When I run import numpy as np
a = np.ones((400, 500000), dtype=np.float32) c = np.dot(a, a.T) produces a "MemoryError" on the 32-bit Enthought Python Distribution on 32-bit Vista. I understand this has to do with the 2GB limit with 32-bit python and the fact numpy wants a contiguous chunk of memory for an array. When I look at the memory use in the task manager though, it looks like it's trying to allocate enough for two 400x500000 arrays. I guess it's explicitly forming a.T. Is there a way to avoid this? I tried c = scipy.lib.blas.fblas.dgemm(1.0, a, a, trans_b=1) but I get the same result. It appears to be using a lot of extra memory. Isn't this just a wrapper to the blas library that passes a pointer to the memory location of a? Why does it seem to be generating the transpose? Is there a way to do A*A.T without two copies of A? Thanks, Greg _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
