I'll have to work with large hermitian matrices and calculate traces, eigenvalues and perform several matric products. In order to speed those up, i noticed that blas includes a function called 'zhemm' for efficient matrix products with at least one hermitian matrix.
is there a way to call that one directly for numpy arrays? are there other, more efficient methods for multiplying that large matrices that one of you might be aware of? especially with the knowledge that they are symmetric/hermitian. i'd appreciate any help in that regard. thanks, q ps: i tried to port the functionality of zhemm into cython, but this is still about a factor of 10 slower than directly using numpy.dot -- There are two things children should get from their parents: roots and wings. The king who needs to remind his people of his rank, is no king. A beggar's mistake harms no one but the beggar. A king's mistake, however, harms everyone but the king. Too often, the measure of power lies not in the number who obey your will, but in the number who suffer your stupidity. _______________________________________________ NumPy-Discussion mailing list [email protected] http://mail.scipy.org/mailman/listinfo/numpy-discussion
