I’m trying to compute the sparse matrix exponential of large matrices (at least 10,000 x 10,000) using Julia packages like Expokit, FastExp, and ExpmV. However, I’m finding that the computation time is significantly longer compared to using Python’s `scipy.sparse.linalg.expm_multiply`

.

For example, I’m using the function `expmv(1.0, M, rho_vectorized)`

, where `M`

is a sparse matrix.

What methods or strategies can I use to speed up the computation of the sparse matrix exponential in Julia? Any advice or tips would be greatly appreciated!