e5">cutlass::epilogue::warp::TileIteratorVoltaTensorOp&lt; WarpShape_, gemm::GemmShape&lt; 32, 32, 4 &gt;, float, layout::RowMajor &gt;</a>
255
+ , <a class="el" href="classcutlass_1_1epilogue_1_1warp_1_1TileIteratorVoltaTensorOp_3_01WarpShape___00_01gemm_1_1GemmSa0ceeeddc22575876eb977da7f5416a8.html#ac192d6b2cd73d09ef1bd275fb58666e0">cutlass::epilogue::warp::TileIteratorVoltaTensorOp&lt; WarpShape_, gemm::GemmShape&lt; 32, 32, 4 &gt;, half_t, layout::RowMajor &gt;</a>
256
+ , <a class="el" href="classcutlass_1_1epilogue_1_1warp_1_1TileIteratorWmmaTensorOp_3_01WarpShape___00_01OperatorShape_fd6a91cd8bbd07ecd1344326b830e3a4.html#a462bcb6dc93d488ea524812ce154a506">cutlass::epilogue::warp::TileIteratorWmmaTensorOp&lt; WarpShape_, OperatorShape_, OperatorFragment_, layout::RowMajor &gt;</a>
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+ , <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaSimtTileIterator_3_01Shape___00_01Operand_1_1kA_00_01Element_67ca7e11a38e38f2c51b84767654a90f.html#a56c5dfa462db81b96a84752b3b1b2f14">cutlass::gemm::warp::MmaSimtTileIterator&lt; Shape_, Operand::kA, Element_, layout::ColumnMajor, Policy_, PartitionsK, PartitionGroupSize &gt;</a>
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+ , <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaSimtTileIterator_3_01Shape___00_01Operand_1_1kA_00_01Element_f0ce904a9294556f15e1cc9cf7c99a93.html#aab2bb83f041f2c533f399d0d39b709ea">cutlass::gemm::warp::MmaSimtTileIterator&lt; Shape_, Operand::kA, Element_, layout::ColumnMajorInterleaved&lt; 4 &gt;, Policy_, PartitionsK, PartitionGroupSize &gt;</a>
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+ , <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaSimtTileIterator_3_01Shape___00_01Operand_1_1kB_00_01Element_ea0a4e7ce3cd5d25cabf79383efdf4d9.html#afdcfb9753cb39c899a9c0c72a827fb54">cutlass::gemm::warp::MmaSimtTileIterator&lt; Shape_, Operand::kB, Element_, layout::RowMajor, Policy_, PartitionsK, PartitionGroupSize &gt;</a>
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+ , <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaSimtTileIterator_3_01Shape___00_01Operand_1_1kB_00_01Element_ada156b62fcbdce47009c5bf1321c92c.html#a62f65b9d86da2381ae91798701b4dbea">cutlass::gemm::warp::MmaSimtTileIterator&lt; Shape_, Operand::kB, Element_, layout::RowMajorInterleaved&lt; 4 &gt;, Policy_, PartitionsK, PartitionGroupSize &gt;</a>
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+ , <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaSimtTileIterator_3_01Shape___00_01Operand_1_1kC_00_01Element_4ccafbc821b3a55cd532602442a74031.html#aaf542ea45305834e59af9c04d3be9532">cutlass::gemm::warp::MmaSimtTileIterator&lt; Shape_, Operand::kC, Element_, layout::ColumnMajor, Policy_ &gt;</a>
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+ , <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaSimtTileIterator_3_01Shape___00_01Operand_1_1kC_00_01Element_8f92ea79e85febb67169c4b2d94b1b20.html#a163b92e35601065588053e29ca2e77b2">cutlass::gemm::warp::MmaSimtTileIterator&lt; Shape_, Operand::kC, Element_, layout::RowMajor, Policy_ &gt;</a>
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+ , <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#a570f020d67995c1a7232e14ec07e3b0c">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::ColumnMajor, InstructionShape_, OpDelta_ &gt;</a>
264
+ , <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a94cf75f2354661fd5f7682f37ba79177">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::ColumnMajorInterleaved&lt; InterleavedN &gt;, InstructionShape_, OpDelta_ &gt;</a>
265
+ , <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a5804aaa9ff4b99b8e1baa0355d34e0c1">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::RowMajor, InstructionShape_, OpDelta_ &gt;</a>
266
+ , <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#a1a46c311062f11a9eb5a4f34407f022b">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::ColumnMajorTensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, int(128/sizeof(Element_))&gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;</a>
267
+ , <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#a6f96ec999bbddffcaca1a31aa31e9708">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::ColumnMajorTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;</a>
268
+ , <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#a6c481c9a25374ae10fc47e17d5736b89">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::RowMajorTensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, int(128/sizeof(Element_))&gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;</a>
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+ , <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#a2eb415e875f59697d8b38af6bfa540de">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::RowMajorTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;</a>
270
+ , <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a9faeee6e6b7c8a8aaa0b60a47b93476b">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::TensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, 64 &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;</a>
271
+ , <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#a0726a2e59e0eff3c40786d8712e47776">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::TensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;</a>
272
+ , <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaVoltaTensorOpAccumulatorTileIterator.html#a279a159ec2eec9a474465aa8365c643c">cutlass::gemm::warp::MmaVoltaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, Layout_, InstructionShape_, OpDelta_ &gt;</a>
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+ , <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaVoltaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operan0d3248553e52cd61ed8a2b3b12a20343.html#a7d8453d7701d5a41b517e877e202187a">cutlass::gemm::warp::MmaVoltaTensorOpMultiplicandTileIterator&lt; Shape_, Operand::kA, Element_, cutlass::layout::ColumnMajorVoltaTensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value &gt;, InstructionShape_, OpDelta_, 32 &gt;</a>
274
+ , <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaVoltaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operan34be8e21a40af3ebd2dc3dff460dca72.html#ae08a89a2167a7c857fe80ea2c856a51c">cutlass::gemm::warp::MmaVoltaTensorOpMultiplicandTileIterator&lt; Shape_, Operand::kA, Element_, cutlass::layout::VoltaTensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value &gt;, InstructionShape_, OpDelta_, 32 &gt;</a>
275
+ , <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaVoltaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand734577b7e54a074d143aba59828c2f2.html#a8eb60b70495618293bd218736ae54f86">cutlass::gemm::warp::MmaVoltaTensorOpMultiplicandTileIterator&lt; Shape_, Operand::kB, Element_, cutlass::layout::RowMajorVoltaTensorOpMultiplicandBCongruous&lt; sizeof_bits&lt; Element_ &gt;::value &gt;, InstructionShape_, OpDelta_, 32 &gt;</a>
276
+ , <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaVoltaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operan16c56cdc2dda5eeb996af8ec0242d501.html#a2ca3e91dcd8ab5b8a002d7d979ce0a3c">cutlass::gemm::warp::MmaVoltaTensorOpMultiplicandTileIterator&lt; Shape_, Operand::kB, Element_, cutlass::layout::VoltaTensorOpMultiplicandBCongruous&lt; sizeof_bits&lt; Element_ &gt;::value &gt;, InstructionShape_, OpDelta_, 32 &gt;</a>
277
+ , <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaVoltaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operan5a221944f4a0e16ccab77ba684856942.html#ad30f89112afa148f8827e4e4ee58d7d1">cutlass::gemm::warp::MmaVoltaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::ColumnMajorVoltaTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, KBlock &gt;, InstructionShape_, OpDelta_, 32 &gt;</a>
278
+ , <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaVoltaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operandcc9821c435540895138bc9af495f321.html#a84ec2d63c1898188aab44b9a577e5241">cutlass::gemm::warp::MmaVoltaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::RowMajorVoltaTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, KBlock &gt;, InstructionShape_, OpDelta_, 32 &gt;</a>
279
+ , <a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaVoltaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operana2f40b28f0d2286b84d86f7238d67b52.html#a2077809dab15c411f95d893766106f0c">cutlass::gemm::warp::MmaVoltaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::VoltaTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, KBlock &gt;, InstructionShape_, OpDelta_, 32 &gt;</a>
280
+ , <a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileIterator2dThreadTile_3_01Shape___00_0165b39a630d10785a3558406f9adb99b9.html#a3b94fd9b0cbdc4a57f1d6e45381e0cd3">cutlass::transform::threadblock::PredicatedTileIterator2dThreadTile&lt; Shape_, Element_, layout::ColumnMajor, AdvanceRank, ThreadMap_, Transpose_ &gt;</a>
281
+ , <a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileIterator2dThreadTile_3_01Shape___00_017a517f3c73efd795ab05059cc9b111e1.html#aed8636c2750ecb8d6901d658017c1fd2">cutlass::transform::threadblock::PredicatedTileIterator2dThreadTile&lt; Shape_, Element_, layout::PitchLinear, AdvanceRank, ThreadMap_, Transpose_ &gt;</a>
282
+ , <a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileIterator2dThreadTile_3_01Shape___00_013671177d6219bfeb0e1b4dc4c1b5bf11.html#a380b3dc2403001e307a84f1634968f4e">cutlass::transform::threadblock::PredicatedTileIterator2dThreadTile&lt; Shape_, Element_, layout::RowMajor, AdvanceRank, ThreadMap_, Transpose_ &gt;</a>
283
+ , <a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileIterator_3_01Shape___00_01Element___0068b3e874b5d93d11f0fa902c7f1d11d9.html#aa8647ab882cf2af303ee89beb641e909">cutlass::transform::threadblock::PredicatedTileIterator&lt; Shape_, Element_, layout::ColumnMajor, AdvanceRank, ThreadMap_, AccessSize &gt;</a>
284
+ , <a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1PredicatedTileIterator_3_01Shape___00_01Element___00f6b3a9dfab5e7c72d5233f7e5e6e3b9b.html#a4fc50f92e4b27f31123244caddee61cd">cutlass::transform::threadblock::PredicatedTileIterator&lt; Shape_, Element_, layout::ColumnMajorInterleaved&lt; InterleavedK &gt;, AdvanceRank, ThreadMap_, AccessSize &gt;</a>
285
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+ , <a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1RegularTileIterator2dThreadTile_3_01Shape___00_01Eleb60d066756d1c18f05fceee6a27bdb8a.html#a69f0e8654cb38dd51e6a35f41ec07356">cutlass::transform::threadblock::RegularTileIterator2dThreadTile&lt; Shape_, Element_, layout::ColumnMajorInterleaved&lt; 4 &gt;, AdvanceRank, ThreadMap_, Alignment &gt;</a>
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+ , <a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1RegularTileIterator2dThreadTile_3_01Shape___00_01Ele76ed82829532ae1c17f4c78158f036c7.html#af6e6a1e3d73cc7347d7ea3693485cbe3">cutlass::transform::threadblock::RegularTileIterator2dThreadTile&lt; Shape_, Element_, layout::PitchLinear, AdvanceRank, ThreadMap_, Alignment &gt;</a>
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+ , <a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1RegularTileIterator2dThreadTile_3_01Shape___00_01Ele654c8f6161ae5340f040397a4e2e045c.html#aba5f853121869a682770680b37bbb797">cutlass::transform::threadblock::RegularTileIterator2dThreadTile&lt; Shape_, Element_, layout::RowMajorInterleaved&lt; 4 &gt;, AdvanceRank, ThreadMap_, Alignment &gt;</a>
291
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+ , <a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1RegularTileIterator_3_01Shape___00_01Element___00_01187f8574e1fe9d7d5e8fbf09bd834bf0.html#aa63f6bca8828aceaa50026251b256017">cutlass::transform::threadblock::RegularTileIterator&lt; Shape_, Element_, layout::ColumnMajorVoltaTensorOpMultiplicandBCongruous&lt; sizeof_bits&lt; Element_ &gt;::value &gt;, AdvanceRank, ThreadMap_, Alignment &gt;</a>
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+ , <a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1RegularTileIterator_3_01Shape___00_01Element___00_01793f74bfd8f116a827948ab01a37349a.html#a6d8622732af94302d10263956e0a8366">cutlass::transform::threadblock::RegularTileIterator&lt; Shape_, Element_, layout::ColumnMajorVoltaTensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value &gt;, AdvanceRank, ThreadMap_, Alignment &gt;</a>
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+ , <a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1RegularTileIterator_3_01Shape___00_01Element___00_01bd31b3810c1fedf2e7e5959ff92b5d3d.html#a9d22c23f02e27d377e978a6bd55f2b6c">cutlass::transform::threadblock::RegularTileIterator&lt; Shape_, Element_, layout::ColumnMajorVoltaTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Shape_::kRow &gt;, AdvanceRank, ThreadMap_, Alignment &gt;</a>
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+ , <a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1RegularTileIterator_3_01Shape___00_01Element___00_0184a89653916f5d51ab59d1b386989a17.html#adcf3e59a87e7cadf97f9b60c1170a94d">cutlass::transform::threadblock::RegularTileIterator&lt; Shape_, Element_, layout::PitchLinear, AdvanceRank, ThreadMap_, Alignment &gt;</a>
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+ , <a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1RegularTileIterator_3_01Shape___00_01Element___00_01b3fa5720e807697de61b9f937b269cd0.html#af196db1a86dd1f953b54e981340fc937">cutlass::transform::threadblock::RegularTileIterator&lt; Shape_, Element_, layout::RowMajorVoltaTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Shape_::kColumn &gt;, AdvanceRank, ThreadMap_, Alignment &gt;</a>
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+ , <a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1RegularTileIterator_3_01Shape___00_01Element___00_01efd5013a2503d6567e2bf6b40c97360c.html#af6d73f3fc9fec9072ef5dbc3e146584f">cutlass::transform::threadblock::RegularTileIterator&lt; Shape_, Element_, layout::TensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, int(128/sizeof(Element_))&gt;, AdvanceRank, ThreadMap_, Alignment &gt;</a>
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+ , <a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1RegularTileIterator_3_01Shape___00_01Element___00_0197fef2242a3454a7d1cebe61aee28b43.html#a34e0c12a6dad7566c6278796f7600335">cutlass::transform::threadblock::RegularTileIterator&lt; Shape_, Element_, layout::TensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, AdvanceRank, ThreadMap_, Alignment &gt;</a>
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+ , <a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1RegularTileIterator_3_01Shape___00_01Element___00_01a75d2cd74e722d6ad6a3b41aabfd432d.html#a5bf53d8efe7308dd31e6b1e5b62472aa">cutlass::transform::threadblock::RegularTileIterator&lt; Shape_, Element_, layout::VoltaTensorOpMultiplicandBCongruous&lt; sizeof_bits&lt; Element_ &gt;::value &gt;, AdvanceRank, ThreadMap_, Alignment &gt;</a>
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+ , <a class="el" href="classcutlass_1_1transform_1_1threadblock_1_1RegularTileIterator_3_01Shape___00_01Element___00_01f96bbeb63e6d4ce4a2551279de3a9f0e.html#a5235b969e38a3c2b34ff994f39ffbc84">cutlass::transform::threadblock::RegularTileIterator&lt; Shape_, Element_, layout::VoltaTensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value &gt;, AdvanceRank, ThreadMap_, Alignment &gt;</a>
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+ </li>
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+ <li>lowest()
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+ : <a class="el" href="structstd_1_1numeric__limits_3_01cutlass_1_1half__t_01_4.html#ac2ae43139037875e38056a675ae1f6c4">std::numeric_limits&lt; cutlass::half_t &gt;</a>
312
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+ <li><a href="annotated.html"><span>Class&#160;List</span></a></li>
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+ <li><a href="classes.html"><span>Class&#160;Index</span></a></li>
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+ <li><a href="inherits.html"><span>Class&#160;Hierarchy</span></a></li>
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+ <li class="current"><a href="functions.html"><span>Class&#160;Members</span></a></li>
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+ <li class="current"><a href="functions_vars.html"><span>Variables</span></a></li>
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+ <li><a href="functions_type.html"><span>Typedefs</span></a></li>
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+ <li><a href="functions_enum.html"><span>Enumerations</span></a></li>
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+ <li><a href="functions_vars_c.html#index_c"><span>c</span></a></li>
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+ <li><a href="functions_vars_d.html#index_d"><span>d</span></a></li>
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+ <li class="current"><a href="functions_vars_h.html#index_h"><span>h</span></a></li>
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+ <li><a href="functions_vars_v.html#index_v"><span>v</span></a></li>
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+ <li><a href="functions_vars_w.html#index_w"><span>w</span></a></li>
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+ <div class="contents">
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+ &#160;
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+
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+ <h3><a class="anchor" id="index_h"></a>- h -</h3><ul>
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+ <li>has_denorm
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+ : <a class="el" href="structstd_1_1numeric__limits_3_01cutlass_1_1half__t_01_4.html#aaf46b5d03403828c1e6633fb714ffd84">std::numeric_limits&lt; cutlass::half_t &gt;</a>
135
+ </li>
136
+ <li>has_denorm_loss
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+ : <a class="el" href="structstd_1_1numeric__limits_3_01cutlass_1_1half__t_01_4.html#a8b371f82151fd0238b7da083fa2b87a9">std::numeric_limits&lt; cutlass::half_t &gt;</a>
138
+ </li>
139
+ <li>has_infinity
140
+ : <a class="el" href="structstd_1_1numeric__limits_3_01cutlass_1_1half__t_01_4.html#a6f7f2fbe6cd7a04803b90b8fa9172098">std::numeric_limits&lt; cutlass::half_t &gt;</a>
141
+ </li>
142
+ <li>has_quiet_NaN
143
+ : <a class="el" href="structstd_1_1numeric__limits_3_01cutlass_1_1half__t_01_4.html#a3d75832e46bc154758e35a03a624ccf8">std::numeric_limits&lt; cutlass::half_t &gt;</a>
144
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+ <li>has_signaling_NaN
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+ : <a class="el" href="structstd_1_1numeric__limits_3_01cutlass_1_1half__t_01_4.html#a68a0d0f6ecc2f3b84f2e71475b2c48bd">std::numeric_limits&lt; cutlass::half_t &gt;</a>
147
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148
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149
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+ </a> 1.8.11
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+ <a href="host_2tensor__foreach_8h.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span>&#160;<span class="comment">/***************************************************************************************************</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span>&#160;<span class="comment"> * Copyright (c) 2017-2019, NVIDIA CORPORATION. All rights reserved.</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span>&#160;<span class="comment"> * Redistribution and use in source and binary forms, with or without modification, are permitted</span></div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span>&#160;<span class="comment"> * provided that the following conditions are met:</span></div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span>&#160;<span class="comment"> * * Redistributions of source code must retain the above copyright notice, this list of</span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span>&#160;<span class="comment"> * conditions and the following disclaimer.</span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span>&#160;<span class="comment"> * * Redistributions in binary form must reproduce the above copyright notice, this list of</span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span>&#160;<span class="comment"> * conditions and the following disclaimer in the documentation and/or other materials</span></div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span>&#160;<span class="comment"> * provided with the distribution.</span></div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span>&#160;<span class="comment"> * * Neither the name of the NVIDIA CORPORATION nor the names of its contributors may be used</span></div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span>&#160;<span class="comment"> * to endorse or promote products derived from this software without specific prior written</span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span>&#160;<span class="comment"> * permission.</span></div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span>&#160;<span class="comment"> * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS &quot;AS IS&quot; AND ANY EXPRESS OR</span></div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span>&#160;<span class="comment"> * IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND</span></div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span>&#160;<span class="comment"> * FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL NVIDIA CORPORATION BE LIABLE</span></div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span>&#160;<span class="comment"> * FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,</span></div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span>&#160;<span class="comment"> * BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;</span></div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span>&#160;<span class="comment"> * OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT,</span></div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span>&#160;<span class="comment"> * STRICT LIABILITY, OR TOR (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE</span></div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span>&#160;<span class="comment"> * OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.