I was talking about emulation mode. It is a pity that I cannot use it with pycuda. For I have implemented a part of my algorithm in cuda now, and wanted to see how much faster it is. Right now I can only compare it with my previous implementation using python and rpy. And this will always be slower than anything wrapped around some C stuff. So a quick way to see what the cuda stuff actually did, was using the emulation mode. However, for me a real benchmark is not required. I was just curious. I am just using this algorithm to learn stuff about cuda, because I see some real potential in it. And it is always better to learn new stuff for things you need. My first Python/R implementation took 1.5 hours and now it is done in 3 seconds. And that with only an hour or 2 coding/learning. I know for sure that I could have slashed a big chunk from the 1.5 hours by just doing the computation in C instead of R, but then I woulnd't be learning cuda :)
But thanks for explaining that it is not possible nor that it would be a good benchmark. Cheers, Willem Ligtenberg On Mon, Apr 20, 2009 at 11:38, Ahmed Fasih <[email protected]> wrote: > I think you are talking about emulation mode, which depends on the > "other" CUDA API that PyCUDA is not written in. It is not supported in > PyCUDA: http://tiker.net/pipermail/pycuda_tiker.net/2008-December/000063.html > > Furthermore, emulation mode is no way to benchmark speedups; this > would be unacceptable for a computing journal or conference (or by > anyone else :P). Frequently the most trivial CPU implementation of an > algorithm is faster than emulation mode, especially for large > problems. To compare CPU and GPU performance, you find the fastest CPU > implementation (leveraging all the features of modern processors such > as SIMD, multi-threading, maximum cache hits, etc.) and compare your > GPU code to that. > > On Mon, Apr 20, 2009 at 5:14 AM, Willem Ligtenberg > <[email protected]> wrote: >> Hi, >> >> I know cuda has a compile option that lets you run the code on CPU >> instead of GPU (and then uses multicore as well). How do I make my >> pycuda script run on the CPUinstead of the GPU? This may also help me >> with specifying how much faster it goes. >> >> Thanks in advance, >> >> Willem Ligtenberg >> >> _______________________________________________ >> PyCuda mailing list >> [email protected] >> http://tiker.net/mailman/listinfo/pycuda_tiker.net >> > _______________________________________________ PyCuda mailing list [email protected] http://tiker.net/mailman/listinfo/pycuda_tiker.net
