<p>Apparently, <code>float128</code> is much slower than <code>double</code>. Like up to 100x slower but the precise slowdown would depend on the operations, of course.</p>

<p><a href="https://www.nsc.liu.se/~pla/blog/2013/10/17/quadruple-precision/" rel="nofollow noreferrer">Multiplying two 256x256 matrices</a> is 100x slower.</p>

<p>The paper <a href="http://perso.ens-lyon.fr/philippe.theveny/benchs/binary128_emu.pdf" rel="nofollow noreferrer">Benchmark of an MPFR emulation of Binary128 arithmetic</a> cites 250x slowdown for summation, 120x slowdown for product, 400x slowdown for dot product.</p>

<p>Another paper <a href="https://arxiv.org/pdf/1412.5316.pdf" rel="nofollow noreferrer">Twofolds in C and C++</a> says <code>__float128</code> summation is 150x (25x times 6x) slower than <code>double</code> summation.</p>
Performance benchmark of float128 type?
<p>Has anyone experienced with <code>float128</code> type? </p>

<p>I would like to know about its performance compared with <code>double</code>, and other high precision types such as <code>boost::multiprecision:cpp_dec_float</code>? Is there any benchmark already done?</p>