implementing sparse matrix multiplication in MATLAB affecting performance
I recently switched to I'm running into unexpected performance optimization when trying to multiply sparse matrices in MATLAB, specifically when using the `*` operator. I have a sparse matrix `A` of size 10000x10000 and another sparse matrix `B` of size 10000x10000. Both matrices contain about 1% non-zero elements. When I execute the following code: ```matlab C = A * B; ``` The operation takes significantly longer than expected, often exceeding 10 seconds. I've verified that both matrices are indeed sparse using `issparse(A)` and `issparse(B)`. I've also tried converting them to full matrices with `full(A)` before multiplication, but that results in memory issues, as they are too large to fit. I've checked the MATLAB documentation for the `sparse` function and the multiplication operator, but I need to find any suggestions for optimizing this operation. I'm using MATLAB R2023a. Is there a more efficient way to handle sparse matrix multiplication, or am I missing some key settings that could speed this up? I've been using Matlab for about a year now. Thanks in advance!