</span></div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span>&#160;<span class="comment"> **************************************************************************************************/</span></div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span>&#160;<span class="preprocessor">#pragma once</span></div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span>&#160;</div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span>&#160;<span class="preprocessor">#include &lt;stdexcept&gt;</span></div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="cutlass_8h.html">cutlass/cutlass.h</a>&quot;</span></div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span>&#160;</div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span>&#160;<span class="keyword">namespace </span><a class="code" href="namespacecutlass.html">cutlass</a> {</div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span>&#160;<span class="keyword">namespace </span>reference {</div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span>&#160;<span class="keyword">namespace </span>host {</div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span>&#160;</div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span>&#160;</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>&#160;<span class="keyword">namespace </span>detail {</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>&#160;</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Func, <span class="keywordtype">int</span> Rank, <span class="keywordtype">int</span> RankRemaining&gt;</div><div class="line"><a name="l00041"></a><span class="lineno"><a class="line" href="structcutlass_1_1reference_1_1host_1_1detail_1_1TensorForEachHelper.html"> 41</a></span>&#160;<span class="keyword">struct </span><a class="code" href="structcutlass_1_1reference_1_1host_1_1detail_1_1TensorForEachHelper.html">TensorForEachHelper</a> {</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>&#160;</div><div class="line"><a name="l00044"></a><span class="lineno"><a class="line" href="structcutlass_1_1reference_1_1host_1_1detail_1_1TensorForEachHelper.html#a1161a761c596e714982fe30141211cca"> 44</a></span>&#160; <span class="keyword">static</span> <span class="keywordtype">int</span> <span class="keyword">const</span> <a class="code" href="structcutlass_1_1reference_1_1host_1_1detail_1_1TensorForEachHelper.html#a1161a761c596e714982fe30141211cca">kActiveRank</a> = Rank - RankRemaining - 1;</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>&#160;</div><div class="line"><a name="l00047"></a><span class="lineno"><a class="line" href="structcutlass_1_1reference_1_1host_1_1detail_1_1TensorForEachHelper.html#aa63906bbecfe42eec1991c9176f066d9"> 47</a></span>&#160; <a class="code" href="structcutlass_1_1reference_1_1host_1_1detail_1_1TensorForEachHelper.html#aa63906bbecfe42eec1991c9176f066d9">TensorForEachHelper</a>(</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>&#160; Func &amp;func,</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>&#160; <a class="code" href="structcutlass_1_1Coord.html">Coord&lt;Rank&gt;</a> <span class="keyword">const</span> &amp;extent,</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>&#160; <a class="code" href="structcutlass_1_1Coord.html">Coord&lt;Rank&gt;</a> &amp;coord) {</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>&#160;</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; extent.<a class="code" href="structcutlass_1_1Coord.html#a8a65128c86b236cd2bea875b85a34bc1">at</a>(kActiveRank); ++i) {</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>&#160; coord[<a class="code" href="structcutlass_1_1reference_1_1host_1_1detail_1_1TensorForEachHelper.html#a1161a761c596e714982fe30141211cca">kActiveRank</a>] = i;</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>&#160; <a class="code" href="structcutlass_1_1reference_1_1host_1_1detail_1_1TensorForEachHelper.html">TensorForEachHelper</a>&lt;Func, Rank, RankRemaining - 1&gt;(func, extent, coord);</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>&#160; }</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>&#160; }</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>&#160;};</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>&#160;</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Func, <span class="keywordtype">int</span> Rank&gt;</div><div class="line"><a name="l00061"></a><span class="lineno"><a class="line" href="structcutlass_1_1reference_1_1host_1_1detail_1_1TensorForEachHelper_3_01Func_00_01Rank_00_010_01_4.html"> 61</a></span>&#160;<span class="keyword">struct </span><a class="code" href="structcutlass_1_1reference_1_1host_1_1detail_1_1TensorForEachHelper.html">TensorForEachHelper</a>&lt;Func, Rank, 0&gt; {</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>&#160;</div><div class="line"><a name="l00064"></a><span class="lineno"><a class="line" href="structcutlass_1_1reference_1_1host_1_1detail_1_1TensorForEachHelper_3_01Func_00_01Rank_00_010_01_4.html#ac558396615146aba17f12df92757a8ea"> 64</a></span>&#160; <span class="keyword">static</span> <span class="keywordtype">int</span> <span class="keyword">const</span> <a class="code" href="structcutlass_1_1reference_1_1host_1_1detail_1_1TensorForEachHelper.html#a1161a761c596e714982fe30141211cca">kActiveRank</a> = Rank - 1;</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>&#160;</div><div class="line"><a name="l00067"></a><span class="lineno"><a class="line" href="structcutlass_1_1reference_1_1host_1_1detail_1_1TensorForEachHelper_3_01Func_00_01Rank_00_010_01_4.html#a5029a4405a9a5e64011addb43bb88120"> 67</a></span>&#160; <a class="code" href="structcutlass_1_1reference_1_1host_1_1detail_1_1TensorForEachHelper_3_01Func_00_01Rank_00_010_01_4.html#a5029a4405a9a5e64011addb43bb88120">TensorForEachHelper</a>(</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>&#160; Func &amp;func,</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>&#160; <a class="code" href="structcutlass_1_1Coord.html">Coord&lt;Rank&gt;</a> <span class="keyword">const</span> &amp;extent,</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>&#160; <a class="code" href="structcutlass_1_1Coord.html">Coord&lt;Rank&gt;</a> &amp;coord) {</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>&#160;</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; extent.<a class="code" href="structcutlass_1_1Coord.html#a8a65128c86b236cd2bea875b85a34bc1">at</a>(kActiveRank); ++i) {</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>&#160; coord[<a class="code" href="structcutlass_1_1reference_1_1host_1_1detail_1_1TensorForEachHelper.html#a1161a761c596e714982fe30141211cca">kActiveRank</a>] = i;</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>&#160; func(coord);</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>&#160; }</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>&#160; }</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>&#160;};</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>&#160;</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>&#160;} <span class="comment">// namespace detail</span></div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>&#160;</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>&#160;</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>&#160;<span class="keyword">template</span> &lt;</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>&#160; <span class="keyword">typename</span> Func, </div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>&#160; <span class="keywordtype">int</span> Rank&gt; </div><div class="line"><a name="l00087"></a><span class="lineno"><a class="line" href="namespacecutlass_1_1reference_1_1host.html#a8c798c04df572b34e3ed3976d69f993d"> 87</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="namespacecutlass_1_1reference_1_1host.html#a8c798c04df572b34e3ed3976d69f993d">TensorForEach</a>(<a class="code" href="structcutlass_1_1Coord.html">Coord&lt;Rank&gt;</a> extent, Func &amp; func) {</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>&#160; <a class="code" href="structcutlass_1_1Coord.html">Coord&lt;Rank&gt;</a> coord;</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>&#160; <a class="code" href="structcutlass_1_1reference_1_1host_1_1detail_1_1TensorForEachHelper.html">detail::TensorForEachHelper</a>&lt;Func, Rank, Rank - 1&gt;(func, extent, coord);</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>&#160;}</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>&#160;</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>&#160;</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>&#160;<span class="keyword">template</span> &lt;</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>&#160; <span class="keyword">typename</span> Func, </div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>&#160; <span class="keywordtype">int</span> Rank&gt; </div><div class="line"><a name="l00098"></a><span class="lineno"><a class="line" href="namespacecutlass_1_1reference_1_1host.html#a3825b1aaaf5e5abf0de5f427e3481ada"> 98</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="namespacecutlass_1_1reference_1_1host.html#a3825b1aaaf5e5abf0de5f427e3481ada">TensorForEachLambda</a>(<a class="code" href="structcutlass_1_1Coord.html">Coord&lt;Rank&gt;</a> extent, Func func) {</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>&#160; <a class="code" href="structcutlass_1_1Coord.html">Coord&lt;Rank&gt;</a> coord;</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>&#160; <a class="code" href="structcutlass_1_1reference_1_1host_1_1detail_1_1TensorForEachHelper.html">detail::TensorForEachHelper</a>&lt;Func, Rank, Rank - 1&gt;(func, extent, coord);</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>&#160;}</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>&#160;</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>&#160;</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Element, <span class="keyword">typename</span> Func&gt;</div><div class="line"><a name="l00106"></a><span class="lineno"><a class="line" href="structcutlass_1_1reference_1_1host_1_1BlockForEach.html"> 106</a></span>&#160;<span class="keyword">struct </span><a class="code" href="structcutlass_1_1reference_1_1host_1_1BlockForEach.html">BlockForEach</a> {</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>&#160;</div><div class="line"><a name="l00109"></a><span class="lineno"><a class="line" href="structcutlass_1_1reference_1_1host_1_1BlockForEach.html#aa2e578397b5cd68214736c2437f92480"> 109</a></span>&#160; <a class="code" href="structcutlass_1_1reference_1_1host_1_1BlockForEach.html#aa2e578397b5cd68214736c2437f92480">BlockForEach</a>(</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>&#160; Element *ptr, </div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>&#160; <span class="keywordtype">size_t</span> capacity,</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>&#160; <span class="keyword">typename</span> Func::Params params = <span class="keyword">typename</span> Func::Params()) {</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>&#160; </div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>&#160; Func func(params);</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>&#160;</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> index = 0; index &lt; capacity; ++index) {</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>&#160; ptr[index] = func();</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>&#160; } </div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>&#160; }</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>&#160;};</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>&#160;</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>&#160;</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>&#160;} <span class="comment">// namespace host</span></div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>&#160;} <span class="comment">// namespace reference</span></div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>&#160;} <span class="comment">// namespace cutlass</span></div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>&#160;</div><div class="ttc" id="structcutlass_1_1reference_1_1host_1_1BlockForEach_html"><div class="ttname"><a href="structcutlass_1_1reference_1_1host_1_1BlockForEach.html">cutlass::reference::host::BlockForEach</a></div><div class="ttdef"><b>Definition:</b> host/tensor_foreach.h:106</div></div>
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+ <div class="ttc" id="namespacecutlass_html"><div class="ttname"><a href="namespacecutlass.html">cutlass</a></div><div class="ttdef"><b>Definition:</b> aligned_buffer.h:35</div></div>
103
+ <div class="ttc" id="structcutlass_1_1reference_1_1host_1_1BlockForEach_html_aa2e578397b5cd68214736c2437f92480"><div class="ttname"><a href="structcutlass_1_1reference_1_1host_1_1BlockForEach.html#aa2e578397b5cd68214736c2437f92480">cutlass::reference::host::BlockForEach::BlockForEach</a></div><div class="ttdeci">BlockForEach(Element *ptr, size_t capacity, typename Func::Params params=typename Func::Params())</div><div class="ttdoc">Constructor performs the operation. </div><div class="ttdef"><b>Definition:</b> host/tensor_foreach.h:109</div></div>
104
+ <div class="ttc" id="structcutlass_1_1reference_1_1host_1_1detail_1_1TensorForEachHelper_html_a1161a761c596e714982fe30141211cca"><div class="ttname"><a href="structcutlass_1_1reference_1_1host_1_1detail_1_1TensorForEachHelper.html#a1161a761c596e714982fe30141211cca">cutlass::reference::host::detail::TensorForEachHelper::kActiveRank</a></div><div class="ttdeci">static int const kActiveRank</div><div class="ttdoc">Index of the active rank. </div><div class="ttdef"><b>Definition:</b> host/tensor_foreach.h:44</div></div>
105
+ <div class="ttc" id="structcutlass_1_1reference_1_1host_1_1detail_1_1TensorForEachHelper_html_aa63906bbecfe42eec1991c9176f066d9"><div class="ttname"><a href="structcutlass_1_1reference_1_1host_1_1detail_1_1TensorForEachHelper.html#aa63906bbecfe42eec1991c9176f066d9">cutlass::reference::host::detail::TensorForEachHelper::TensorForEachHelper</a></div><div class="ttdeci">TensorForEachHelper(Func &amp;func, Coord&lt; Rank &gt; const &amp;extent, Coord&lt; Rank &gt; &amp;coord)</div><div class="ttdoc">Constructor for general rank. </div><div class="ttdef"><b>Definition:</b> host/tensor_foreach.h:47</div></div>
106
+ <div class="ttc" id="structcutlass_1_1reference_1_1host_1_1detail_1_1TensorForEachHelper_html"><div class="ttname"><a href="structcutlass_1_1reference_1_1host_1_1detail_1_1TensorForEachHelper.html">cutlass::reference::host::detail::TensorForEachHelper</a></div><div class="ttdoc">Helper to perform for-each operation. </div><div class="ttdef"><b>Definition:</b> host/tensor_foreach.h:41</div></div>
107
+ <div class="ttc" id="structcutlass_1_1reference_1_1host_1_1detail_1_1TensorForEachHelper_3_01Func_00_01Rank_00_010_01_4_html_a5029a4405a9a5e64011addb43bb88120"><div class="ttname"><a href="structcutlass_1_1reference_1_1host_1_1detail_1_1TensorForEachHelper_3_01Func_00_01Rank_00_010_01_4.html#a5029a4405a9a5e64011addb43bb88120">cutlass::reference::host::detail::TensorForEachHelper&lt; Func, Rank, 0 &gt;::TensorForEachHelper</a></div><div class="ttdeci">TensorForEachHelper(Func &amp;func, Coord&lt; Rank &gt; const &amp;extent, Coord&lt; Rank &gt; &amp;coord)</div><div class="ttdoc">Constructor for fastest changing rank. </div><div class="ttdef"><b>Definition:</b> host/tensor_foreach.h:67</div></div>
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+ <div class="ttc" id="structcutlass_1_1Coord_html"><div class="ttname"><a href="structcutlass_1_1Coord.html">cutlass::Coord</a></div><div class="ttdoc">Statically-sized array specifying Coords within a tensor. </div><div class="ttdef"><b>Definition:</b> coord.h:43</div></div>
109
+ <div class="ttc" id="namespacecutlass_1_1reference_1_1host_html_a3825b1aaaf5e5abf0de5f427e3481ada"><div class="ttname"><a href="namespacecutlass_1_1reference_1_1host.html#a3825b1aaaf5e5abf0de5f427e3481ada">cutlass::reference::host::TensorForEachLambda</a></div><div class="ttdeci">void TensorForEachLambda(Coord&lt; Rank &gt; extent, Func func)</div><div class="ttdoc">Iterates over the index space of a tensor and calls a C++ lambda. </div><div class="ttdef"><b>Definition:</b> host/tensor_foreach.h:98</div></div>
110
+ <div class="ttc" id="namespacecutlass_1_1reference_1_1host_html_a8c798c04df572b34e3ed3976d69f993d"><div class="ttname"><a href="namespacecutlass_1_1reference_1_1host.html#a8c798c04df572b34e3ed3976d69f993d">cutlass::reference::host::TensorForEach</a></div><div class="ttdeci">void TensorForEach(Coord&lt; Rank &gt; extent, Func &amp;func)</div><div class="ttdoc">Iterates over the index space of a tensor. </div><div class="ttdef"><b>Definition:</b> host/tensor_foreach.h:87</div></div>
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+ <tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
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+ <tr class="memitem:"><td class="memItemLeft" align="right" valign="top">struct &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1platform_1_1is__arithmetic.html">is_arithmetic</a></td></tr>
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+ <tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">std::is_arithmetic <a href="structcutlass_1_1platform_1_1is__arithmetic.html#details">More...</a><br /></td></tr>
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+ <tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
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+ <tr class="memitem:"><td class="memItemLeft" align="right" valign="top">struct &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1platform_1_1is__base__of.html">is_base_of</a></td></tr>
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+ <tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">std::is_base_of <a href="structcutlass_1_1platform_1_1is__base__of.html#details">More...</a><br /></td></tr>
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+ <tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
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+ <tr class="memitem:"><td class="memItemLeft" align="right" valign="top">struct &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1platform_1_1is__base__of__helper.html">is_base_of_helper</a></td></tr>
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+ <tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Helper for std::is_base_of. <a href="structcutlass_1_1platform_1_1is__base__of__helper.html#details">More...</a><br /></td></tr>
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+ <tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
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+ <tr class="memitem:"><td class="memItemLeft" align="right" valign="top">struct &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1platform_1_1is__floating__point.html">is_floating_point</a></td></tr>
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+ <tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">std::is_floating_point <a href="structcutlass_1_1platform_1_1is__floating__point.html#details">More...</a><br /></td></tr>
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+ <tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
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+ <tr class="memitem:"><td class="memItemLeft" align="right" valign="top">struct &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1platform_1_1is__fundamental.html">is_fundamental</a></td></tr>
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+ <tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">std::is_fundamental <a href="structcutlass_1_1platform_1_1is__fundamental.html#details">More...</a><br /></td></tr>
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+ <tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
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+ <tr class="memitem:"><td class="memItemLeft" align="right" valign="top">struct &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1platform_1_1is__integral.html">is_integral</a></td></tr>
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+ <tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">std::is_integral <a href="structcutlass_1_1platform_1_1is__integral.html#details">More...</a><br /></td></tr>
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+ <tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
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+ <tr class="memitem:"><td class="memItemLeft" align="right" valign="top">struct &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1platform_1_1is__integral_3_01char_01_4.html">is_integral&lt; char &gt;</a></td></tr>
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+ <tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
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+ <tr class="memitem:"><td class="memItemLeft" align="right" valign="top">struct &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1platform_1_1is__integral_3_01const_01T_01_4.html">is_integral&lt; const T &gt;</a></td></tr>
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+ <tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
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+ <tr class="memitem:"><td class="memItemLeft" align="right" valign="top">struct &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1platform_1_1is__integral_3_01const_01volatile_01T_01_4.html">is_integral&lt; const volatile T &gt;</a></td></tr>
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+ <tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
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+ <tr class="memitem:"><td class="memItemLeft" align="right" valign="top">struct &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1platform_1_1is__integral_3_01int_01_4.html">is_integral&lt; int &gt;</a></td></tr>
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+ <tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
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+ <tr class="memitem:"><td class="memItemLeft" align="right" valign="top">struct &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1platform_1_1is__integral_3_01long_01_4.html">is_integral&lt; long &gt;</a></td></tr>
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+ <tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
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+ <tr class="memitem:"><td class="memItemLeft" align="right" valign="top">struct &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1platform_1_1is__integral_3_01long_01long_01_4.html">is_integral&lt; long long &gt;</a></td></tr>
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+ <tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
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+ <tr class="memitem:"><td class="memItemLeft" align="right" valign="top">struct &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1platform_1_1is__integral_3_01short_01_4.html">is_integral&lt; short &gt;</a></td></tr>
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+ <tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
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+ <tr class="memitem:"><td class="memItemLeft" align="right" valign="top">struct &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1platform_1_1is__integral_3_01signed_01char_01_4.html">is_integral&lt; signed char &gt;</a></td></tr>
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+ <tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
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+ <tr class="memitem:"><td class="memItemLeft" align="right" valign="top">struct &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1platform_1_1is__integral_3_01unsigned_01char_01_4.html">is_integral&lt; unsigned char &gt;</a></td></tr>
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+ <tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
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+ <tr class="memitem:"><td class="memItemLeft" align="right" valign="top">struct &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1platform_1_1is__integral_3_01unsigned_01int_01_4.html">is_integral&lt; unsigned int &gt;</a></td></tr>
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+ <tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
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+ <tr class="memitem:"><td class="memItemLeft" align="right" valign="top">struct &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1platform_1_1is__integral_3_01unsigned_01long_01_4.html">is_integral&lt; unsigned long &gt;</a></td></tr>
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+ <tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
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+ <tr class="memitem:"><td class="memItemLeft" align="right" valign="top">struct &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1platform_1_1is__integral_3_01unsigned_01long_01long_01_4.html">is_integral&lt; unsigned long long &gt;</a></td></tr>
