Lewis, "Mcgibbney, Lewis J (398M)" <[email protected]> writes: > I DO NOT need to use PyCUDA in stages 1 or 4 e.g. Pre and post processing. > > What I am looking for is advice on what is ‘common’ practice for NOT > reimplementing an entire project (>13,000 C and IDL code) in PyCUDA but > instead on using PyCUDA in conjunction with the C and IDL where PyCUDA would > be leveraged to to the heavily lifting of the ‘many at once’ pixel > classification task which is part of the spectral unmixing. > Is this kind of thing done often? > Is it common to be combining PyCUDA with code in other languages to achieve > these types of tasks?
While I'm not sure I can speak with authority on how common this type of usage is, I think I can say with some confidence that Python is probably one of the easier language in which to pull off a coupling such as what you describe. In general, Python excels in the role of a 'glue' language coupling disparate components together. For instance, there is an existing coupling module that would let you talk to your IDL code and seamlessly exchange data as numpy arrays: http://www.cacr.caltech.edu/~mmckerns/pyIDL.html Python is further very easy to couple with existing C code, and perhaps the main 'problem' is that there are a large number of approaches available that you could use, ranging from 'cffi', 'swig', 'boost.python', and many more ways of accomplishing this wrapping. Hope that helps at least a bit, Andreas
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