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
>

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