On Tue, 13 Dec 2011 07:53:40 -0800 (PST), ggeo <gg...@windowslive.com> wrote: > Hello , i am starting to learnd pyCuda and i have a few questions. > > 1) When i create a Cuda project (or PyCuda) how can i handle the threads and > blocks in order to maximize the efficiency.I mean ,that when i create a > project i don't now where (in what card ) it would run.Is there a way to > handle this?
Excellent question. Unfortunately, aside from autotuning (which PyCUDA will let you do quite easily), nobody has figured out a good solution to that--at least as far as I know. In general, the answer is very much problem-specific. > 2) If i have to include headers or libraries ,for example "#include > <boost/array.hpp>" is there a way to do this?Because it doesn't accept this. > (Ok, one way for the header is to put it in the kernel function) All your functions/methods must be __device__ methods, so directly using existing headers (such as boost) is not going to work. That said, using header files with PyCUDA should be fine, as long as you specify the path to them (even if they live in the current directory--because PyCUDA doesn't run nvcc in the current working directory). HTH, Andreas
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