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I am looking to use the multiprocessing module to speed up the run time of some Transport Planning models. I've optimized as much as I can via 'normal' methods but at the heart of it is an absurdly parallel problem. Eg Perform the same set of matrix operations four 4 different sets of inputs, all independent information. Pseudo Code: for mat1,mat2,mat3,mat4 in zip([a1,a2,a3,a4],[b1,b2,b3,b4],[c1,c2,c3,c4],[d1,d2,d3,d4]): result1 = mat1*mat2^mat3 result2 = mat1/mat4 result3 = mat3.T*mat2.T+mat4 So all I really want to do is process the iterations of this loop in parallel on a quad core computer. I've read up here and other places on the multiprocessing module and it seems to fit the bill perfectly except for the required: if __name__ == '__main__' From what I understand this means that you can only multiprocess code run from a script? ie if I do something like: import multiprocessing from numpy.random import randn a = randn(100,100) b = randn(100,100) c = randn(100,100) d = randn(100,100) def process_matrix(mat): return mat^2 if __name__=='__main__': print "Multiprocessing" jobs=[] for input_matrix in [a,b,c,d]: p = multiprocessing.Process(target=process_matrix,args=(input_matrix,)) jobs.append(p) p.start() It runs fine, however assuming I saved the above as 'matrix_multiproc.py', and defined a new file 'importing_test.py' which just states: import matrix_multiproc The multiprocessing does not happen because the name is now 'matrix_multiproc' and not ' main ' Does this mean I can never use parallel processing on an imported module? All I am trying to do is have my model run as: def Model_Run(): import Part1, Part2, Part3, matrix_mult

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