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+ <tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
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+ <tr class="memitem:"><td class="memItemLeft" align="right" valign="top">struct &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1platform_1_1is__integral_3_01unsigned_01short_01_4.html">is_integral&lt; unsigned short &gt;</a></td></tr>
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+ <tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
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+ <tr class="memitem:"><td class="memItemLeft" align="right" valign="top">struct &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1platform_1_1is__integral_3_01volatile_01T_01_4.html">is_integral&lt; volatile T &gt;</a></td></tr>
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+ <tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
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+ <tr class="memitem:"><td class="memItemLeft" align="right" valign="top">struct &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1platform_1_1is__pointer.html">is_pointer</a></td></tr>
215
+ <tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">std::is_pointer <a href="structcutlass_1_1platform_1_1is__pointer.html#details">More...</a><br /></td></tr>
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+ <tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
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+ <tr class="memitem:"><td class="memItemLeft" align="right" valign="top">struct &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1platform_1_1is__pointer__helper.html">is_pointer_helper</a></td></tr>
218
+ <tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Helper for std::is_pointer (false specialization) <a href="structcutlass_1_1platform_1_1is__pointer__helper.html#details">More...</a><br /></td></tr>
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+ <tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
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+ <tr class="memitem:"><td class="memItemLeft" align="right" valign="top">struct &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1platform_1_1is__pointer__helper_3_01T_01_5_01_4.html">is_pointer_helper&lt; T * &gt;</a></td></tr>
221
+ <tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Helper for std::is_pointer (true specialization) <a href="structcutlass_1_1platform_1_1is__pointer__helper_3_01T_01_5_01_4.html#details">More...</a><br /></td></tr>
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+ <tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
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+ <tr class="memitem:"><td class="memItemLeft" align="right" valign="top">struct &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1platform_1_1is__same.html">is_same</a></td></tr>
224
+ <tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">std::is_same (false specialization) <a href="structcutlass_1_1platform_1_1is__same.html#details">More...</a><br /></td></tr>
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+ <tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
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+ <tr class="memitem:"><td class="memItemLeft" align="right" valign="top">struct &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1platform_1_1is__same_3_01A_00_01A_01_4.html">is_same&lt; A, A &gt;</a></td></tr>
227
+ <tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">std::is_same (true specialization) <a href="structcutlass_1_1platform_1_1is__same_3_01A_00_01A_01_4.html#details">More...</a><br /></td></tr>
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+ <tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
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+ <tr class="memitem:"><td class="memItemLeft" align="right" valign="top">struct &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1platform_1_1is__trivially__copyable.html">is_trivially_copyable</a></td></tr>
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+ <tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
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+ <tr class="memitem:"><td class="memItemLeft" align="right" valign="top">struct &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1platform_1_1is__void.html">is_void</a></td></tr>
232
+ <tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">std::is_void <a href="structcutlass_1_1platform_1_1is__void.html#details">More...</a><br /></td></tr>
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+ <tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
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+ <tr class="memitem:"><td class="memItemLeft" align="right" valign="top">struct &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1platform_1_1is__volatile.html">is_volatile</a></td></tr>
235
+ <tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">std::is_volatile <a href="structcutlass_1_1platform_1_1is__volatile.html#details">More...</a><br /></td></tr>
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+ <tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
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+ <tr class="memitem:"><td class="memItemLeft" align="right" valign="top">struct &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1platform_1_1is__volatile_3_01volatile_01T_01_4.html">is_volatile&lt; volatile T &gt;</a></td></tr>
238
+ <tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
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+ <tr class="memitem:"><td class="memItemLeft" align="right" valign="top">struct &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1platform_1_1nullptr__t.html">nullptr_t</a></td></tr>
240
+ <tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">std::nullptr_t <a href="structcutlass_1_1platform_1_1nullptr__t.html#details">More...</a><br /></td></tr>
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+ <tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
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+ <tr class="memitem:"><td class="memItemLeft" align="right" valign="top">struct &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1platform_1_1remove__const.html">remove_const</a></td></tr>
243
+ <tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">std::remove_const (non-const specialization) <a href="structcutlass_1_1platform_1_1remove__const.html#details">More...</a><br /></td></tr>
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+ <tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
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+ <tr class="memitem:"><td class="memItemLeft" align="right" valign="top">struct &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1platform_1_1remove__const_3_01const_01T_01_4.html">remove_const&lt; const T &gt;</a></td></tr>
246
+ <tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">std::remove_const (const specialization) <a href="structcutlass_1_1platform_1_1remove__const_3_01const_01T_01_4.html#details">More...</a><br /></td></tr>
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+ <tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
248
+ <tr class="memitem:"><td class="memItemLeft" align="right" valign="top">struct &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1platform_1_1remove__cv.html">remove_cv</a></td></tr>
249
+ <tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">std::remove_cv <a href="structcutlass_1_1platform_1_1remove__cv.html#details">More...</a><br /></td></tr>
250
+ <tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
251
+ <tr class="memitem:"><td class="memItemLeft" align="right" valign="top">struct &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1platform_1_1remove__volatile.html">remove_volatile</a></td></tr>
252
+ <tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">std::remove_volatile (non-volatile specialization) <a href="structcutlass_1_1platform_1_1remove__volatile.html#details">More...</a><br /></td></tr>
253
+ <tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
254
+ <tr class="memitem:"><td class="memItemLeft" align="right" valign="top">struct &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1platform_1_1remove__volatile_3_01volatile_01T_01_4.html">remove_volatile&lt; volatile T &gt;</a></td></tr>
255
+ <tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">std::remove_volatile (volatile specialization) <a href="structcutlass_1_1platform_1_1remove__volatile_3_01volatile_01T_01_4.html#details">More...</a><br /></td></tr>
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+ <tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
257
+ <tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classcutlass_1_1platform_1_1unique__ptr.html">unique_ptr</a></td></tr>
258
+ <tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">std::unique_ptr <a href="classcutlass_1_1platform_1_1unique__ptr.html#details">More...</a><br /></td></tr>
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+ <tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
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+ </table><table class="memberdecls">
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+ <tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="typedef-members"></a>
262
+ Typedefs</h2></td></tr>
263
+ <tr class="memitem:a0eddc4a3921e137f31fd8014be96e807"><td class="memItemLeft" align="right" valign="top">typedef <a class="el" href="structcutlass_1_1platform_1_1integral__constant.html">integral_constant</a>&lt; bool, true &gt;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacecutlass_1_1platform.html#a0eddc4a3921e137f31fd8014be96e807">true_type</a></td></tr>
264
+ <tr class="memdesc:a0eddc4a3921e137f31fd8014be96e807"><td class="mdescLeft">&#160;</td><td class="mdescRight">The type used as a compile-time boolean with true value. <a href="#a0eddc4a3921e137f31fd8014be96e807">More...</a><br /></td></tr>
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+ <tr class="separator:a0eddc4a3921e137f31fd8014be96e807"><td class="memSeparator" colspan="2">&#160;</td></tr>
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+ <tr class="memitem:ad8c95b2109070847b13d355120344380"><td class="memItemLeft" align="right" valign="top">typedef <a class="el" href="structcutlass_1_1platform_1_1integral__constant.html">integral_constant</a>&lt; bool, false &gt;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacecutlass_1_1platform.html#ad8c95b2109070847b13d355120344380">false_type</a></td></tr>
267
+ <tr class="memdesc:ad8c95b2109070847b13d355120344380"><td class="mdescLeft">&#160;</td><td class="mdescRight">The type used as a compile-time boolean with false value. <a href="#ad8c95b2109070847b13d355120344380">More...</a><br /></td></tr>
268
+ <tr class="separator:ad8c95b2109070847b13d355120344380"><td class="memSeparator" colspan="2">&#160;</td></tr>
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+ </table><table class="memberdecls">
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+ <tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="func-members"></a>
271
+ Functions</h2></td></tr>
272
+ <tr class="memitem:a57c071d2a7305dd4ec60542e66b0c81c"><td class="memTemplParams" colspan="2">template&lt;typename T &gt; </td></tr>
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+ <tr class="memitem:a57c071d2a7305dd4ec60542e66b0c81c"><td class="memTemplItemLeft" align="right" valign="top"><a class="el" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a> <a class="el" href="platform_8h.html#a72f0657181cca64b44eb186b707eb380">constexpr</a> const T &amp;&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacecutlass_1_1platform.html#a57c071d2a7305dd4ec60542e66b0c81c">min</a> (const T &amp;a, const T &amp;b)</td></tr>
274
+ <tr class="memdesc:a57c071d2a7305dd4ec60542e66b0c81c"><td class="mdescLeft">&#160;</td><td class="mdescRight">std::min <a href="#a57c071d2a7305dd4ec60542e66b0c81c">More...</a><br /></td></tr>
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+ <tr class="separator:a57c071d2a7305dd4ec60542e66b0c81c"><td class="memSeparator" colspan="2">&#160;</td></tr>
276
+ <tr class="memitem:af6a9a165e53d7e85ae121d5789aa03e0"><td class="memTemplParams" colspan="2">template&lt;typename T &gt; </td></tr>
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+ <tr class="memitem:af6a9a165e53d7e85ae121d5789aa03e0"><td class="memTemplItemLeft" align="right" valign="top"><a class="el" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a> <a class="el" href="platform_8h.html#a72f0657181cca64b44eb186b707eb380">constexpr</a> const T &amp;&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacecutlass_1_1platform.html#af6a9a165e53d7e85ae121d5789aa03e0">max</a> (const T &amp;a, const T &amp;b)</td></tr>
278
+ <tr class="memdesc:af6a9a165e53d7e85ae121d5789aa03e0"><td class="mdescLeft">&#160;</td><td class="mdescRight">std::max <a href="#af6a9a165e53d7e85ae121d5789aa03e0">More...</a><br /></td></tr>
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+ <tr class="separator:af6a9a165e53d7e85ae121d5789aa03e0"><td class="memSeparator" colspan="2">&#160;</td></tr>
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+ <tr class="memitem:ab9b8306ae9dc21fa646c49b68fa8e197"><td class="memTemplParams" colspan="2">template&lt;class T1 , class T2 &gt; </td></tr>
281
+ <tr class="memitem:ab9b8306ae9dc21fa646c49b68fa8e197"><td class="memTemplItemLeft" align="right" valign="top"><a class="el" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a> <a class="el" href="platform_8h.html#a72f0657181cca64b44eb186b707eb380">constexpr</a> bool&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacecutlass_1_1platform.html#ab9b8306ae9dc21fa646c49b68fa8e197">operator==</a> (const pair&lt; T1, T2 &gt; &amp;lhs, const pair&lt; T1, T2 &gt; &amp;rhs)</td></tr>
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+ <tr class="separator:ab9b8306ae9dc21fa646c49b68fa8e197"><td class="memSeparator" colspan="2">&#160;</td></tr>
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+ <tr class="memitem:a3e83320a39137d92042eb0bf93be9678"><td class="memTemplItemLeft" align="right" valign="top">void&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacecutlass_1_1platform.html#a3e83320a39137d92042eb0bf93be9678">swap</a> (<a class="el" href="classcutlass_1_1platform_1_1unique__ptr.html">unique_ptr</a>&lt; T, Deleter &gt; &amp;lhs, <a class="el" href="classcutlass_1_1platform_1_1unique__ptr.html">unique_ptr</a>&lt; T, Deleter &gt; &amp;rhs) <a class="el" href="platform_8h.html#a189faadd7f99f6c354db09acbb2aafcd">noexcept</a></td></tr>
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+ <div class="memproto">
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+ <div class="memtemplate">
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+ template&lt;&gt; </div>
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+ <tr>
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+ <td class="memname">struct cutlass::platform::__align__ </td>
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+ <td>(</td>
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+ </div><div class="memdoc">
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+ <div class="memitem">
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+ <div class="memproto">
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+ template&lt;&gt; </div>
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+ <table class="memname">
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+ <tr>
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+ <td class="memname">struct cutlass::platform::__align__ </td>
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+ <td>(</td>
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+ <td class="paramtype">2&#160;</td>
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+ <td class="paramname"></td><td>)</td>
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+ <td></td>
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+ </tr>
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+ <div class="memitem">
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+ <div class="memproto">
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+ template&lt;&gt; </div>
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+ <tr>
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+ <td class="memname">struct cutlass::platform::__align__ </td>
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+ <td>(</td>
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+ <td></td>
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+ </tr>
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+ <div class="memitem">
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+ <div class="memproto">
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+ <div class="memtemplate">
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+ template&lt;&gt; </div>
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+ <tr>
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+ <td class="memname">struct cutlass::platform::__align__ </td>
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+ <td>(</td>
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+ <td></td>
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+ <div class="memitem">
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+ <div class="memproto">
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+ template&lt;&gt; </div>
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+ <table class="memname">
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+ <tr>
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+ <td class="memname">struct cutlass::platform::__align__ </td>
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+ <td>(</td>
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+ <div class="memitem">
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+ <div class="memproto">
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+ template&lt;&gt; </div>
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+ <td>(</td>
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+ <li class="navelem"><a class="el" href="namespacecutlass.html">cutlass</a></li><li class="navelem"><a class="el" href="namespacecutlass_1_1epilogue.html">epilogue</a></li><li class="navelem"><a class="el" href="namespacecutlass_1_1epilogue_1_1threadblock.html">threadblock</a></li><li class="navelem"><a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html">DefaultEpilogueComplexTensorOp</a></li> </ul>
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+ <div class="header">
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+ <div class="summary">
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+ <a href="#pub-types">Public Types</a> &#124;
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+ <a href="#pub-static-attribs">Static Public Attributes</a> &#124;
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+ <a href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp-members.html">List of all members</a> </div>
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+ <div class="headertitle">
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+ <div class="title">cutlass::epilogue::threadblock::DefaultEpilogueComplexTensorOp&lt; Shape_, WarpMmaTensorOp_, PartitionsK, OutputOp_, ElementsPerAccess &gt; Struct Template Reference</div> </div>
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+ </div><!--header-->
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+ <div class="contents">
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+
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+ <p>Defines sensible defaults for epilogues for TensorOps.
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+ </p>
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+
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+ <p><code>#include &lt;<a class="el" href="default__epilogue__complex__tensor__op_8h_source.html">default_epilogue_complex_tensor_op.h</a>&gt;</code></p>
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+ <table class="memberdecls">
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+ Public Types</h2></td></tr>
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+ <tr class="memitem:a3103ac8f979c182f26c3b80ce15643f6"><td class="memItemLeft" align="right" valign="top">using&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a3103ac8f979c182f26c3b80ce15643f6">Shape</a> = Shape_</td></tr>
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+ <tr class="separator:a3103ac8f979c182f26c3b80ce15643f6"><td class="memSeparator" colspan="2">&#160;</td></tr>
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+ <tr class="separator:a9323e876327a9bfe0f277b78c787ec01"><td class="memSeparator" colspan="2">&#160;</td></tr>
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+ <tr class="memitem:a1021107776d67cf428dfd799bbaaa02f"><td class="memItemLeft" align="right" valign="top">using&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a1021107776d67cf428dfd799bbaaa02f">ElementOutput</a> = typename OutputOp::ElementOutput</td></tr>
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+ <tr class="separator:a1021107776d67cf428dfd799bbaaa02f"><td class="memSeparator" colspan="2">&#160;</td></tr>
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+ <tr class="memitem:a89a49a6d25f358cffe669ece2abe2f11"><td class="memItemLeft" align="right" valign="top">using&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a89a49a6d25f358cffe669ece2abe2f11">LayoutC</a> = typename WarpMmaTensorOp::LayoutC</td></tr>
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+ <tr class="separator:a89a49a6d25f358cffe669ece2abe2f11"><td class="memSeparator" colspan="2">&#160;</td></tr>
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+ <tr class="separator:a43ad144aa28bab769fa744744eb0321a"><td class="memSeparator" colspan="2">&#160;</td></tr>
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+ <tr class="memitem:adb357c79d059162f558cfeab52484fca"><td class="memItemLeft" align="right" valign="top">using&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#adb357c79d059162f558cfeab52484fca">OutputTileThreadMap</a> = typename <a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapTensorOp.html">cutlass::epilogue::threadblock::DefaultThreadMapTensorOp</a>&lt; <a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a3103ac8f979c182f26c3b80ce15643f6">Shape</a>, typename WarpMmaTensorOp::Shape, <a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a6a7770417159c242d8252998aebfa96e">kPartitionsK</a>, <a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a1021107776d67cf428dfd799bbaaa02f">ElementOutput</a>, <a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#afc3c42f94722a38fbf23436fc16320e5">kElementsPerAccess</a> &gt;::Type</td></tr>
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+ <tr class="memitem:ab421b49d591111d62eac560f8b96c10a"><td class="memItemLeft" align="right" valign="top">using&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#ab421b49d591111d62eac560f8b96c10a">OutputTileIterator</a> = <a class="el" href="classcutlass_1_1epilogue_1_1threadblock_1_1PredicatedTileIterator.html">cutlass::epilogue::threadblock::PredicatedTileIterator</a>&lt; <a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#adb357c79d059162f558cfeab52484fca">OutputTileThreadMap</a>, <a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a1021107776d67cf428dfd799bbaaa02f">ElementOutput</a> &gt;</td></tr>
