title: Strange results for CUDA SDK Bandwidth Test
body: <p>I have a CUDA application that is data movement bound (i.e. large memcopies from host to device with relatively little computations done in the kernel).  On older GPUs I was compute-bound (e.g. QUADRO FX 5800), but with Fermi and Kepler architectures, that is no longer the case (for my optimized code).</p>
  
  <p>I just moved my code to a GTX 680 and was impressed with the increased compute performance, but perplexed that the bandwidth between the host and GPU seems to have dropped (relative to my Fermi M20270).</p>
  
  <p>In short when I run the canned SDK bandwidth test I get ~5000 MB/sec on the GTX 680 versus ~5700 MB/sec on the M2070.  I recognize that the GTX is "only a gamer card", but the specs for the GTX 680 seem more impressive than for the M2070, WITH THE EXCEPTION OF THE BUS WIDTH.</p>
  
  <p>From wikipedia:
  M2070: 102.4 GB/sec, GDDR3, 512 bit bus width
  GTX 680: 192 GB/sec, GDDR5, 256 bit bus width</p>
  
  <p>I'm running the canned test with "--wc --memory=pinned" to use write-combined memory.</p>
  
  <p>The improved results I get with this test are mirrored by the results I am getting with my optimized CUDA code.</p>
  
  <p>Unfortunately, I can't run the test on the same machine (and just switch video cards), but I have tried the GTX 680 on older and newer machines and get the same "degraded" results (relative to what I get on the M2070).</p>
  
  <p>Can anyone confirm that they are able to achieve higher throughput memcopies with the M2070 Quadro than the GTX 680?  Doesn't the bandwidth spec take into consideration the bus width?  The other possibility is that I'm not doing the memcopies correctly/optimally on the GTX 680, but in that case, is there a patch for the bandwidth test so that it will also show that I'm transfering data faster to the 680 than to the M2070?</p>
  
  <p>Thanks.</p>