A lot of matrix routines will have sparse matrix support. Though often the line between wanting a sparse matrix and wanting some kind of adjacency-list graph st

A lot of matrix routines will have sparse matrix support. Though often the line between wanting a sparse matrix and wanting some kind of adjacency-list graph structure can be pretty fine... Also, only tangentially related, but if you can change your problem formulation to make the matrix of interest sparse(r), that can be a huge win. Two things that have helped me in the past: - Rows or columns that have mostly the same (nonzero) coefficient throughout. You can normally do some simple substitution to turn them into zeros. - Rows or columns that are naturally very similar to each other. You can often replace `y` with `y-x` or replace `x[i]` with `x[i]-x[i+1]` to turn one (or `n-1`) columns "mostly empty."