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+ <tr class="separator:ab421b49d591111d62eac560f8b96c10a"><td class="memSeparator" colspan="2">&#160;</td></tr>
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+ <tr class="memitem:a9c88165210cc6535336db0e5043fa10f"><td class="memItemLeft" align="right" valign="top">using&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a9c88165210cc6535336db0e5043fa10f">AccumulatorFragmentIterator</a> = <a class="el" href="classcutlass_1_1epilogue_1_1warp_1_1FragmentIteratorComplexTensorOp.html">cutlass::epilogue::warp::FragmentIteratorComplexTensorOp</a>&lt; typename WarpMmaTensorOp::Shape, typename WarpMmaTensorOp::Policy::Operator::Shape, typename WarpMmaTensorOp::Policy::Operator::ElementC, typename WarpMmaTensorOp::Policy::Operator::FragmentC, <a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a89a49a6d25f358cffe669ece2abe2f11">LayoutC</a> &gt;</td></tr>
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+ <tr class="separator:a9c88165210cc6535336db0e5043fa10f"><td class="memSeparator" colspan="2">&#160;</td></tr>
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+ <tr class="memitem:ac41f55deccd93d0ca21c75bd1b311658"><td class="memItemLeft" align="right" valign="top">using&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#ac41f55deccd93d0ca21c75bd1b311658">WarpTileIterator</a> = <a class="el" href="classcutlass_1_1epilogue_1_1warp_1_1TileIteratorTensorOp.html">cutlass::epilogue::warp::TileIteratorTensorOp</a>&lt; typename WarpMmaTensorOp::Shape, typename WarpMmaTensorOp::Policy::Operator::Shape, <a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a43ad144aa28bab769fa744744eb0321a">ElementAccumulator</a>, <a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a89a49a6d25f358cffe669ece2abe2f11">LayoutC</a> &gt;</td></tr>
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+ <tr class="separator:ac41f55deccd93d0ca21c75bd1b311658"><td class="memSeparator" colspan="2">&#160;</td></tr>
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+ <tr class="memitem:af85ee3278368759b9876c07124b09ffd"><td class="memItemLeft" align="right" valign="top">using&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#af85ee3278368759b9876c07124b09ffd">SharedLoadIterator</a> = <a class="el" href="classcutlass_1_1epilogue_1_1threadblock_1_1SharedLoadIterator.html">cutlass::epilogue::threadblock::SharedLoadIterator</a>&lt; typename OutputTileThreadMap::CompactedThreadMap, <a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a43ad144aa28bab769fa744744eb0321a">ElementAccumulator</a> &gt;</td></tr>
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+ <tr class="separator:af85ee3278368759b9876c07124b09ffd"><td class="memSeparator" colspan="2">&#160;</td></tr>
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+ <tr class="memdesc:a6685913f5820773e1b26ea2eb76866cd"><td class="mdescLeft">&#160;</td><td class="mdescRight">Hard-coded padding elements added. <a href="#a6685913f5820773e1b26ea2eb76866cd">More...</a><br /></td></tr>
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+ <tr class="separator:a6685913f5820773e1b26ea2eb76866cd"><td class="memSeparator" colspan="2">&#160;</td></tr>
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+ <tr class="memitem:ae035b28fb369d5eafa086e1fcb8b6b0f"><td class="memItemLeft" align="right" valign="top">using&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#ae035b28fb369d5eafa086e1fcb8b6b0f">Epilogue</a> = <a class="el" href="classcutlass_1_1epilogue_1_1threadblock_1_1Epilogue.html">cutlass::epilogue::threadblock::Epilogue</a>&lt; <a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a3103ac8f979c182f26c3b80ce15643f6">Shape</a>, <a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a9323e876327a9bfe0f277b78c787ec01">WarpMmaTensorOp</a>, <a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a6a7770417159c242d8252998aebfa96e">kPartitionsK</a>, <a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#ab421b49d591111d62eac560f8b96c10a">OutputTileIterator</a>, <a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a9c88165210cc6535336db0e5043fa10f">AccumulatorFragmentIterator</a>, <a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#ac41f55deccd93d0ca21c75bd1b311658">WarpTileIterator</a>, <a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#af85ee3278368759b9876c07124b09ffd">SharedLoadIterator</a>, <a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a517049715fcabdb536f278604477829e">OutputOp</a>, <a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a6685913f5820773e1b26ea2eb76866cd">Padding</a> &gt;</td></tr>
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+ <tr class="separator:ae035b28fb369d5eafa086e1fcb8b6b0f"><td class="memSeparator" colspan="2">&#160;</td></tr>
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+ </table><table class="memberdecls">
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+ <tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-static-attribs"></a>
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+ Static Public Attributes</h2></td></tr>
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+ <tr class="memitem:a6a7770417159c242d8252998aebfa96e"><td class="memItemLeft" align="right" valign="top">static int const&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a6a7770417159c242d8252998aebfa96e">kPartitionsK</a> = PartitionsK</td></tr>
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+ <tr class="separator:a6a7770417159c242d8252998aebfa96e"><td class="memSeparator" colspan="2">&#160;</td></tr>
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+ <tr class="memitem:afc3c42f94722a38fbf23436fc16320e5"><td class="memItemLeft" align="right" valign="top">static int const&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#afc3c42f94722a38fbf23436fc16320e5">kElementsPerAccess</a> = ElementsPerAccess</td></tr>
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+ <tr class="separator:afc3c42f94722a38fbf23436fc16320e5"><td class="memSeparator" colspan="2">&#160;</td></tr>
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+ </table>
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+ <h2 class="groupheader">Member Typedef Documentation</h2>
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+ <a class="anchor" id="a9c88165210cc6535336db0e5043fa10f"></a>
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+ <div class="memitem">
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+ <div class="memproto">
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+ <div class="memtemplate">
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+ template&lt;typename Shape_ , typename WarpMmaTensorOp_ , int PartitionsK, typename OutputOp_ , int ElementsPerAccess&gt; </div>
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+ <table class="memname">
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+ <tr>
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+ <td class="memname">using <a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html">cutlass::epilogue::threadblock::DefaultEpilogueComplexTensorOp</a>&lt; Shape_, WarpMmaTensorOp_, PartitionsK, OutputOp_, ElementsPerAccess &gt;::<a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a9c88165210cc6535336db0e5043fa10f">AccumulatorFragmentIterator</a> = <a class="el" href="classcutlass_1_1epilogue_1_1warp_1_1FragmentIteratorComplexTensorOp.html">cutlass::epilogue::warp::FragmentIteratorComplexTensorOp</a>&lt; typename WarpMmaTensorOp::Shape, typename WarpMmaTensorOp::Policy::Operator::Shape, typename WarpMmaTensorOp::Policy::Operator::ElementC, typename WarpMmaTensorOp::Policy::Operator::FragmentC, <a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a89a49a6d25f358cffe669ece2abe2f11">LayoutC</a> &gt;</td>
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+ </tr>
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+ </table>
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+ </div><div class="memdoc">
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+
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+ </div>
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+ </div>
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+ <a class="anchor" id="a43ad144aa28bab769fa744744eb0321a"></a>
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+ <div class="memitem">
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+ <div class="memproto">
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+ <div class="memtemplate">
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+ template&lt;typename Shape_ , typename WarpMmaTensorOp_ , int PartitionsK, typename OutputOp_ , int ElementsPerAccess&gt; </div>
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+ <table class="memname">
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+ <tr>
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+ <td class="memname">using <a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html">cutlass::epilogue::threadblock::DefaultEpilogueComplexTensorOp</a>&lt; Shape_, WarpMmaTensorOp_, PartitionsK, OutputOp_, ElementsPerAccess &gt;::<a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a43ad144aa28bab769fa744744eb0321a">ElementAccumulator</a> = typename WarpMmaTensorOp::ElementC</td>
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+ </tr>
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+ </table>
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+ </div><div class="memdoc">
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+
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+ </div>
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+ </div>
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+ <a class="anchor" id="a1021107776d67cf428dfd799bbaaa02f"></a>
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+ <div class="memitem">
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+ <div class="memproto">
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+ <div class="memtemplate">
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+ template&lt;typename Shape_ , typename WarpMmaTensorOp_ , int PartitionsK, typename OutputOp_ , int ElementsPerAccess&gt; </div>
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+ <table class="memname">
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+ <tr>
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+ <td class="memname">using <a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html">cutlass::epilogue::threadblock::DefaultEpilogueComplexTensorOp</a>&lt; Shape_, WarpMmaTensorOp_, PartitionsK, OutputOp_, ElementsPerAccess &gt;::<a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a1021107776d67cf428dfd799bbaaa02f">ElementOutput</a> = typename OutputOp::ElementOutput</td>
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+ </tr>
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+ </table>
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+ </div><div class="memdoc">
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+
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+ </div>
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+ </div>
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+ <a class="anchor" id="ae035b28fb369d5eafa086e1fcb8b6b0f"></a>
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+ <div class="memitem">
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+ <div class="memproto">
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+ <div class="memtemplate">
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+ template&lt;typename Shape_ , typename WarpMmaTensorOp_ , int PartitionsK, typename OutputOp_ , int ElementsPerAccess&gt; </div>
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+ <table class="memname">
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+ <tr>
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+ <td class="memname">using <a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html">cutlass::epilogue::threadblock::DefaultEpilogueComplexTensorOp</a>&lt; Shape_, WarpMmaTensorOp_, PartitionsK, OutputOp_, ElementsPerAccess &gt;::<a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#ae035b28fb369d5eafa086e1fcb8b6b0f">Epilogue</a> = <a class="el" href="classcutlass_1_1epilogue_1_1threadblock_1_1Epilogue.html">cutlass::epilogue::threadblock::Epilogue</a>&lt; <a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a3103ac8f979c182f26c3b80ce15643f6">Shape</a>, <a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a9323e876327a9bfe0f277b78c787ec01">WarpMmaTensorOp</a>, <a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a6a7770417159c242d8252998aebfa96e">kPartitionsK</a>, <a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#ab421b49d591111d62eac560f8b96c10a">OutputTileIterator</a>, <a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a9c88165210cc6535336db0e5043fa10f">AccumulatorFragmentIterator</a>, <a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#ac41f55deccd93d0ca21c75bd1b311658">WarpTileIterator</a>, <a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#af85ee3278368759b9876c07124b09ffd">SharedLoadIterator</a>, <a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a517049715fcabdb536f278604477829e">OutputOp</a>, <a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a6685913f5820773e1b26ea2eb76866cd">Padding</a> &gt;</td>
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+ </tr>
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+ </table>
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+ </div><div class="memdoc">
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+
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+ </div>
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+ </div>
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+ <a class="anchor" id="a89a49a6d25f358cffe669ece2abe2f11"></a>
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+ <div class="memitem">
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+ <div class="memproto">
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+ <div class="memtemplate">
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+ template&lt;typename Shape_ , typename WarpMmaTensorOp_ , int PartitionsK, typename OutputOp_ , int ElementsPerAccess&gt; </div>
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+ <table class="memname">
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+ <tr>
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+ <td class="memname">using <a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html">cutlass::epilogue::threadblock::DefaultEpilogueComplexTensorOp</a>&lt; Shape_, WarpMmaTensorOp_, PartitionsK, OutputOp_, ElementsPerAccess &gt;::<a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a89a49a6d25f358cffe669ece2abe2f11">LayoutC</a> = typename WarpMmaTensorOp::LayoutC</td>
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+ </tr>
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+ </table>
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+ </div><div class="memdoc">
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+
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+ </div>
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+ </div>
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+ <a class="anchor" id="a517049715fcabdb536f278604477829e"></a>
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+ <div class="memitem">
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+ <div class="memproto">
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+ <div class="memtemplate">
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+ template&lt;typename Shape_ , typename WarpMmaTensorOp_ , int PartitionsK, typename OutputOp_ , int ElementsPerAccess&gt; </div>
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+ <table class="memname">
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+ <tr>
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+ <td class="memname">using <a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html">cutlass::epilogue::threadblock::DefaultEpilogueComplexTensorOp</a>&lt; Shape_, WarpMmaTensorOp_, PartitionsK, OutputOp_, ElementsPerAccess &gt;::<a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a517049715fcabdb536f278604477829e">OutputOp</a> = OutputOp_</td>
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+ </tr>
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+ </table>
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+ </div><div class="memdoc">
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+
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+ </div>
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+ </div>
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+ <a class="anchor" id="ab421b49d591111d62eac560f8b96c10a"></a>
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+ <div class="memitem">
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+ <div class="memproto">
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+ <div class="memtemplate">
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+ template&lt;typename Shape_ , typename WarpMmaTensorOp_ , int PartitionsK, typename OutputOp_ , int ElementsPerAccess&gt; </div>
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+ <table class="memname">
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+ <tr>
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+ <td class="memname">using <a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html">cutlass::epilogue::threadblock::DefaultEpilogueComplexTensorOp</a>&lt; Shape_, WarpMmaTensorOp_, PartitionsK, OutputOp_, ElementsPerAccess &gt;::<a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#ab421b49d591111d62eac560f8b96c10a">OutputTileIterator</a> = <a class="el" href="classcutlass_1_1epilogue_1_1threadblock_1_1PredicatedTileIterator.html">cutlass::epilogue::threadblock::PredicatedTileIterator</a>&lt; <a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#adb357c79d059162f558cfeab52484fca">OutputTileThreadMap</a>, <a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a1021107776d67cf428dfd799bbaaa02f">ElementOutput</a> &gt;</td>
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+ </tr>
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+ </table>
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+ </div><div class="memdoc">
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+
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+ </div>
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+ </div>
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+ <a class="anchor" id="adb357c79d059162f558cfeab52484fca"></a>
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+ <div class="memitem">
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+ <div class="memproto">
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+ <div class="memtemplate">
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+ template&lt;typename Shape_ , typename WarpMmaTensorOp_ , int PartitionsK, typename OutputOp_ , int ElementsPerAccess&gt; </div>
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+ <table class="memname">
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+ <tr>
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+ <td class="memname">using <a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html">cutlass::epilogue::threadblock::DefaultEpilogueComplexTensorOp</a>&lt; Shape_, WarpMmaTensorOp_, PartitionsK, OutputOp_, ElementsPerAccess &gt;::<a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#adb357c79d059162f558cfeab52484fca">OutputTileThreadMap</a> = typename <a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapTensorOp.html">cutlass::epilogue::threadblock::DefaultThreadMapTensorOp</a>&lt; <a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a3103ac8f979c182f26c3b80ce15643f6">Shape</a>, typename WarpMmaTensorOp::Shape, <a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a6a7770417159c242d8252998aebfa96e">kPartitionsK</a>, <a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a1021107776d67cf428dfd799bbaaa02f">ElementOutput</a>, <a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#afc3c42f94722a38fbf23436fc16320e5">kElementsPerAccess</a> &gt;::Type</td>
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+ </tr>
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+ </table>
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+ </div><div class="memdoc">
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+
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+ </div>
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+ </div>
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+ <a class="anchor" id="a6685913f5820773e1b26ea2eb76866cd"></a>
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+ <div class="memitem">
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+ <div class="memproto">
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+ <div class="memtemplate">
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+ template&lt;typename Shape_ , typename WarpMmaTensorOp_ , int PartitionsK, typename OutputOp_ , int ElementsPerAccess&gt; </div>
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+ <table class="memname">
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+ <tr>
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+ <td class="memname">using <a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html">cutlass::epilogue::threadblock::DefaultEpilogueComplexTensorOp</a>&lt; Shape_, WarpMmaTensorOp_, PartitionsK, OutputOp_, ElementsPerAccess &gt;::<a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a6685913f5820773e1b26ea2eb76866cd">Padding</a> = <a class="el" href="structcutlass_1_1MatrixShape.html">cutlass::MatrixShape</a>&lt;0, 0&gt;</td>
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+ </tr>
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+ </table>
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+ </div><div class="memdoc">
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+
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+ </div>
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+ </div>
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+ <a class="anchor" id="a3103ac8f979c182f26c3b80ce15643f6"></a>
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+ <div class="memitem">
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+ <div class="memproto">
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+ <div class="memtemplate">
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+ template&lt;typename Shape_ , typename WarpMmaTensorOp_ , int PartitionsK, typename OutputOp_ , int ElementsPerAccess&gt; </div>
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+ <table class="memname">
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+ <tr>
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+ <td class="memname">using <a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html">cutlass::epilogue::threadblock::DefaultEpilogueComplexTensorOp</a>&lt; Shape_, WarpMmaTensorOp_, PartitionsK, OutputOp_, ElementsPerAccess &gt;::<a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a3103ac8f979c182f26c3b80ce15643f6">Shape</a> = Shape_</td>
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+ </tr>
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+ </table>
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+ </div><div class="memdoc">
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+
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+ </div>
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+ </div>
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+ <a class="anchor" id="af85ee3278368759b9876c07124b09ffd"></a>
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+ <div class="memitem">
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+ <div class="memproto">
