pyCUDA vs C performance differences?
I'm new to CUDA programming and I was wondering how the performance of pyCUDA is compared to programs implemented in plain C. Will the performance be roughly the same? Are there any bottle necks that I should be aware of?
EDIT: I obviously tried to google this issue first, and was surprised to not find any information. i.e. I would have excepted that the pyCUDA people have this question answered in their FAQ.
Answer
If you're using CUDA -- whether directly through C or with pyCUDA -- all the heavy numerical work you're doing is done in kernels that execute on the gpu and are written in CUDA C (directly by you, or indirectly with elementwise kernels). So there should be no real difference in performance in those parts of your code.
Now, the initialization of arrays, and any post-work analysis, will be done in python (probably with numpy) if you use pyCUDA, and that generally will be significantly slower than doing it directly in a compiled language (though if you've built your numpy/scipy in such a way that it links directly to high-performance libraries, then those calls at least would perform the same in either language). But hopefully, your initialization and finalization are small fractions of the total amount of work you have to do, so that even if there is significant overhead there, it still hopefully won't have a huge impact on overall runtime.
And in fact if it turns out that the python parts of the computation does hurt your application's performance, starting out doing your development in pyCUDA may still be an excellent way to get started, as the development is significantly easier, and you can always re-implement those parts of the code that are too slow in Python in straight C, and call those from python, gaining some of the best of both worlds.