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Message-ID: <f56ab8d3442b9fb65d9ea262a6184cdc@smtp.hushmail.com> Date: Sun, 23 Aug 2015 23:05:30 +0200 From: magnum <john.magnum@...hmail.com> To: john-dev@...ts.openwall.com Subject: Re: interleaving on GPUs On 2015-08-23 07:08, Solar Designer wrote: > I just read this about NVIDIA's Kepler (such as the old GTX TITAN that > we have in super): > > http://docs.nvidia.com/cuda/kepler-tuning-guide/index.html#device-utilization-and-occupancy > > "Also note that Kepler GPUs can utilize ILP in place of > thread/warp-level parallelism (TLP) more readily than Fermi GPUs can. > Furthermore, some degree of ILP in conjunction with TLP is required by > Kepler GPUs in order to approach peak single-precision performance, > since SMX's warp scheduler issues one or two independent instructions > from each of four warps per clock. ILP can be increased by means of, for > example, processing several data items concurrently per thread or > unrolling loops in the device code, though note that either of these > approaches may also increase register pressure." > > Note that they explicitly mention "processing several data items > concurrently per thread". So it appears that when targeting Kepler, up > to 2x interleaving at OpenCL kernel source level could make sense. Shouldn't simply using vectorized code (eg. using uint2) result in just the interleaving we want (on nvidia)? I tested this with some of our formats that can optionally run vectorized but they don't seem to gain from --force-vector=2. magnum
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