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+ <div class="memtemplate">
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+ template&lt;typename Shape_ , typename WarpMmaTensorOp_ , int PartitionsK, typename OutputOp_ , int ElementsPerAccess&gt; </div>
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+ <table class="memname">
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+ <tr>
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+ <td class="memname">using <a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html">cutlass::epilogue::threadblock::DefaultEpilogueComplexTensorOp</a>&lt; Shape_, WarpMmaTensorOp_, PartitionsK, OutputOp_, ElementsPerAccess &gt;::<a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#af85ee3278368759b9876c07124b09ffd">SharedLoadIterator</a> = <a class="el" href="classcutlass_1_1epilogue_1_1threadblock_1_1SharedLoadIterator.html">cutlass::epilogue::threadblock::SharedLoadIterator</a>&lt; typename OutputTileThreadMap::CompactedThreadMap, <a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a43ad144aa28bab769fa744744eb0321a">ElementAccumulator</a> &gt;</td>
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+ </tr>
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+ </table>
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+ </div><div class="memdoc">
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+
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+ </div>
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+ </div>
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+ <a class="anchor" id="a9323e876327a9bfe0f277b78c787ec01"></a>
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+ <div class="memitem">
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+ <div class="memproto">
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+ <div class="memtemplate">
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+ template&lt;typename Shape_ , typename WarpMmaTensorOp_ , int PartitionsK, typename OutputOp_ , int ElementsPerAccess&gt; </div>
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+ <table class="memname">
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+ <tr>
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+ <td class="memname">using <a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html">cutlass::epilogue::threadblock::DefaultEpilogueComplexTensorOp</a>&lt; Shape_, WarpMmaTensorOp_, PartitionsK, OutputOp_, ElementsPerAccess &gt;::<a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a9323e876327a9bfe0f277b78c787ec01">WarpMmaTensorOp</a> = WarpMmaTensorOp_</td>
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+ </tr>
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+ </table>
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+ </div><div class="memdoc">
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+
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+ </div>
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+ </div>
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+ <a class="anchor" id="ac41f55deccd93d0ca21c75bd1b311658"></a>
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+ <div class="memitem">
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+ <div class="memproto">
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+ <div class="memtemplate">
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+ template&lt;typename Shape_ , typename WarpMmaTensorOp_ , int PartitionsK, typename OutputOp_ , int ElementsPerAccess&gt; </div>
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+ <table class="memname">
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+ <tr>
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+ <td class="memname">using <a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html">cutlass::epilogue::threadblock::DefaultEpilogueComplexTensorOp</a>&lt; Shape_, WarpMmaTensorOp_, PartitionsK, OutputOp_, ElementsPerAccess &gt;::<a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#ac41f55deccd93d0ca21c75bd1b311658">WarpTileIterator</a> = <a class="el" href="classcutlass_1_1epilogue_1_1warp_1_1TileIteratorTensorOp.html">cutlass::epilogue::warp::TileIteratorTensorOp</a>&lt; typename WarpMmaTensorOp::Shape, typename WarpMmaTensorOp::Policy::Operator::Shape, <a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a43ad144aa28bab769fa744744eb0321a">ElementAccumulator</a>, <a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html#a89a49a6d25f358cffe669ece2abe2f11">LayoutC</a> &gt;</td>
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+ </tr>
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+ </table>
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+ </div><div class="memdoc">
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+
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+ </div>
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+ </div>
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+ <h2 class="groupheader">Member Data Documentation</h2>
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+ <a class="anchor" id="afc3c42f94722a38fbf23436fc16320e5"></a>
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+ <div class="memitem">
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+ <div class="memproto">
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+ <div class="memtemplate">
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+ template&lt;typename Shape_ , typename WarpMmaTensorOp_ , int PartitionsK, typename OutputOp_ , int ElementsPerAccess&gt; </div>
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+ <table class="mlabels">
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+ <tr>
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+ <td class="mlabels-left">
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+ <table class="memname">
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+ <tr>
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+ <td class="memname">int const <a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html">cutlass::epilogue::threadblock::DefaultEpilogueComplexTensorOp</a>&lt; Shape_, WarpMmaTensorOp_, PartitionsK, OutputOp_, ElementsPerAccess &gt;::kElementsPerAccess = ElementsPerAccess</td>
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+ </tr>
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+ </table>
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+ </td>
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+ <td class="mlabels-right">
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+ <span class="mlabels"><span class="mlabel">static</span></span> </td>
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+ </tr>
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+ </table>
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+ </div><div class="memdoc">
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+
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+ </div>
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+ </div>
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+ <a class="anchor" id="a6a7770417159c242d8252998aebfa96e"></a>
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+ <div class="memitem">
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+ <div class="memproto">
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+ <div class="memtemplate">
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+ template&lt;typename Shape_ , typename WarpMmaTensorOp_ , int PartitionsK, typename OutputOp_ , int ElementsPerAccess&gt; </div>
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+ <table class="mlabels">
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+ <tr>
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+ <td class="mlabels-left">
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+ <table class="memname">
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+ <tr>
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+ <td class="memname">int const <a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultEpilogueComplexTensorOp.html">cutlass::epilogue::threadblock::DefaultEpilogueComplexTensorOp</a>&lt; Shape_, WarpMmaTensorOp_, PartitionsK, OutputOp_, ElementsPerAccess &gt;::kPartitionsK = PartitionsK</td>
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+ </tr>
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+ </table>
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+ </td>
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+ <td class="mlabels-right">
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+ <span class="mlabels"><span class="mlabel">static</span></span> </td>
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+ </tr>
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+ </table>
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+ </div><div class="memdoc">
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+
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+ </div>
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+ </div>
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+ <hr/>The documentation for this struct was generated from the following file:<ul>
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+ <li><a class="el" href="default__epilogue__complex__tensor__op_8h_source.html">default_epilogue_complex_tensor_op.h</a></li>
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+ </ul>
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+ </div><!-- contents -->
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+ Generated by &#160;<a href="http://www.doxygen.org/index.html">
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+ <img class="footer" src="doxygen.png" alt="doxygen"/>
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+ </a> 1.8.11
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+ </small></address>
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+ </body>
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+ </html>
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+ <div id="projectbrief">CUDA Templates for Linear Algebra Subroutines and Solvers</div>
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+ <li class="navelem"><a class="el" href="namespacecutlass.html">cutlass</a></li><li class="navelem"><a class="el" href="namespacecutlass_1_1epilogue.html">epilogue</a></li><li class="navelem"><a class="el" href="namespacecutlass_1_1epilogue_1_1threadblock.html">threadblock</a></li><li class="navelem"><a class="el" href="classcutlass_1_1epilogue_1_1threadblock_1_1InterleavedPredicatedTileIterator.html">InterleavedPredicatedTileIterator</a></li><li class="navelem"><a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1InterleavedPredicatedTileIterator_1_1Params.html">Params</a></li> </ul>
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+ <div class="header">
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+ <div class="summary">
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+ <a href="#pub-methods">Public Member Functions</a> &#124;
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+ <a href="#pub-attribs">Public Attributes</a> &#124;
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+ <a href="structcutlass_1_1epilogue_1_1threadblock_1_1InterleavedPredicatedTileIterator_1_1Params-members.html">List of all members</a> </div>
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+ <div class="headertitle">
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+ <div class="title">cutlass::epilogue::threadblock::InterleavedPredicatedTileIterator&lt; ThreadMap_, Element_, InterleavedK &gt;::Params Struct Reference</div> </div>
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+ </div><!--header-->
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+ <div class="contents">
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+
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+ <p><code>#include &lt;<a class="el" href="epilogue_2threadblock_2predicated__tile__iterator_8h_source.html">predicated_tile_iterator.h</a>&gt;</code></p>
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+ <tr class="memitem:a6f0ad92d44376e1bf61e7fb6932a3dfd"><td class="memItemLeft" align="right" valign="top"><a class="el" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a> <a class="el" href="namespacecutlass.html#ac5a88c5840a28a9e0206b9cc7812a18d">Status</a>&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1InterleavedPredicatedTileIterator_1_1Params.html#a6f0ad92d44376e1bf61e7fb6932a3dfd">initialize</a> (<a class="el" href="classcutlass_1_1epilogue_1_1threadblock_1_1InterleavedPredicatedTileIterator.html#acc8e9e6194f2c47232f456b761349bf2">Index</a> stride_)</td></tr>
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+ <tr class="separator:acfdbad18358373f86ef8f2f3eae62a1f"><td class="memSeparator" colspan="2">&#160;</td></tr>
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+ </table><table class="memberdecls">
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+ <tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-attribs"></a>
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+ Public Attributes</h2></td></tr>
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+ <tr class="memitem:ae3275575a9c4a54e8444b31bd3874996"><td class="memItemLeft" align="right" valign="top"><a class="el" href="classcutlass_1_1epilogue_1_1threadblock_1_1InterleavedPredicatedTileIterator.html#acc8e9e6194f2c47232f456b761349bf2">Index</a>&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1InterleavedPredicatedTileIterator_1_1Params.html#ae3275575a9c4a54e8444b31bd3874996">stride</a></td></tr>
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+ <tr class="memdesc:ae3275575a9c4a54e8444b31bd3874996"><td class="mdescLeft">&#160;</td><td class="mdescRight">stride in bytes between columns <a href="#ae3275575a9c4a54e8444b31bd3874996">More...</a><br /></td></tr>
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+ <tr class="separator:ae3275575a9c4a54e8444b31bd3874996"><td class="memSeparator" colspan="2">&#160;</td></tr>
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+ <tr class="memdesc:a31c6472b5e890a37657d573646114156"><td class="mdescLeft">&#160;</td><td class="mdescRight">amount to add to move to the next 'row' position <a href="#a31c6472b5e890a37657d573646114156">More...</a><br /></td></tr>
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+ <tr class="separator:a31c6472b5e890a37657d573646114156"><td class="memSeparator" colspan="2">&#160;</td></tr>
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+ <tr class="memdesc:a5593ba3ee47ba8bb6dc2b0b001b38824"><td class="mdescLeft">&#160;</td><td class="mdescRight">amount to add to move to the next 'column' position <a href="#a5593ba3ee47ba8bb6dc2b0b001b38824">More...</a><br /></td></tr>
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+ <tr class="separator:a5593ba3ee47ba8bb6dc2b0b001b38824"><td class="memSeparator" colspan="2">&#160;</td></tr>
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+ </table>
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+ <h2 class="groupheader">Constructor &amp; Destructor Documentation</h2>
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+ <div class="memitem">
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+ <div class="memproto">
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+ template&lt;typename ThreadMap_ , typename Element_ , int InterleavedK&gt; </div>
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+ <td>(</td>
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+ template&lt;typename ThreadMap_ , typename Element_ , int InterleavedK&gt; </div>
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+ <td class="mlabels-left">
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+ <td class="memname"><a class="el" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a> <a class="el" href="classcutlass_1_1epilogue_1_1threadblock_1_1InterleavedPredicatedTileIterator.html">cutlass::epilogue::threadblock::InterleavedPredicatedTileIterator</a>&lt; ThreadMap_, Element_, InterleavedK &gt;::Params::Params </td>
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+ <td>(</td>
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+ <td class="paramtype"><a class="el" href="classcutlass_1_1epilogue_1_1threadblock_1_1InterleavedPredicatedTileIterator.html#a160a6628f34c37e13d13a9f87b0090a3">Layout</a> const &amp;&#160;</td>
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+ <td class="paramname"><em>layout</em></td><td>)</td>
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+ <div class="memitem">
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+ template&lt;typename ThreadMap_ , typename Element_ , int InterleavedK&gt; </div>
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+ <td class="mlabels-left">
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+ <td>(</td>
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+ <div class="memitem">
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+ <div class="memproto">
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+ <div class="memtemplate">
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+ template&lt;typename ThreadMap_ , typename Element_ , int InterleavedK&gt; </div>
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+ <table class="memname">
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+ <td class="memname"><a class="el" href="classcutlass_1_1epilogue_1_1threadblock_1_1InterleavedPredicatedTileIterator.html#acc8e9e6194f2c47232f456b761349bf2">Index</a> <a class="el" href="classcutlass_1_1epilogue_1_1threadblock_1_1InterleavedPredicatedTileIterator.html">cutlass::epilogue::threadblock::InterleavedPredicatedTileIterator</a>&lt; ThreadMap_, Element_, InterleavedK &gt;::Params::advance_column</td>
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+ </div><div class="memdoc">
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+
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+ </div>
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+ <div class="memitem">
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+ <div class="memproto">
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+ <div class="memtemplate">
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+ template&lt;typename ThreadMap_ , typename Element_ , int InterleavedK&gt; </div>
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+ <table class="memname">
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+ <tr>
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+ <td class="memname"><a class="el" href="classcutlass_1_1epilogue_1_1threadblock_1_1InterleavedPredicatedTileIterator.html#acc8e9e6194f2c47232f456b761349bf2">Index</a> <a class="el" href="classcutlass_1_1epilogue_1_1threadblock_1_1InterleavedPredicatedTileIterator.html">cutlass::epilogue::threadblock::InterleavedPredicatedTileIterator</a>&lt; ThreadMap_, Element_, InterleavedK &gt;::Params::advance_row</td>
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+ </tr>
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+
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+ <a class="anchor" id="ae3275575a9c4a54e8444b31bd3874996"></a>
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+ <div class="memitem">
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+ <div class="memproto">
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+ <div class="memtemplate">
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+ template&lt;typename ThreadMap_ , typename Element_ , int InterleavedK&gt; </div>
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+ <table class="memname">
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+ <tr>
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+ <td class="memname"><a class="el" href="classcutlass_1_1epilogue_1_1threadblock_1_1InterleavedPredicatedTileIterator.html#acc8e9e6194f2c47232f456b761349bf2">Index</a> <a class="el" href="classcutlass_1_1epilogue_1_1threadblock_1_1InterleavedPredicatedTileIterator.html">cutlass::epilogue::threadblock::InterleavedPredicatedTileIterator</a>&lt; ThreadMap_, Element_, InterleavedK &gt;::Params::stride</td>
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+ <hr/>The documentation for this struct was generated from the following file:<ul>
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+ <li class="navelem"><a class="el" href="namespacecutlass.html">cutlass</a></li><li class="navelem"><a class="el" href="namespacecutlass_1_1epilogue.html">epilogue</a></li><li class="navelem"><a class="el" href="namespacecutlass_1_1epilogue_1_1threadblock.html">threadblock</a></li><li class="navelem"><a class="el" href="namespacecutlass_1_1epilogue_1_1threadblock_1_1detail.html">detail</a></li><li class="navelem"><a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1detail_1_1RowArrangement_3_01Shape_00_01WarpsRemaini91159e6f7e123d881e3ec45101fa4f81.html">RowArrangement&lt; Shape, WarpsRemaining, ElementsPerAccess, ElementSize, false &gt;</a></li> </ul>
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+ <table class="directory">
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+ <tr class="even"><td class="entry"><a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1detail_1_1RowArrangement_3_01Shape_00_01WarpsRemaini91159e6f7e123d881e3ec45101fa4f81.html#adcac777a84015bf6ba63cbd86907ac74">kAccessRows</a></td><td class="entry"><a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1detail_1_1RowArrangement_3_01Shape_00_01WarpsRemaini91159e6f7e123d881e3ec45101fa4f81.html">cutlass::epilogue::threadblock::detail::RowArrangement&lt; Shape, WarpsRemaining, ElementsPerAccess, ElementSize, false &gt;</a></td><td class="entry"><span class="mlabel">static</span></td></tr>
107
+ <tr><td class="entry"><a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1detail_1_1RowArrangement_3_01Shape_00_01WarpsRemaini91159e6f7e123d881e3ec45101fa4f81.html#a015f6bd69b9a05b2fbac3544789d7936">kAccessWidth</a></td><td class="entry"><a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1detail_1_1RowArrangement_3_01Shape_00_01WarpsRemaini91159e6f7e123d881e3ec45101fa4f81.html">cutlass::epilogue::threadblock::detail::RowArrangement&lt; Shape, WarpsRemaining, ElementsPerAccess, ElementSize, false &gt;</a></td><td class="entry"><span class="mlabel">static</span></td></tr>
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+ <tr class="even"><td class="entry"><a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1detail_1_1RowArrangement_3_01Shape_00_01WarpsRemaini91159e6f7e123d881e3ec45101fa4f81.html#a531cc8d50e9d4cca5957795b0a6959a8">kDeltaColumn</a></td><td class="entry"><a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1detail_1_1RowArrangement_3_01Shape_00_01WarpsRemaini91159e6f7e123d881e3ec45101fa4f81.html">cutlass::epilogue::threadblock::detail::RowArrangement&lt; Shape, WarpsRemaining, ElementsPerAccess, ElementSize, false &gt;</a></td><td class="entry"><span class="mlabel">static</span></td></tr>
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+ <tr class="even"><td class="entry"><a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1detail_1_1RowArrangement_3_01Shape_00_01WarpsRemaini91159e6f7e123d881e3ec45101fa4f81.html#aeebbd6691025dfc55b8daa8dbcec17b7">kElementSize</a></td><td class="entry"><a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1detail_1_1RowArrangement_3_01Shape_00_01WarpsRemaini91159e6f7e123d881e3ec45101fa4f81.html">cutlass::epilogue::threadblock::detail::RowArrangement&lt; Shape, WarpsRemaining, ElementsPerAccess, ElementSize, false &gt;</a></td><td class="entry"><span class="mlabel">static</span></td></tr>
