On Freitag 26 Juni 2009, Vince Fulco wrote: > Early attempts to port over the Monte Carlo Option Pricing code > supplied with the SDK and need to mod it for simple time series > bootstrapping. Not being terribly facile in C/C++ (but learning!), > could someone provide a short list of the critical components which > need to be wrapped by pycuda?
What PyCUDA can do for you is compile and execute functions marked __global__ in that sample's source code--i.e. code that runs on the GPU. Everything else is CPU code, and making that accessible is beyond the scope of PyCUDA. If you do want to leave that CPU code in C, there are several other packages that might help you, ranging from Swig, Cython, Boost Python (potentially with codepy), to ctypes. I'm guessing that you might have the most fun if you just port the CPU control code to Python, though--less hassle. > I am aware of the various > kernels/functions necessary from the main body of code but more > interested in a how-to in terms of referencing the ancillary functions > properly. I.E. the RNGs "MonteCarlo_SM10" and "MonteCarlo_SM13" > routines. See above--if you want to keep those in C, use one of the packages mentioned above (and worry about compiling them separately), or just quickly translate them to Python. (you'll find they get a fair bit shorter :P) Andreas
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