[PyCUDA] PyCUDA and fast user-generated code
lists at informa.tiker.net
Wed Nov 10 14:48:47 PST 2010
On Wed, 10 Nov 2010 22:10:55 -0000, "Daniel White" <twinbee42 at skytopia.com> wrote:
> Hi Tomasz and Andreas,
> Thanks both for the info. I've considered OpenCL, but from what I've
> seen, it's
<CL myth debunking below>
- not quite as mature as CUDA
To make up for that, it avoids some of CUDA's design mistakes. (e.g.
context as thread-global state) Also, the CL drivers have been through a
few revisions, and they've come a long way. Lastly, CL builds on the
same infrastructure as CUDA (in Nvidia's case) and thus benefits from
CUDA's maturity where it matters most.
Not true. A colleague of mine (Tim Warburton) was able to get equivalent
code running faster on CL than on CUDA, on the same hardware. (Perhaps
the LLVM-based compiler is better? Who knows.)
- more difficult to use
If you compare the example programs at
it's plain to see that that's not the case.
> though that might have changed in these past few months). I love the
> principle of the open standard. I just wish CUDA could become like that.
> I may also hold off until Microsoft release their GPGPU language.
MS have released a GPGPU language, it's called DirectCompute, and mainly
for use with DirectX in games. (Were they planning on releasing another
I'm not meaning to tell you that you should use CL, I'm just trying to
make sure you base your decision on accurate information. :)
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