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+ <tr><td class="entry"><a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1detail_1_1RowArrangement_3_01Shape_00_01WarpsRemaini91159e6f7e123d881e3ec45101fa4f81.html#a06fa764531f37833164d36513884a255">kElementsPerAccess</a></td><td class="entry"><a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1detail_1_1RowArrangement_3_01Shape_00_01WarpsRemaini91159e6f7e123d881e3ec45101fa4f81.html">cutlass::epilogue::threadblock::detail::RowArrangement&lt; Shape, WarpsRemaining, ElementsPerAccess, ElementSize, false &gt;</a></td><td class="entry"><span class="mlabel">static</span></td></tr>
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+ <tr class="even"><td class="entry"><a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1detail_1_1RowArrangement_3_01Shape_00_01WarpsRemaini91159e6f7e123d881e3ec45101fa4f81.html#aa60e9c20f478f032e2451a252bca21d1">kIterationsColumn</a></td><td class="entry"><a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1detail_1_1RowArrangement_3_01Shape_00_01WarpsRemaini91159e6f7e123d881e3ec45101fa4f81.html">cutlass::epilogue::threadblock::detail::RowArrangement&lt; Shape, WarpsRemaining, ElementsPerAccess, ElementSize, false &gt;</a></td><td class="entry"><span class="mlabel">static</span></td></tr>
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sglang_repo/sgl-kernel/3rdparty/flashinfer/3rdparty/cutlass/docs/structcutlass_1_1gemm_1_1thread_1_1detail_1_1Mma__HFMA2_3_01Shape_00_01layout_1_1ColumnMajor_00_17070298bc4cced0a1b98aee2bb6b455.html ADDED
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+ <li class="navelem"><a class="el" href="namespacecutlass.html">cutlass</a></li><li class="navelem"><a class="el" href="namespacecutlass_1_1gemm.html">gemm</a></li><li class="navelem"><a class="el" href="namespacecutlass_1_1gemm_1_1thread.html">thread</a></li><li class="navelem"><a class="el" href="namespacecutlass_1_1gemm_1_1thread_1_1detail.html">detail</a></li><li class="navelem"><a class="el" href="structcutlass_1_1gemm_1_1thread_1_1detail_1_1Mma__HFMA2_3_01Shape_00_01layout_1_1ColumnMajor_00_17070298bc4cced0a1b98aee2bb6b455.html">Mma_HFMA2&lt; Shape, layout::ColumnMajor, layout::RowMajor, layout::ColumnMajor, true &gt;</a></li> </ul>
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+ <div class="header">
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+ <a href="#pub-types">Public Types</a> &#124;
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+ <a href="#pub-methods">Public Member Functions</a> &#124;
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+ <a href="structcutlass_1_1gemm_1_1thread_1_1detail_1_1Mma__HFMA2_3_01Shape_00_01layout_1_1ColumnMajor_00_f16629e5249aa6882f509571d2434832.html">List of all members</a> </div>
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+ <div class="headertitle">
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+ <div class="title">cutlass::gemm::thread::detail::Mma_HFMA2&lt; Shape, layout::ColumnMajor, layout::RowMajor, layout::ColumnMajor, true &gt; Struct Template Reference</div> </div>
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+ </div><!--header-->
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+ <div class="contents">
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+
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+ <p><code>#include &lt;<a class="el" href="gemm_2thread_2mma__sm60_8h_source.html">mma_sm60.h</a>&gt;</code></p>
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+ <table class="memberdecls">
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+ <tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-types"></a>
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+ Public Types</h2></td></tr>
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+ <tr class="memitem:abd3217abf12bdf7810408cd0af10e684"><td class="memItemLeft" align="right" valign="top">using&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1gemm_1_1thread_1_1detail_1_1Mma__HFMA2_3_01Shape_00_01layout_1_1ColumnMajor_00_17070298bc4cced0a1b98aee2bb6b455.html#abd3217abf12bdf7810408cd0af10e684">FragmentA</a> = Array&lt; <a class="el" href="structcutlass_1_1half__t.html">half_t</a>, Shape::kMK &gt;</td></tr>
113
+ <tr class="memdesc:abd3217abf12bdf7810408cd0af10e684"><td class="mdescLeft">&#160;</td><td class="mdescRight">A operand storage. <a href="#abd3217abf12bdf7810408cd0af10e684">More...</a><br /></td></tr>
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+ <tr class="separator:abd3217abf12bdf7810408cd0af10e684"><td class="memSeparator" colspan="2">&#160;</td></tr>
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116
+ <tr class="memdesc:a99594cf2b14d51d930aeffe5f2a2eedd"><td class="mdescLeft">&#160;</td><td class="mdescRight">B operand storage. <a href="#a99594cf2b14d51d930aeffe5f2a2eedd">More...</a><br /></td></tr>
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+ <tr class="separator:a99594cf2b14d51d930aeffe5f2a2eedd"><td class="memSeparator" colspan="2">&#160;</td></tr>
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+ <tr class="memitem:a58f282b08f9bdf33863e87838edcff79"><td class="memItemLeft" align="right" valign="top">using&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1gemm_1_1thread_1_1detail_1_1Mma__HFMA2_3_01Shape_00_01layout_1_1ColumnMajor_00_17070298bc4cced0a1b98aee2bb6b455.html#a58f282b08f9bdf33863e87838edcff79">FragmentC</a> = Array&lt; <a class="el" href="structcutlass_1_1half__t.html">half_t</a>, Shape::kMN &gt;</td></tr>
119
+ <tr class="memdesc:a58f282b08f9bdf33863e87838edcff79"><td class="mdescLeft">&#160;</td><td class="mdescRight">C operand storage. <a href="#a58f282b08f9bdf33863e87838edcff79">More...</a><br /></td></tr>
120
+ <tr class="separator:a58f282b08f9bdf33863e87838edcff79"><td class="memSeparator" colspan="2">&#160;</td></tr>
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+ </table><table class="memberdecls">
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+ <tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-methods"></a>
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+ Public Member Functions</h2></td></tr>
124
+ <tr class="memitem:a6b501c0685b9b181fa48dba331d5a6ec"><td class="memItemLeft" align="right" valign="top"><a class="el" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a> void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1gemm_1_1thread_1_1detail_1_1Mma__HFMA2_3_01Shape_00_01layout_1_1ColumnMajor_00_17070298bc4cced0a1b98aee2bb6b455.html#a6b501c0685b9b181fa48dba331d5a6ec">operator()</a> (<a class="el" href="structcutlass_1_1gemm_1_1thread_1_1detail_1_1Mma__HFMA2_3_01Shape_00_01layout_1_1ColumnMajor_00_17070298bc4cced0a1b98aee2bb6b455.html#a58f282b08f9bdf33863e87838edcff79">FragmentC</a> &amp;D, <a class="el" href="structcutlass_1_1gemm_1_1thread_1_1detail_1_1Mma__HFMA2_3_01Shape_00_01layout_1_1ColumnMajor_00_17070298bc4cced0a1b98aee2bb6b455.html#abd3217abf12bdf7810408cd0af10e684">FragmentA</a> const &amp;A, <a class="el" href="structcutlass_1_1gemm_1_1thread_1_1detail_1_1Mma__HFMA2_3_01Shape_00_01layout_1_1ColumnMajor_00_17070298bc4cced0a1b98aee2bb6b455.html#a99594cf2b14d51d930aeffe5f2a2eedd">FragmentB</a> const &amp;B, <a class="el" href="structcutlass_1_1gemm_1_1thread_1_1detail_1_1Mma__HFMA2_3_01Shape_00_01layout_1_1ColumnMajor_00_17070298bc4cced0a1b98aee2bb6b455.html#a58f282b08f9bdf33863e87838edcff79">FragmentC</a> const &amp;C)</td></tr>
125
+ <tr class="memdesc:a6b501c0685b9b181fa48dba331d5a6ec"><td class="mdescLeft">&#160;</td><td class="mdescRight">Computes a matrix product D = A * B + C. <a href="#a6b501c0685b9b181fa48dba331d5a6ec">More...</a><br /></td></tr>
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+ <tr class="separator:a6b501c0685b9b181fa48dba331d5a6ec"><td class="memSeparator" colspan="2">&#160;</td></tr>
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+ </table>
128
+ <h2 class="groupheader">Member Typedef Documentation</h2>
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+ <a class="anchor" id="abd3217abf12bdf7810408cd0af10e684"></a>
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+ <div class="memitem">
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+ <div class="memproto">
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+ <div class="memtemplate">
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+ template&lt;typename Shape &gt; </div>
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+ <table class="memname">
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+ <tr>
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+ <td class="memname">using <a class="el" href="structcutlass_1_1gemm_1_1thread_1_1detail_1_1Mma__HFMA2.html">cutlass::gemm::thread::detail::Mma_HFMA2</a>&lt; Shape, <a class="el" href="classcutlass_1_1layout_1_1ColumnMajor.html">layout::ColumnMajor</a>, <a class="el" href="classcutlass_1_1layout_1_1RowMajor.html">layout::RowMajor</a>, <a class="el" href="classcutlass_1_1layout_1_1ColumnMajor.html">layout::ColumnMajor</a>, true &gt;::<a class="el" href="structcutlass_1_1gemm_1_1thread_1_1detail_1_1Mma__HFMA2_3_01Shape_00_01layout_1_1ColumnMajor_00_17070298bc4cced0a1b98aee2bb6b455.html#abd3217abf12bdf7810408cd0af10e684">FragmentA</a> = Array&lt;<a class="el" href="structcutlass_1_1half__t.html">half_t</a>, Shape::kMK&gt;</td>
137
+ </tr>
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+ </table>
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+ </div><div class="memdoc">
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+
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+ </div>
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+ </div>
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+ <a class="anchor" id="a99594cf2b14d51d930aeffe5f2a2eedd"></a>
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+ <div class="memitem">
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+ <div class="memproto">
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+ <div class="memtemplate">
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+ template&lt;typename Shape &gt; </div>
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+ <table class="memname">
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+ <tr>
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+ <td class="memname">using <a class="el" href="structcutlass_1_1gemm_1_1thread_1_1detail_1_1Mma__HFMA2.html">cutlass::gemm::thread::detail::Mma_HFMA2</a>&lt; Shape, <a class="el" href="classcutlass_1_1layout_1_1ColumnMajor.html">layout::ColumnMajor</a>, <a class="el" href="classcutlass_1_1layout_1_1RowMajor.html">layout::RowMajor</a>, <a class="el" href="classcutlass_1_1layout_1_1ColumnMajor.html">layout::ColumnMajor</a>, true &gt;::<a class="el" href="structcutlass_1_1gemm_1_1thread_1_1detail_1_1Mma__HFMA2_3_01Shape_00_01layout_1_1ColumnMajor_00_17070298bc4cced0a1b98aee2bb6b455.html#a99594cf2b14d51d930aeffe5f2a2eedd">FragmentB</a> = Array&lt;<a class="el" href="structcutlass_1_1half__t.html">half_t</a>, Shape::kKN&gt;</td>
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+ </tr>
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+ </table>
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+ </div><div class="memdoc">
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+
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+ </div>
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+ </div>
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+ <a class="anchor" id="a58f282b08f9bdf33863e87838edcff79"></a>
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+ <div class="memitem">
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+ <div class="memproto">
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+ <div class="memtemplate">
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+ template&lt;typename Shape &gt; </div>
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+ <table class="memname">
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+ <tr>
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+ <td class="memname">using <a class="el" href="structcutlass_1_1gemm_1_1thread_1_1detail_1_1Mma__HFMA2.html">cutlass::gemm::thread::detail::Mma_HFMA2</a>&lt; Shape, <a class="el" href="classcutlass_1_1layout_1_1ColumnMajor.html">layout::ColumnMajor</a>, <a class="el" href="classcutlass_1_1layout_1_1RowMajor.html">layout::RowMajor</a>, <a class="el" href="classcutlass_1_1layout_1_1ColumnMajor.html">layout::ColumnMajor</a>, true &gt;::<a class="el" href="structcutlass_1_1gemm_1_1thread_1_1detail_1_1Mma__HFMA2_3_01Shape_00_01layout_1_1ColumnMajor_00_17070298bc4cced0a1b98aee2bb6b455.html#a58f282b08f9bdf33863e87838edcff79">FragmentC</a> = Array&lt;<a class="el" href="structcutlass_1_1half__t.html">half_t</a>, Shape::kMN&gt;</td>
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+ </tr>
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+ </table>
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+ </div><div class="memdoc">
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+
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+ </div>
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+ </div>
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+ <h2 class="groupheader">Member Function Documentation</h2>
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+ <a class="anchor" id="a6b501c0685b9b181fa48dba331d5a6ec"></a>
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+ <div class="memitem">
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+ <div class="memproto">
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+ <div class="memtemplate">
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+ template&lt;typename Shape &gt; </div>
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+ <table class="mlabels">
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+ <tr>
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+ <td class="mlabels-left">
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+ <table class="memname">
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+ <tr>
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+ <td class="memname"><a class="el" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a> void <a class="el" href="structcutlass_1_1gemm_1_1thread_1_1detail_1_1Mma__HFMA2.html">cutlass::gemm::thread::detail::Mma_HFMA2</a>&lt; Shape, <a class="el" href="classcutlass_1_1layout_1_1ColumnMajor.html">layout::ColumnMajor</a>, <a class="el" href="classcutlass_1_1layout_1_1RowMajor.html">layout::RowMajor</a>, <a class="el" href="classcutlass_1_1layout_1_1ColumnMajor.html">layout::ColumnMajor</a>, true &gt;::operator() </td>
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+ <td>(</td>
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+ <td class="paramtype"><a class="el" href="structcutlass_1_1gemm_1_1thread_1_1detail_1_1Mma__HFMA2_3_01Shape_00_01layout_1_1ColumnMajor_00_17070298bc4cced0a1b98aee2bb6b455.html#a58f282b08f9bdf33863e87838edcff79">FragmentC</a> &amp;&#160;</td>
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+ <td class="paramname"><em>D</em>, </td>
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+ </tr>
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+ <tr>
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+ <td class="paramkey"></td>
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+ <td></td>
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+ <td class="paramtype"><a class="el" href="structcutlass_1_1gemm_1_1thread_1_1detail_1_1Mma__HFMA2_3_01Shape_00_01layout_1_1ColumnMajor_00_17070298bc4cced0a1b98aee2bb6b455.html#abd3217abf12bdf7810408cd0af10e684">FragmentA</a> const &amp;&#160;</td>
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+ <td class="paramname"><em>A</em>, </td>
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+ </tr>
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+ <tr>
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+ <td class="paramkey"></td>
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+ <td></td>
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+ <td class="paramtype"><a class="el" href="structcutlass_1_1gemm_1_1thread_1_1detail_1_1Mma__HFMA2_3_01Shape_00_01layout_1_1ColumnMajor_00_17070298bc4cced0a1b98aee2bb6b455.html#a99594cf2b14d51d930aeffe5f2a2eedd">FragmentB</a> const &amp;&#160;</td>
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+ <td class="paramname"><em>B</em>, </td>
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+ </tr>
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+ <tr>
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+ <td class="paramkey"></td>
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+ <td></td>
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+ <td class="paramtype"><a class="el" href="structcutlass_1_1gemm_1_1thread_1_1detail_1_1Mma__HFMA2_3_01Shape_00_01layout_1_1ColumnMajor_00_17070298bc4cced0a1b98aee2bb6b455.html#a58f282b08f9bdf33863e87838edcff79">FragmentC</a> const &amp;&#160;</td>
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+ <td class="paramname"><em>C</em>&#160;</td>
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+ </tr>
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+ <tr>
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+ <td></td>
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+ <td>)</td>
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+ <td></td><td></td>
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+ </tr>
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+ </table>
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+ </td>
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+ <td class="mlabels-right">
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+ <span class="mlabels"><span class="mlabel">inline</span></span> </td>
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+ </table>
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+ </div><div class="memdoc">
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+ <p>Initialize output with input </p>
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+
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+ </div>
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+ </div>
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+ <hr/>The documentation for this struct was generated from the following file:<ul>
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+ <li><a class="el" href="gemm_2thread_2mma__sm60_8h_source.html">gemm/thread/mma_sm60.h</a></li>
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+ <li><a href="inherits.html"><span>Class&#160;Hierarchy</span></a></li>
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+ <li><a href="functions.html"><span>Class&#160;Members</span></a></li>
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+ <div id="nav-path" class="navpath">
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+ <ul>
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+ <li class="navelem"><a class="el" href="namespacecutlass.html">cutlass</a></li><li class="navelem"><a class="el" href="namespacecutlass_1_1gemm.html">gemm</a></li><li class="navelem"><a class="el" href="namespacecutlass_1_1gemm_1_1thread.html">thread</a></li><li class="navelem"><a class="el" href="namespacecutlass_1_1gemm_1_1thread_1_1detail.html">detail</a></li><li class="navelem"><a class="el" href="structcutlass_1_1gemm_1_1thread_1_1detail_1_1Mma__HFMA2_3_01Shape_00_01layout_1_1RowMajor_00_01l086c058a15d6c79558e4f3d9ff1dc148.html">Mma_HFMA2&lt; Shape, layout::RowMajor, layout::RowMajor, layout::RowMajor, true &gt;</a></li> </ul>
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+ </div>
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+ </div><!-- top -->
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+ <div class="header">
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+ <div class="summary">
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+ <a href="#pub-types">Public Types</a> &#124;
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+ <a href="#pub-methods">Public Member Functions</a> &#124;
102
+ <a href="structcutlass_1_1gemm_1_1thread_1_1detail_1_1Mma__HFMA2_3_01Shape_00_01layout_1_1RowMajor_00_01l2d7c9369ee79d34a9ecd602986cfab0c.html">List of all members</a> </div>
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+ <div class="headertitle">
104
+ <div class="title">cutlass::gemm::thread::detail::Mma_HFMA2&lt; Shape, layout::RowMajor, layout::RowMajor, layout::RowMajor, true &gt; Struct Template Reference</div> </div>
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+ </div><!--header-->
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+ <div class="contents">
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+
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+ <p><code>#include &lt;<a class="el" href="gemm_2thread_2mma__sm60_8h_source.html">mma_sm60.h</a>&gt;</code></p>
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+ <table class="memberdecls">
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+ <tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-types"></a>
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+ Public Types</h2></td></tr>
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+ <tr class="memitem:abb2a511d7b8b60cac068df2a9caa52c3"><td class="memItemLeft" align="right" valign="top">using&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1gemm_1_1thread_1_1detail_1_1Mma__HFMA2_3_01Shape_00_01layout_1_1RowMajor_00_01l086c058a15d6c79558e4f3d9ff1dc148.html#abb2a511d7b8b60cac068df2a9caa52c3">FragmentA</a> = Array&lt; <a class="el" href="structcutlass_1_1half__t.html">half_t</a>, Shape::kMK &gt;</td></tr>
113
+ <tr class="memdesc:abb2a511d7b8b60cac068df2a9caa52c3"><td class="mdescLeft">&#160;</td><td class="mdescRight">A operand storage. <a href="#abb2a511d7b8b60cac068df2a9caa52c3">More...</a><br /></td></tr>
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+ <tr class="separator:abb2a511d7b8b60cac068df2a9caa52c3"><td class="memSeparator" colspan="2">&#160;</td></tr>
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116
+ <tr class="memdesc:adbb7b7b310e01a955d0567039b09d55e"><td class="mdescLeft">&#160;</td><td class="mdescRight">B operand storage. <a href="#adbb7b7b310e01a955d0567039b09d55e">More...</a><br /></td></tr>
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+ <tr class="separator:adbb7b7b310e01a955d0567039b09d55e"><td class="memSeparator" colspan="2">&#160;</td></tr>
118
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119
+ <tr class="memdesc:a8c02fc1a052ea30219a6a31c2dfb92d5"><td class="mdescLeft">&#160;</td><td class="mdescRight">C operand storage. <a href="#a8c02fc1a052ea30219a6a31c2dfb92d5">More...</a><br /></td></tr>
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+ <tr class="separator:a8c02fc1a052ea30219a6a31c2dfb92d5"><td class="memSeparator" colspan="2">&#160;</td></tr>
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+ </table><table class="memberdecls">
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+ <tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-methods"></a>
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+ Public Member Functions</h2></td></tr>
124
