Julia is slower than matlab when it comes to matrix diagonalization?

[Ralph_Smith]

Here is my source:

Some eigenpairs from a large, sparse, nonsymmetric matrix: Julia vs Matlab

Actually, Matlab does not use Arpack anymore. Instead, they have implemented their own version of the Krylov-Schur method accessible from the Matlab prompt with edit eigs.m. I am not sure whether the following tweak will resolve your issue, however, I remember from my own work on a modesolver that SuiteSparse conducts an iterative refinement of the solutions by default. Disabling this refinement using SuiteSparse.UMFPACK.umf_ctrl[8] = 0 improved the performance of eigs significantly for my us…

Further down that thread is an updated way to get the faster sparse solution, which may help @jiang_ming_zhang as well.