efficient linear algebra
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Hi, I have a simulation that has to repeatedly find the dot product of a 250,000x3 array with a 3x1 array. I have a working atlas 3.6.0, and believe scipy to be properly installed, all the tests pass, etc. I read (http://www.scipy.org/mailinglists/mailman?fn=scipy-user/2004-June/002902.htm...) that scipy.dot may not be the fastest solution, so I tried dot, = scipy.linalg.blas.get_blas_funcs(['gemm'],(ones([250000,3],'d'),ones((3,1),'d'))) and dot, = scipy.linalg.blas.get_blas_funcs(['dot'],(ones([250000,3],'d'),ones((3,1),'d'))) When I tested how long each takes, scipy.dot took .1 seconds, the blas gemm took 0.13 seconds, and the blas dot gave me the following error: error: (len(y)-offy>(n-1)*abs(incy)) failed for 1st keyword n If I dot an Nx3 with a 3x1, I get the above error. If I dot a 1x3 with a 3xN, I do not get the error. Is this a bug? Is my approach correct? Should I expect much of a performance boost from using the function returned by get_blas_funcs, and if so, are there suggestions as to why I might be taking a performance hit? Where can I learn more about using the blas routines intelligently? Thank you, Darren
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Darren Dale