+ <tr class="memitem:a882d7a806108fbec527cce945c976e9f"><td class="memItemLeft" align="right" valign="top"><a class="el" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a> void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1gemm_1_1thread_1_1detail_1_1Mma__HFMA2_3_01Shape_00_01layout_1_1RowMajor_00_01l086c058a15d6c79558e4f3d9ff1dc148.html#a882d7a806108fbec527cce945c976e9f">operator()</a> (<a class="el" href="structcutlass_1_1gemm_1_1thread_1_1detail_1_1Mma__HFMA2_3_01Shape_00_01layout_1_1RowMajor_00_01l086c058a15d6c79558e4f3d9ff1dc148.html#a8c02fc1a052ea30219a6a31c2dfb92d5">FragmentC</a> &amp;D, <a class="el" href="structcutlass_1_1gemm_1_1thread_1_1detail_1_1Mma__HFMA2_3_01Shape_00_01layout_1_1RowMajor_00_01l086c058a15d6c79558e4f3d9ff1dc148.html#abb2a511d7b8b60cac068df2a9caa52c3">FragmentA</a> const &amp;A, <a class="el" href="structcutlass_1_1gemm_1_1thread_1_1detail_1_1Mma__HFMA2_3_01Shape_00_01layout_1_1RowMajor_00_01l086c058a15d6c79558e4f3d9ff1dc148.html#adbb7b7b310e01a955d0567039b09d55e">FragmentB</a> const &amp;B, <a class="el" href="structcutlass_1_1gemm_1_1thread_1_1detail_1_1Mma__HFMA2_3_01Shape_00_01layout_1_1RowMajor_00_01l086c058a15d6c79558e4f3d9ff1dc148.html#a8c02fc1a052ea30219a6a31c2dfb92d5">FragmentC</a> const &amp;C)</td></tr>
125
+ <tr class="memdesc:a882d7a806108fbec527cce945c976e9f"><td class="mdescLeft">&#160;</td><td class="mdescRight">Computes a matrix product D = A * B + C. <a href="#a882d7a806108fbec527cce945c976e9f">More...</a><br /></td></tr>
126
+ <tr class="separator:a882d7a806108fbec527cce945c976e9f"><td class="memSeparator" colspan="2">&#160;</td></tr>
127
+ </table>
128
+ <h2 class="groupheader">Member Typedef Documentation</h2>
129
+ <a class="anchor" id="abb2a511d7b8b60cac068df2a9caa52c3"></a>
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+ <div class="memitem">
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+ <div class="memproto">
132
+ <div class="memtemplate">
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+ template&lt;typename Shape &gt; </div>
134
+ <table class="memname">
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+ <tr>
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+ <td class="memname">using <a class="el" href="structcutlass_1_1gemm_1_1thread_1_1detail_1_1Mma__HFMA2.html">cutlass::gemm::thread::detail::Mma_HFMA2</a>&lt; Shape, <a class="el" href="classcutlass_1_1layout_1_1RowMajor.html">layout::RowMajor</a>, <a class="el" href="classcutlass_1_1layout_1_1RowMajor.html">layout::RowMajor</a>, <a class="el" href="classcutlass_1_1layout_1_1RowMajor.html">layout::RowMajor</a>, true &gt;::<a class="el" href="structcutlass_1_1gemm_1_1thread_1_1detail_1_1Mma__HFMA2_3_01Shape_00_01layout_1_1RowMajor_00_01l086c058a15d6c79558e4f3d9ff1dc148.html#abb2a511d7b8b60cac068df2a9caa52c3">FragmentA</a> = Array&lt;<a class="el" href="structcutlass_1_1half__t.html">half_t</a>, Shape::kMK&gt;</td>
137
+ </tr>
138
+ </table>
139
+ </div><div class="memdoc">
140
+
141
+ </div>
142
+ </div>
143
+ <a class="anchor" id="adbb7b7b310e01a955d0567039b09d55e"></a>
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+ <div class="memitem">
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+ <div class="memproto">
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+ <div class="memtemplate">
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+ template&lt;typename Shape &gt; </div>
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+ <table class="memname">
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+ <tr>
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+ <td class="memname">using <a class="el" href="structcutlass_1_1gemm_1_1thread_1_1detail_1_1Mma__HFMA2.html">cutlass::gemm::thread::detail::Mma_HFMA2</a>&lt; Shape, <a class="el" href="classcutlass_1_1layout_1_1RowMajor.html">layout::RowMajor</a>, <a class="el" href="classcutlass_1_1layout_1_1RowMajor.html">layout::RowMajor</a>, <a class="el" href="classcutlass_1_1layout_1_1RowMajor.html">layout::RowMajor</a>, true &gt;::<a class="el" href="structcutlass_1_1gemm_1_1thread_1_1detail_1_1Mma__HFMA2_3_01Shape_00_01layout_1_1RowMajor_00_01l086c058a15d6c79558e4f3d9ff1dc148.html#adbb7b7b310e01a955d0567039b09d55e">FragmentB</a> = Array&lt;<a class="el" href="structcutlass_1_1half__t.html">half_t</a>, Shape::kKN&gt;</td>
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+ </tr>
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+ </table>
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+ </div><div class="memdoc">
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+
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+ </div>
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+ </div>
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+ <a class="anchor" id="a8c02fc1a052ea30219a6a31c2dfb92d5"></a>
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+ <div class="memitem">
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+ <div class="memproto">
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+ <div class="memtemplate">
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+ template&lt;typename Shape &gt; </div>
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+ <table class="memname">
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+ <tr>
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+ <td class="memname">using <a class="el" href="structcutlass_1_1gemm_1_1thread_1_1detail_1_1Mma__HFMA2.html">cutlass::gemm::thread::detail::Mma_HFMA2</a>&lt; Shape, <a class="el" href="classcutlass_1_1layout_1_1RowMajor.html">layout::RowMajor</a>, <a class="el" href="classcutlass_1_1layout_1_1RowMajor.html">layout::RowMajor</a>, <a class="el" href="classcutlass_1_1layout_1_1RowMajor.html">layout::RowMajor</a>, true &gt;::<a class="el" href="structcutlass_1_1gemm_1_1thread_1_1detail_1_1Mma__HFMA2_3_01Shape_00_01layout_1_1RowMajor_00_01l086c058a15d6c79558e4f3d9ff1dc148.html#a8c02fc1a052ea30219a6a31c2dfb92d5">FragmentC</a> = Array&lt;<a class="el" href="structcutlass_1_1half__t.html">half_t</a>, Shape::kMN&gt;</td>
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+ </tr>
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+ </table>
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+ </div><div class="memdoc">
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+
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+ </div>
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+ </div>
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+ <h2 class="groupheader">Member Function Documentation</h2>
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+ <a class="anchor" id="a882d7a806108fbec527cce945c976e9f"></a>
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+ <div class="memitem">
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+ <div class="memproto">
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+ <div class="memtemplate">
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+ template&lt;typename Shape &gt; </div>
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+ <table class="mlabels">
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+ <tr>
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+ <td class="mlabels-left">
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+ <table class="memname">
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+ <tr>
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+ <td class="memname"><a class="el" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a> void <a class="el" href="structcutlass_1_1gemm_1_1thread_1_1detail_1_1Mma__HFMA2.html">cutlass::gemm::thread::detail::Mma_HFMA2</a>&lt; Shape, <a class="el" href="classcutlass_1_1layout_1_1RowMajor.html">layout::RowMajor</a>, <a class="el" href="classcutlass_1_1layout_1_1RowMajor.html">layout::RowMajor</a>, <a class="el" href="classcutlass_1_1layout_1_1RowMajor.html">layout::RowMajor</a>, true &gt;::operator() </td>
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+ <td>(</td>
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+ <td class="paramtype"><a class="el" href="structcutlass_1_1gemm_1_1thread_1_1detail_1_1Mma__HFMA2_3_01Shape_00_01layout_1_1RowMajor_00_01l086c058a15d6c79558e4f3d9ff1dc148.html#a8c02fc1a052ea30219a6a31c2dfb92d5">FragmentC</a> &amp;&#160;</td>
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+ <td class="paramname"><em>D</em>, </td>
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+ </tr>
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+ <tr>
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+ <td class="paramkey"></td>
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+ <td></td>
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+ <td class="paramtype"><a class="el" href="structcutlass_1_1gemm_1_1thread_1_1detail_1_1Mma__HFMA2_3_01Shape_00_01layout_1_1RowMajor_00_01l086c058a15d6c79558e4f3d9ff1dc148.html#abb2a511d7b8b60cac068df2a9caa52c3">FragmentA</a> const &amp;&#160;</td>
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+ <td class="paramname"><em>A</em>, </td>
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+ </tr>
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+ <tr>
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+ <td class="paramkey"></td>
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+ <td></td>
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+ <td class="paramtype"><a class="el" href="structcutlass_1_1gemm_1_1thread_1_1detail_1_1Mma__HFMA2_3_01Shape_00_01layout_1_1RowMajor_00_01l086c058a15d6c79558e4f3d9ff1dc148.html#adbb7b7b310e01a955d0567039b09d55e">FragmentB</a> const &amp;&#160;</td>
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+ <td class="paramname"><em>B</em>, </td>
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+ </tr>
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+ <tr>
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+ <td class="paramkey"></td>
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+ <td></td>
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+ <td class="paramtype"><a class="el" href="structcutlass_1_1gemm_1_1thread_1_1detail_1_1Mma__HFMA2_3_01Shape_00_01layout_1_1RowMajor_00_01l086c058a15d6c79558e4f3d9ff1dc148.html#a8c02fc1a052ea30219a6a31c2dfb92d5">FragmentC</a> const &amp;&#160;</td>
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+ <td class="paramname"><em>C</em>&#160;</td>
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+ </tr>
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+ <tr>
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+ <td></td>
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+ <td>)</td>
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+ <td></td><td></td>
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+ </tr>
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+ </table>
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+ </td>
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+ <td class="mlabels-right">
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+ <span class="mlabels"><span class="mlabel">inline</span></span> </td>
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+ </tr>
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+ </table>
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+ </div><div class="memdoc">
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+ <p>Initialize output with input</p>
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+ <p>Use 1x2x1 HFMA2 sequence for bulk of computation </p>
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+
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+ </div>
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+ </div>
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+ <hr/>The documentation for this struct was generated from the following file:<ul>
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+ <li><a class="el" href="gemm_2thread_2mma__sm60_8h_source.html">gemm/thread/mma_sm60.h</a></li>
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+ </ul>
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+ Generated by &#160;<a href="http://www.doxygen.org/index.html">
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+ <img class="footer" src="doxygen.png" alt="doxygen"/>
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+ </a> 1.8.11
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+ </html>
sglang_repo/sgl-kernel/3rdparty/flashinfer/3rdparty/cutlass/docs/structcutlass_1_1gemm_1_1threadblock_1_1DefaultMmaCore_3_01Shape___00_01WarpShape___00_01GemmShaa65fcc9419ddceacdfc43dd268adb852.html ADDED
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+ <ul>
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+ <li class="navelem"><a class="el" href="namespacecutlass.html">cutlass</a></li><li class="navelem"><a class="el" href="namespacecutlass_1_1gemm.html">gemm</a></li><li class="navelem"><a class="el" href="namespacecutlass_1_1gemm_1_1threadblock.html">threadblock</a></li><li class="navelem"><a class="el" href="structcutlass_1_1gemm_1_1threadblock_1_1DefaultMmaCore_3_01Shape___00_01WarpShape___00_01GemmSha69bef08ea63dd930f99d9788105873dd.html">DefaultMmaCore&lt; Shape_, WarpShape_, GemmShape&lt; 8, 8, 4 &gt;, ElementA_, layout::ColumnMajor, ElementB_, layout::RowMajor, ElementC_, LayoutC_, arch::OpClassTensorOp, 2, Operator_ &gt;</a></li> </ul>
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+ </div>
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+ </div><!-- top -->
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+ <div class="header">
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+ <div class="headertitle">
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+ <div class="title">cutlass::gemm::threadblock::DefaultMmaCore&lt; Shape_, WarpShape_, GemmShape&lt; 8, 8, 4 &gt;, ElementA_, layout::ColumnMajor, ElementB_, layout::RowMajor, ElementC_, LayoutC_, arch::OpClassTensorOp, 2, Operator_ &gt; Member List</div> </div>
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+ </div><!--header-->
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+ <div class="contents">
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+
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+ <p>This is the complete list of members for <a class="el" href="structcutlass_1_1gemm_1_1threadblock_1_1DefaultMmaCore_3_01Shape___00_01WarpShape___00_01GemmSha69bef08ea63dd930f99d9788105873dd.html">cutlass::gemm::threadblock::DefaultMmaCore&lt; Shape_, WarpShape_, GemmShape&lt; 8, 8, 4 &gt;, ElementA_, layout::ColumnMajor, ElementB_, layout::RowMajor, ElementC_, LayoutC_, arch::OpClassTensorOp, 2, Operator_ &gt;</a>, including all inherited members.</p>
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+ <table class="directory">
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+ <tr class="even"><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1threadblock_1_1DefaultMmaCore_3_01Shape___00_01WarpShape___00_01GemmSha69bef08ea63dd930f99d9788105873dd.html#a4bfead606719cb274810948e59621cb9">ElementA</a> typedef</td><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1threadblock_1_1DefaultMmaCore_3_01Shape___00_01WarpShape___00_01GemmSha69bef08ea63dd930f99d9788105873dd.html">cutlass::gemm::threadblock::DefaultMmaCore&lt; Shape_, WarpShape_, GemmShape&lt; 8, 8, 4 &gt;, ElementA_, layout::ColumnMajor, ElementB_, layout::RowMajor, ElementC_, LayoutC_, arch::OpClassTensorOp, 2, Operator_ &gt;</a></td><td class="entry"></td></tr>
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+ <tr><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1threadblock_1_1DefaultMmaCore_3_01Shape___00_01WarpShape___00_01GemmSha69bef08ea63dd930f99d9788105873dd.html#aac1670f1d1c63dea41b46d5cec0eb535">ElementB</a> typedef</td><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1threadblock_1_1DefaultMmaCore_3_01Shape___00_01WarpShape___00_01GemmSha69bef08ea63dd930f99d9788105873dd.html">cutlass::gemm::threadblock::DefaultMmaCore&lt; Shape_, WarpShape_, GemmShape&lt; 8, 8, 4 &gt;, ElementA_, layout::ColumnMajor, ElementB_, layout::RowMajor, ElementC_, LayoutC_, arch::OpClassTensorOp, 2, Operator_ &gt;</a></td><td class="entry"></td></tr>
108
+ <tr class="even"><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1threadblock_1_1DefaultMmaCore_3_01Shape___00_01WarpShape___00_01GemmSha69bef08ea63dd930f99d9788105873dd.html#afc60be78e753a885a88842b29363bc33">ElementC</a> typedef</td><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1threadblock_1_1DefaultMmaCore_3_01Shape___00_01WarpShape___00_01GemmSha69bef08ea63dd930f99d9788105873dd.html">cutlass::gemm::threadblock::DefaultMmaCore&lt; Shape_, WarpShape_, GemmShape&lt; 8, 8, 4 &gt;, ElementA_, layout::ColumnMajor, ElementB_, layout::RowMajor, ElementC_, LayoutC_, arch::OpClassTensorOp, 2, Operator_ &gt;</a></td><td class="entry"></td></tr>
109
+ <tr><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1threadblock_1_1DefaultMmaCore_3_01Shape___00_01WarpShape___00_01GemmSha69bef08ea63dd930f99d9788105873dd.html#a89646f5bc7ad42508f5d0bdc258a758c">InstructionShape</a> typedef</td><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1threadblock_1_1DefaultMmaCore_3_01Shape___00_01WarpShape___00_01GemmSha69bef08ea63dd930f99d9788105873dd.html">cutlass::gemm::threadblock::DefaultMmaCore&lt; Shape_, WarpShape_, GemmShape&lt; 8, 8, 4 &gt;, ElementA_, layout::ColumnMajor, ElementB_, layout::RowMajor, ElementC_, LayoutC_, arch::OpClassTensorOp, 2, Operator_ &gt;</a></td><td class="entry"></td></tr>
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+ <tr class="even"><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1threadblock_1_1DefaultMmaCore_3_01Shape___00_01WarpShape___00_01GemmSha69bef08ea63dd930f99d9788105873dd.html#a051a850ff5e96734a936a05b8247e69f">IteratorThreadMapA</a> typedef</td><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1threadblock_1_1DefaultMmaCore_3_01Shape___00_01WarpShape___00_01GemmSha69bef08ea63dd930f99d9788105873dd.html">cutlass::gemm::threadblock::DefaultMmaCore&lt; Shape_, WarpShape_, GemmShape&lt; 8, 8, 4 &gt;, ElementA_, layout::ColumnMajor, ElementB_, layout::RowMajor, ElementC_, LayoutC_, arch::OpClassTensorOp, 2, Operator_ &gt;</a></td><td class="entry"></td></tr>
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+ <tr><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1threadblock_1_1DefaultMmaCore_3_01Shape___00_01WarpShape___00_01GemmSha69bef08ea63dd930f99d9788105873dd.html#ab1a8a43bc393cdc8b9c690d3f1f4b2cb">IteratorThreadMapB</a> typedef</td><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1threadblock_1_1DefaultMmaCore_3_01Shape___00_01WarpShape___00_01GemmSha69bef08ea63dd930f99d9788105873dd.html">cutlass::gemm::threadblock::DefaultMmaCore&lt; Shape_, WarpShape_, GemmShape&lt; 8, 8, 4 &gt;, ElementA_, layout::ColumnMajor, ElementB_, layout::RowMajor, ElementC_, LayoutC_, arch::OpClassTensorOp, 2, Operator_ &gt;</a></td><td class="entry"></td></tr>
112
+ <tr class="even"><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1threadblock_1_1DefaultMmaCore_3_01Shape___00_01WarpShape___00_01GemmSha69bef08ea63dd930f99d9788105873dd.html#a32c6dec4033b897cf0dcd7be05c50e97">kAccessSizeInBits</a></td><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1threadblock_1_1DefaultMmaCore_3_01Shape___00_01WarpShape___00_01GemmSha69bef08ea63dd930f99d9788105873dd.html">cutlass::gemm::threadblock::DefaultMmaCore&lt; Shape_, WarpShape_, GemmShape&lt; 8, 8, 4 &gt;, ElementA_, layout::ColumnMajor, ElementB_, layout::RowMajor, ElementC_, LayoutC_, arch::OpClassTensorOp, 2, Operator_ &gt;</a></td><td class="entry"><span class="mlabel">static</span></td></tr>
113
+ <tr><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1threadblock_1_1DefaultMmaCore_3_01Shape___00_01WarpShape___00_01GemmSha69bef08ea63dd930f99d9788105873dd.html#ada2536fb91814110dec128a60c529e5d">kThreads</a></td><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1threadblock_1_1DefaultMmaCore_3_01Shape___00_01WarpShape___00_01GemmSha69bef08ea63dd930f99d9788105873dd.html">cutlass::gemm::threadblock::DefaultMmaCore&lt; Shape_, WarpShape_, GemmShape&lt; 8, 8, 4 &gt;, ElementA_, layout::ColumnMajor, ElementB_, layout::RowMajor, ElementC_, LayoutC_, arch::OpClassTensorOp, 2, Operator_ &gt;</a></td><td class="entry"><span class="mlabel">static</span></td></tr>
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+ <tr class="even"><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1threadblock_1_1DefaultMmaCore_3_01Shape___00_01WarpShape___00_01GemmSha69bef08ea63dd930f99d9788105873dd.html#ad860546d4ad48fde1742eb335ba8219a">kWarpSize</a></td><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1threadblock_1_1DefaultMmaCore_3_01Shape___00_01WarpShape___00_01GemmSha69bef08ea63dd930f99d9788105873dd.html">cutlass::gemm::threadblock::DefaultMmaCore&lt; Shape_, WarpShape_, GemmShape&lt; 8, 8, 4 &gt;, ElementA_, layout::ColumnMajor, ElementB_, layout::RowMajor, ElementC_, LayoutC_, arch::OpClassTensorOp, 2, Operator_ &gt;</a></td><td class="entry"><span class="mlabel">static</span></td></tr>
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+ <tr><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1threadblock_1_1DefaultMmaCore_3_01Shape___00_01WarpShape___00_01GemmSha69bef08ea63dd930f99d9788105873dd.html#ae0db22993acc56306d5c595bcbdd1c4e">LayoutA</a> typedef</td><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1threadblock_1_1DefaultMmaCore_3_01Shape___00_01WarpShape___00_01GemmSha69bef08ea63dd930f99d9788105873dd.html">cutlass::gemm::threadblock::DefaultMmaCore&lt; Shape_, WarpShape_, GemmShape&lt; 8, 8, 4 &gt;, ElementA_, layout::ColumnMajor, ElementB_, layout::RowMajor, ElementC_, LayoutC_, arch::OpClassTensorOp, 2, Operator_ &gt;</a></td><td class="entry"></td></tr>
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+ <tr class="even"><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1threadblock_1_1DefaultMmaCore_3_01Shape___00_01WarpShape___00_01GemmSha69bef08ea63dd930f99d9788105873dd.html#abff453e33928281f73a7ee5616b77392">LayoutB</a> typedef</td><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1threadblock_1_1DefaultMmaCore_3_01Shape___00_01WarpShape___00_01GemmSha69bef08ea63dd930f99d9788105873dd.html">cutlass::gemm::threadblock::DefaultMmaCore&lt; Shape_, WarpShape_, GemmShape&lt; 8, 8, 4 &gt;, ElementA_, layout::ColumnMajor, ElementB_, layout::RowMajor, ElementC_, LayoutC_, arch::OpClassTensorOp, 2, Operator_ &gt;</a></td><td class="entry"></td></tr>
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+ <tr><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1threadblock_1_1DefaultMmaCore_3_01Shape___00_01WarpShape___00_01GemmSha69bef08ea63dd930f99d9788105873dd.html#a2fb601e219420bc2a306683811797683">LayoutC</a> typedef</td><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1threadblock_1_1DefaultMmaCore_3_01Shape___00_01WarpShape___00_01GemmSha69bef08ea63dd930f99d9788105873dd.html">cutlass::gemm::threadblock::DefaultMmaCore&lt; Shape_, WarpShape_, GemmShape&lt; 8, 8, 4 &gt;, ElementA_, layout::ColumnMajor, ElementB_, layout::RowMajor, ElementC_, LayoutC_, arch::OpClassTensorOp, 2, Operator_ &gt;</a></td><td class="entry"></td></tr>
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+ <tr class="even"><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1threadblock_1_1DefaultMmaCore_3_01Shape___00_01WarpShape___00_01GemmSha69bef08ea63dd930f99d9788105873dd.html#a902194945a2d446b1c5b8b8b9f2b7cfe">MmaPolicy</a> typedef</td><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1threadblock_1_1DefaultMmaCore_3_01Shape___00_01WarpShape___00_01GemmSha69bef08ea63dd930f99d9788105873dd.html">cutlass::gemm::threadblock::DefaultMmaCore&lt; Shape_, WarpShape_, GemmShape&lt; 8, 8, 4 &gt;, ElementA_, layout::ColumnMajor, ElementB_, layout::RowMajor, ElementC_, LayoutC_, arch::OpClassTensorOp, 2, Operator_ &gt;</a></td><td class="entry"></td></tr>
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+ <tr><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1threadblock_1_1DefaultMmaCore_3_01Shape___00_01WarpShape___00_01GemmSha69bef08ea63dd930f99d9788105873dd.html#adf395731ef027df47e8f4012e95bb887">MmaTensorOp</a> typedef</td><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1threadblock_1_1DefaultMmaCore_3_01Shape___00_01WarpShape___00_01GemmSha69bef08ea63dd930f99d9788105873dd.html">cutlass::gemm::threadblock::DefaultMmaCore&lt; Shape_, WarpShape_, GemmShape&lt; 8, 8, 4 &gt;, ElementA_, layout::ColumnMajor, ElementB_, layout::RowMajor, ElementC_, LayoutC_, arch::OpClassTensorOp, 2, Operator_ &gt;</a></td><td class="entry"></td></tr>
