# Cholesky Decomposition of a Sparse Symmetric Positive Semidefinite (SPSD) Singular Matrix

**URL:** <https://discourse.julialang.org/t/cholesky-decomposition-of-a-sparse-symmetric-positive-semidefinite-spsd-singular-matrix/119682>\
**Category:** Numerics\
**Tags:** linearalgebra, numerics, sparse, factorization\
**Created:** [September 21, 2024, 2:57pm UTC](https://discourse.julialang.org/t/cholesky-decomposition-of-a-sparse-symmetric-positive-semidefinite-spsd-singular-matrix/119682 "2024-09-21T14:57:40Z")\
**Posts on this page:** 1\
**Showing post:** 20

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**Author:** ![RoyiAvital](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/royiavital/32/571_2.png) [@RoyiAvital](https://discourse.julialang.org/u/RoyiAvital)\
**Post date:** [September 23, 2024, 5:31pm UTC](https://discourse.julialang.org/t/cholesky-decomposition-of-a-sparse-symmetric-positive-semidefinite-spsd-singular-matrix/119682/20 "2024-09-23T17:31:44Z")

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> [@dpo](#):
>
> It’s worth benchmarking. If A is that sparse, matrix-vector products will be very fast.

[I did benchmark](https://discourse.julialang.org/t/119655/8). They were order of magnitude slower.

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