I am trying to calculate the eigenvalues of a large (say, n=1000 to 10000) sparse Hermitian square matrix using SAGE
numpy.linalg.eigvalsh(MyMatrix)
takes very long. I noticed it utilizes only a single core of my CPU.
How would one go about speeding the calculation? Specifically, I'm looking for a solution using parallel computation, or maybe something which is "more compiled".
Thank you.