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+ <tr class="even"><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1threadblock_1_1DefaultMmaCore_3_01Shape___00_01WarpShape___00_01GemmSha69bef08ea63dd930f99d9788105873dd.html#afeb8d17d6a273e928754fb48efcee76e">Operator</a> typedef</td><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1threadblock_1_1DefaultMmaCore_3_01Shape___00_01WarpShape___00_01GemmSha69bef08ea63dd930f99d9788105873dd.html">cutlass::gemm::threadblock::DefaultMmaCore&lt; Shape_, WarpShape_, GemmShape&lt; 8, 8, 4 &gt;, ElementA_, layout::ColumnMajor, ElementB_, layout::RowMajor, ElementC_, LayoutC_, arch::OpClassTensorOp, 2, Operator_ &gt;</a></td><td class="entry"></td></tr>
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+ <tr><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1threadblock_1_1DefaultMmaCore_3_01Shape___00_01WarpShape___00_01GemmSha69bef08ea63dd930f99d9788105873dd.html#a306af5bbc3c70b900f41539a55eccb2a">OperatorClass</a> typedef</td><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1threadblock_1_1DefaultMmaCore_3_01Shape___00_01WarpShape___00_01GemmSha69bef08ea63dd930f99d9788105873dd.html">cutlass::gemm::threadblock::DefaultMmaCore&lt; Shape_, WarpShape_, GemmShape&lt; 8, 8, 4 &gt;, ElementA_, layout::ColumnMajor, ElementB_, layout::RowMajor, ElementC_, LayoutC_, arch::OpClassTensorOp, 2, Operator_ &gt;</a></td><td class="entry"></td></tr>
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+ <tr class="even"><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1threadblock_1_1DefaultMmaCore_3_01Shape___00_01WarpShape___00_01GemmSha69bef08ea63dd930f99d9788105873dd.html#acb4f53137e01145a137fd4eaebb71f67">Policy</a> typedef</td><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1threadblock_1_1DefaultMmaCore_3_01Shape___00_01WarpShape___00_01GemmSha69bef08ea63dd930f99d9788105873dd.html">cutlass::gemm::threadblock::DefaultMmaCore&lt; Shape_, WarpShape_, GemmShape&lt; 8, 8, 4 &gt;, ElementA_, layout::ColumnMajor, ElementB_, layout::RowMajor, ElementC_, LayoutC_, arch::OpClassTensorOp, 2, Operator_ &gt;</a></td><td class="entry"></td></tr>
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+ <tr><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1threadblock_1_1DefaultMmaCore_3_01Shape___00_01WarpShape___00_01GemmSha69bef08ea63dd930f99d9788105873dd.html#ab40604c28cb3a812614c04f15836de69">Shape</a> typedef</td><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1threadblock_1_1DefaultMmaCore_3_01Shape___00_01WarpShape___00_01GemmSha69bef08ea63dd930f99d9788105873dd.html">cutlass::gemm::threadblock::DefaultMmaCore&lt; Shape_, WarpShape_, GemmShape&lt; 8, 8, 4 &gt;, ElementA_, layout::ColumnMajor, ElementB_, layout::RowMajor, ElementC_, LayoutC_, arch::OpClassTensorOp, 2, Operator_ &gt;</a></td><td class="entry"></td></tr>
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+ <tr class="even"><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1threadblock_1_1DefaultMmaCore_3_01Shape___00_01WarpShape___00_01GemmSha69bef08ea63dd930f99d9788105873dd.html#a5fc4add5b46ac8b363e3fbaec11e635e">SmemIteratorA</a> typedef</td><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1threadblock_1_1DefaultMmaCore_3_01Shape___00_01WarpShape___00_01GemmSha69bef08ea63dd930f99d9788105873dd.html">cutlass::gemm::threadblock::DefaultMmaCore&lt; Shape_, WarpShape_, GemmShape&lt; 8, 8, 4 &gt;, ElementA_, layout::ColumnMajor, ElementB_, layout::RowMajor, ElementC_, LayoutC_, arch::OpClassTensorOp, 2, Operator_ &gt;</a></td><td class="entry"></td></tr>
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+ <tr><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1threadblock_1_1DefaultMmaCore_3_01Shape___00_01WarpShape___00_01GemmSha69bef08ea63dd930f99d9788105873dd.html#a2e52623668aea10ce8c8bad0d6bea5e0">SmemIteratorB</a> typedef</td><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1threadblock_1_1DefaultMmaCore_3_01Shape___00_01WarpShape___00_01GemmSha69bef08ea63dd930f99d9788105873dd.html">cutlass::gemm::threadblock::DefaultMmaCore&lt; Shape_, WarpShape_, GemmShape&lt; 8, 8, 4 &gt;, ElementA_, layout::ColumnMajor, ElementB_, layout::RowMajor, ElementC_, LayoutC_, arch::OpClassTensorOp, 2, Operator_ &gt;</a></td><td class="entry"></td></tr>
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+ <tr class="even"><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1threadblock_1_1DefaultMmaCore_3_01Shape___00_01WarpShape___00_01GemmSha69bef08ea63dd930f99d9788105873dd.html#a28d0b7ceeea828ffc192183a9f3760a4">SmemLayoutA</a> typedef</td><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1threadblock_1_1DefaultMmaCore_3_01Shape___00_01WarpShape___00_01GemmSha69bef08ea63dd930f99d9788105873dd.html">cutlass::gemm::threadblock::DefaultMmaCore&lt; Shape_, WarpShape_, GemmShape&lt; 8, 8, 4 &gt;, ElementA_, layout::ColumnMajor, ElementB_, layout::RowMajor, ElementC_, LayoutC_, arch::OpClassTensorOp, 2, Operator_ &gt;</a></td><td class="entry"></td></tr>
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+ <tr><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1threadblock_1_1DefaultMmaCore_3_01Shape___00_01WarpShape___00_01GemmSha69bef08ea63dd930f99d9788105873dd.html#ad715dac1cb5e5836c506793e1897656c">SmemLayoutB</a> typedef</td><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1threadblock_1_1DefaultMmaCore_3_01Shape___00_01WarpShape___00_01GemmSha69bef08ea63dd930f99d9788105873dd.html">cutlass::gemm::threadblock::DefaultMmaCore&lt; Shape_, WarpShape_, GemmShape&lt; 8, 8, 4 &gt;, ElementA_, layout::ColumnMajor, ElementB_, layout::RowMajor, ElementC_, LayoutC_, arch::OpClassTensorOp, 2, Operator_ &gt;</a></td><td class="entry"></td></tr>
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+ <tr class="even"><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1threadblock_1_1DefaultMmaCore_3_01Shape___00_01WarpShape___00_01GemmSha69bef08ea63dd930f99d9788105873dd.html#aef40ac436e33231522d5e2efe2f7ad70">WarpCount</a> typedef</td><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1threadblock_1_1DefaultMmaCore_3_01Shape___00_01WarpShape___00_01GemmSha69bef08ea63dd930f99d9788105873dd.html">cutlass::gemm::threadblock::DefaultMmaCore&lt; Shape_, WarpShape_, GemmShape&lt; 8, 8, 4 &gt;, ElementA_, layout::ColumnMajor, ElementB_, layout::RowMajor, ElementC_, LayoutC_, arch::OpClassTensorOp, 2, Operator_ &gt;</a></td><td class="entry"></td></tr>
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+ <tr><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1threadblock_1_1DefaultMmaCore_3_01Shape___00_01WarpShape___00_01GemmSha69bef08ea63dd930f99d9788105873dd.html#a9b9289a0c501a320f0aa36c0390e3272">WarpShape</a> typedef</td><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1threadblock_1_1DefaultMmaCore_3_01Shape___00_01WarpShape___00_01GemmSha69bef08ea63dd930f99d9788105873dd.html">cutlass::gemm::threadblock::DefaultMmaCore&lt; Shape_, WarpShape_, GemmShape&lt; 8, 8, 4 &gt;, ElementA_, layout::ColumnMajor, ElementB_, layout::RowMajor, ElementC_, LayoutC_, arch::OpClassTensorOp, 2, Operator_ &gt;</a></td><td class="entry"></td></tr>
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sglang_repo/sgl-kernel/3rdparty/flashinfer/3rdparty/cutlass/docs/structcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___02100c8adad47cbe03be37d64b9a26478.html ADDED
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+ <li class="navelem"><a class="el" href="namespacecutlass.html">cutlass</a></li><li class="navelem"><a class="el" href="namespacecutlass_1_1gemm.html">gemm</a></li><li class="navelem"><a class="el" href="namespacecutlass_1_1gemm_1_1warp.html">warp</a></li><li class="navelem"><a class="el" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html">MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::RowMajor, InstructionShape_, OpDelta_ &gt;</a></li><li class="navelem"><a class="el" href="structcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___093b5d2838ac5a742704ef62b5c8688f0.html">Policy</a></li> </ul>
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+ <div class="title">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::RowMajor, InstructionShape_, OpDelta_ &gt;::Policy Member List</div> </div>
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+ <p>This is the complete list of members for <a class="el" href="structcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___093b5d2838ac5a742704ef62b5c8688f0.html">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::RowMajor, InstructionShape_, OpDelta_ &gt;::Policy</a>, including all inherited members.</p>
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+ <tr class="even"><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___093b5d2838ac5a742704ef62b5c8688f0.html#a29f781ce62fd4a067019ae90aa35c075">MmaIterations</a> typedef</td><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___093b5d2838ac5a742704ef62b5c8688f0.html">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::RowMajor, InstructionShape_, OpDelta_ &gt;::Policy</a></td><td class="entry"></td></tr>
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+ <li><a href="annotated.html"><span>Class&#160;List</span></a></li>
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+ <iframe src="javascript:void(0)" frameborder="0"
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+ </iframe>
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+ </div>
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+
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+ <div id="nav-path" class="navpath">
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+ <ul>
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+ <li class="navelem"><a class="el" href="namespacecutlass.html">cutlass</a></li><li class="navelem"><a class="el" href="namespacecutlass_1_1layout.html">layout</a></li><li class="navelem"><a class="el" href="structcutlass_1_1layout_1_1RowMajorVoltaTensorOpMultiplicandBCongruous.html">RowMajorVoltaTensorOpMultiplicandBCongruous</a></li> </ul>
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+ </div>
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+ </div><!-- top -->
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+ <div class="header">
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+ <div class="headertitle">
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+ <div class="title">cutlass::layout::RowMajorVoltaTensorOpMultiplicandBCongruous&lt; ElementSize &gt; Member List</div> </div>
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+ </div><!--header-->
102
+ <div class="contents">
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+
104
+ <p>This is the complete list of members for <a class="el" href="structcutlass_1_1layout_1_1RowMajorVoltaTensorOpMultiplicandBCongruous.html">cutlass::layout::RowMajorVoltaTensorOpMultiplicandBCongruous&lt; ElementSize &gt;</a>, including all inherited members.</p>
105
+ <table class="directory">
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+ <tr class="even"><td class="entry"><a class="el" href="structcutlass_1_1layout_1_1RowMajorVoltaTensorOpMultiplicandBCongruous.html#ae6751845741fbf3494391564ba85c1c3">AccessCount</a> typedef</td><td class="entry"><a class="el" href="structcutlass_1_1layout_1_1RowMajorVoltaTensorOpMultiplicandBCongruous.html">cutlass::layout::RowMajorVoltaTensorOpMultiplicandBCongruous&lt; ElementSize &gt;</a></td><td class="entry"></td></tr>
107
+ <tr><td class="entry"><a class="el" href="structcutlass_1_1layout_1_1RowMajorVoltaTensorOpMultiplicandBCongruous.html#a8b6ca2d7852ba45313d67cf83536bd1e">Base</a> typedef</td><td class="entry"><a class="el" href="structcutlass_1_1layout_1_1RowMajorVoltaTensorOpMultiplicandBCongruous.html">cutlass::layout::RowMajorVoltaTensorOpMultiplicandBCongruous&lt; ElementSize &gt;</a></td><td class="entry"></td></tr>
108
+ <tr class="even"><td class="entry"><a class="el" href="structcutlass_1_1layout_1_1RowMajorVoltaTensorOpMultiplicandBCongruous.html#a2a556452484f1d6958ec57d0a5b68dea">capacity</a>(TensorCoord const &amp;extent) const </td><td class="entry"><a class="el" href="structcutlass_1_1layout_1_1RowMajorVoltaTensorOpMultiplicandBCongruous.html">cutlass::layout::RowMajorVoltaTensorOpMultiplicandBCongruous&lt; ElementSize &gt;</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
109
+ <tr><td class="entry"><a class="el" href="structcutlass_1_1layout_1_1RowMajorVoltaTensorOpMultiplicandBCongruous.html#a80908838bd1135f03e37d342a140bc34">Index</a> typedef</td><td class="entry"><a class="el" href="structcutlass_1_1layout_1_1RowMajorVoltaTensorOpMultiplicandBCongruous.html">cutlass::layout::RowMajorVoltaTensorOpMultiplicandBCongruous&lt; ElementSize &gt;</a></td><td class="entry"></td></tr>
110
+ <tr class="even"><td class="entry"><a class="el" href="structcutlass_1_1layout_1_1RowMajorVoltaTensorOpMultiplicandBCongruous.html#ab5bc99d0b654ac8a086e1f8012fe2f16">inverse</a>(LongIndex offset) const </td><td class="entry"><a class="el" href="structcutlass_1_1layout_1_1RowMajorVoltaTensorOpMultiplicandBCongruous.html">cutlass::layout::RowMajorVoltaTensorOpMultiplicandBCongruous&lt; ElementSize &gt;</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
111
+ <tr><td class="entry"><a class="el" href="structcutlass_1_1layout_1_1RowMajorVoltaTensorOpMultiplicandBCongruous.html#ad2355d0822557706181cdc0f69d120d5">kAccessSize</a></td><td class="entry"><a class="el" href="structcutlass_1_1layout_1_1RowMajorVoltaTensorOpMultiplicandBCongruous.html">cutlass::layout::RowMajorVoltaTensorOpMultiplicandBCongruous&lt; ElementSize &gt;</a></td><td class="entry"><span class="mlabel">static</span></td></tr>
112
+ <tr class="even"><td class="entry"><a class="el" href="structcutlass_1_1layout_1_1RowMajorVoltaTensorOpMultiplicandBCongruous.html#a43c426d2a016db41441769263525254b">kElementSize</a></td><td class="entry"><a class="el" href="structcutlass_1_1layout_1_1RowMajorVoltaTensorOpMultiplicandBCongruous.html">cutlass::layout::RowMajorVoltaTensorOpMultiplicandBCongruous&lt; ElementSize &gt;</a></td><td class="entry"><span class="mlabel">static</span></td></tr>
113
+ <tr><td class="entry"><a class="el" href="structcutlass_1_1layout_1_1RowMajorVoltaTensorOpMultiplicandBCongruous.html#a57a4589fb0bc4b5675577326f21250b9">kElementsPerAccess</a></td><td class="entry"><a class="el" href="structcutlass_1_1layout_1_1RowMajorVoltaTensorOpMultiplicandBCongruous.html">cutlass::layout::RowMajorVoltaTensorOpMultiplicandBCongruous&lt; ElementSize &gt;</a></td><td class="entry"><span class="mlabel">static</span></td></tr>
114
+ <tr class="even"><td class="entry"><a class="el" href="structcutlass_1_1layout_1_1RowMajorVoltaTensorOpMultiplicandBCongruous.html#a921af4231b727ed09cbd6f8f03443b6c">kRank</a></td><td class="entry"><a class="el" href="structcutlass_1_1layout_1_1RowMajorVoltaTensorOpMultiplicandBCongruous.html">cutlass::layout::RowMajorVoltaTensorOpMultiplicandBCongruous&lt; ElementSize &gt;</a></td><td class="entry"><span class="mlabel">static</span></td></tr>
115
+ <tr><td class="entry"><a class="el" href="structcutlass_1_1layout_1_1RowMajorVoltaTensorOpMultiplicandBCongruous.html#af4a8ae7ae7264c025a223d49bc296a56">kStrideRank</a></td><td class="entry"><a class="el" href="structcutlass_1_1layout_1_1RowMajorVoltaTensorOpMultiplicandBCongruous.html">cutlass::layout::RowMajorVoltaTensorOpMultiplicandBCongruous&lt; ElementSize &gt;</a></td><td class="entry"><span class="mlabel">static</span></td></tr>
116
+ <tr class="even"><td class="entry"><a class="el" href="structcutlass_1_1layout_1_1RowMajorVoltaTensorOpMultiplicandBCongruous.html#a25800f82b5edd600b45db3ce69b51ddb">LongIndex</a> typedef</td><td class="entry"><a class="el" href="structcutlass_1_1layout_1_1RowMajorVoltaTensorOpMultiplicandBCongruous.html">cutlass::layout::RowMajorVoltaTensorOpMultiplicandBCongruous&lt; ElementSize &gt;</a></td><td class="entry"></td></tr>
117
+ <tr><td class="entry"><a class="el" href="structcutlass_1_1layout_1_1RowMajorVoltaTensorOpMultiplicandBCongruous.html#abd1a744d04f46d408e2bdce12660ccf2">operator()</a>(TensorCoord const &amp;coord) const </td><td class="entry"><a class="el" href="structcutlass_1_1layout_1_1RowMajorVoltaTensorOpMultiplicandBCongruous.html">cutlass::layout::RowMajorVoltaTensorOpMultiplicandBCongruous&lt; ElementSize &gt;</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
118
+ <tr class="even"><td class="entry"><a class="el" href="structcutlass_1_1layout_1_1RowMajorVoltaTensorOpMultiplicandBCongruous.html#a860c3a44cff442eada17a765b5744049">packed</a>(TensorCoord const &amp;extent)</td><td class="entry"><a class="el" href="structcutlass_1_1layout_1_1RowMajorVoltaTensorOpMultiplicandBCongruous.html">cutlass::layout::RowMajorVoltaTensorOpMultiplicandBCongruous&lt; ElementSize &gt;</a></td><td class="entry"><span class="mlabel">inline</span><span class="mlabel">static</span></td></tr>
119
+ <tr><td class="entry"><a class="el" href="structcutlass_1_1layout_1_1RowMajorVoltaTensorOpMultiplicandBCongruous.html#ac8c8479bd68f8ff26281ccf20257c416">PartitionCount</a> typedef</td><td class="entry"><a class="el" href="structcutlass_1_1layout_1_1RowMajorVoltaTensorOpMultiplicandBCongruous.html">cutlass::layout::RowMajorVoltaTensorOpMultiplicandBCongruous&lt; ElementSize &gt;</a></td><td class="entry"></td></tr>
120
+ <tr class="even"><td class="entry"><a class="el" href="structcutlass_1_1layout_1_1RowMajorVoltaTensorOpMultiplicandBCongruous.html#ac2ea9ce6186f5940fbfbb9d8528c450d">PartitionShape</a> typedef</td><td class="entry"><a class="el" href="structcutlass_1_1layout_1_1RowMajorVoltaTensorOpMultiplicandBCongruous.html">cutlass::layout::RowMajorVoltaTensorOpMultiplicandBCongruous&lt; ElementSize &gt;</a></td><td class="entry"></td></tr>
121
+ <tr><td class="entry"><a class="el" href="structcutlass_1_1layout_1_1RowMajorVoltaTensorOpMultiplicandBCongruous.html#aad4ca016701d73fee071bf10c35219ab">RowMajorVoltaTensorOpMultiplicandBCongruous</a>(Index ldm=0)</td><td class="entry"><a class="el" href="structcutlass_1_1layout_1_1RowMajorVoltaTensorOpMultiplicandBCongruous.html">cutlass::layout::RowMajorVoltaTensorOpMultiplicandBCongruous&lt; ElementSize &gt;</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
122
+ <tr class="even"><td class="entry"><a class="el" href="structcutlass_1_1layout_1_1RowMajorVoltaTensorOpMultiplicandBCongruous.html#ab6c4659f6f6a893ae6327964158a762b">RowMajorVoltaTensorOpMultiplicandBCongruous</a>(Stride stride)</td><td class="entry"><a class="el" href="structcutlass_1_1layout_1_1RowMajorVoltaTensorOpMultiplicandBCongruous.html">cutlass::layout::RowMajorVoltaTensorOpMultiplicandBCongruous&lt; ElementSize &gt;</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
123
+ <tr><td class="entry"><a class="el" href="structcutlass_1_1layout_1_1RowMajorVoltaTensorOpMultiplicandBCongruous.html#a3339e229b6a98b36c12fbe078c000253">stride</a>() const </td><td class="entry"><a class="el" href="structcutlass_1_1layout_1_1RowMajorVoltaTensorOpMultiplicandBCongruous.html">cutlass::layout::RowMajorVoltaTensorOpMultiplicandBCongruous&lt; ElementSize &gt;</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
124
+ <tr class="even"><td class="entry"><a class="el" href="structcutlass_1_1layout_1_1RowMajorVoltaTensorOpMultiplicandBCongruous.html#a2670d9258bf26606a2893178060c4045">stride</a>()</td><td class="entry"><a class="el" href="structcutlass_1_1layout_1_1RowMajorVoltaTensorOpMultiplicandBCongruous.html">cutlass::layout::RowMajorVoltaTensorOpMultiplicandBCongruous&lt; ElementSize &gt;</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
125
+ <tr><td class="entry"><a class="el" href="structcutlass_1_1layout_1_1RowMajorVoltaTensorOpMultiplicandBCongruous.html#aa336aaa24657da9066b65071fc6c079d">Stride</a> typedef</td><td class="entry"><a class="el" href="structcutlass_1_1layout_1_1RowMajorVoltaTensorOpMultiplicandBCongruous.html">cutlass::layout::RowMajorVoltaTensorOpMultiplicandBCongruous&lt; ElementSize &gt;</a></td><td class="entry"></td></tr>
126
+ <tr class="even"><td class="entry"><a class="el" href="structcutlass_1_1layout_1_1RowMajorVoltaTensorOpMultiplicandBCongruous.html#a4a0e04585251e71a206eed06abcba609">TensorCoord</a> typedef</td><td class="entry"><a class="el" href="structcutlass_1_1layout_1_1RowMajorVoltaTensorOpMultiplicandBCongruous.html">cutlass::layout::RowMajorVoltaTensorOpMultiplicandBCongruous&lt; ElementSize &gt;</a></td><td class="entry"></td></tr>
127
+ <tr><td class="entry"><a class="el" href="structcutlass_1_1layout_1_1RowMajorVoltaTensorOpMultiplicandBCongruous.html#a308cc4d18560408bc3c17ea090877b18">TileShape</a> typedef</td><td class="entry"><a class="el" href="structcutlass_1_1layout_1_1RowMajorVoltaTensorOpMultiplicandBCongruous.html">cutlass::layout::RowMajorVoltaTensorOpMultiplicandBCongruous&lt; ElementSize &gt;</a></td><td class="entry"></td></tr>
128
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+ <li class="navelem"><a class="el" href="namespacecutlass.html">cutlass</a></li><li class="navelem"><a class="el" href="namespacecutlass_1_1platform.html">platform</a></li><li class="navelem"><a class="el" href="structcutlass_1_1platform_1_1alignment__of_3_01long4_01_4.html">alignment_of&lt; long4 &gt;</a></li> </ul>
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+ <div class="contents">
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+ <p>This is the complete list of members for <a class="el" href="structcutlass_1_1platform_1_1alignment__of_3_01long4_01_4.html">cutlass::platform::alignment_of&lt; long4 &gt;</a>, including all inherited members.</p>
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+ <table class="directory">
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+ <tr class="even"><td class="entry"><a class="el" href="structcutlass_1_1platform_1_1alignment__of_3_01long4_01_4.html#a773c4b1a1a8c6d7600152ffb073087eea3d020dd8ba5c735a60d7c2c897e158f5">value</a> enum value</td><td class="entry"><a class="el" href="structcutlass_1_1platform_1_1alignment__of_3_01long4_01_4.html">cutlass::platform::alignment_of&lt; long4 &gt;</a></td><td class="entry"></td></tr>
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+ <tr class="even"><td class="entry"><a class="el" href="structcutlass_1_1transform_1_1threadblock_1_1RegularTileAccessIterator_3_01Shape___00_01Element_3be8b96d170d886f39b6b30acab65e7a.html#a1ef8ca3c06d9ce974836317f67b5d752">kAccessSizeInBits</a></td><td class="entry"><a class="el" href="structcutlass_1_1transform_1_1threadblock_1_1RegularTileAccessIterator_3_01Shape___00_01Element_3be8b96d170d886f39b6b30acab65e7a.html">cutlass::transform::threadblock::RegularTileAccessIterator&lt; Shape_, Element_, layout::TensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, AdvanceRank, ThreadMap_, Alignment &gt;::Detail</a></td><td class="entry"><span class="mlabel">static</span></td></tr>
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+ <tr><td class="entry"><a class="el" href="structcutlass_1_1transform_1_1threadblock_1_1RegularTileAccessIterator_3_01Shape___00_01Element_3be8b96d170d886f39b6b30acab65e7a.html#af6f2e4a74ec2bd4c258208d53e06f4d0">kPointerCount</a></td><td class="entry"><a class="el" href="structcutlass_1_1transform_1_1threadblock_1_1RegularTileAccessIterator_3_01Shape___00_01Element_3be8b96d170d886f39b6b30acab65e7a.html">cutlass::transform::threadblock::RegularTileAccessIterator&lt; Shape_, Element_, layout::TensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, AdvanceRank, ThreadMap_, Alignment &gt;::Detail</a></td><td class="entry"><span class="mlabel">static</span></td></tr>
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