Dnia 2010-09-28, wto o godzinie 23:46 -0400, Andreas Kloeckner pisze: > On Mon, 27 Sep 2010 04:42:00 -0700 (PDT), jmcarval <jmcar...@fe.up.pt> wrote: > > > > Hi. > > Installed PyCUDA 0.94.1 in several Linux boxes. > > All have Ubuntu 10.4 with CUDA 3.1 (drv 256.40) and python 2.6.5 > > > > Boxes with 1.1 capability GPUs like 8600GT, 9400 GT or FX850 are ok and some > > user's are already trying them. > > Boxes with 1.3 (GTX280) and 2.0 (GTX480) have dificulties just running the > > supplied tests. On these: > > > > test_cumath.py passes all tests but is 5 times slower in the GTX280 and > > 40(!) times slower in the GTX480 > > As far as I can see, this test never uses float64 > > This might just be due to the G80/G92 compilers being faster than the > 280/480 ones. In general, the tests are not meant for benchmarking. That > said, I don't really observe slowdowns like that. > > > test_gpuarray.py is 2 times slower in the GTX280 and fails the dot, sum, > > minmax and subset_minmax tests on the GTX480. > > I can't reproduce these issues on the Fermi devices (all C2050s on > Linux) that I have access to, so I'm having a hard time tracking down > this problem. Any help would be much appreciated. > > As a hypothesis: Are there multiple versions of the Fermi silicon? Any > way to detect which one you have?
GTX 470/480 have GF100 which provides computing capabilities 2.0 GTX 460 has GF104, which has computing capabilities 2.1 - including 48 (not 32 as in all previous chips) processors per MP. I do not know anything about Tesla and other high-end hardware. I am not sure how it is related though. -- Tomasz Rybak <bogom...@post.pl> GPG/PGP key ID: 2AD5 9860 Fingerprint A481 824E 7DD3 9C0E C40A 488E C654 FB33 2AD5 9860 http://member.acm.org/~tomaszrybak
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