N = 1000 x = sprand(N, N, 0.5) \ full(sprand(N, 1, 0.5) The code is giving us some solutions. For N=10000 memory runs out of my laptop machine. What are my options if I want to go, for example, N=10000000, assumed that there is enough performance in distributed machines?

Distributed computing of x = A \ b

simonbyrne July 29, 2018, 5:41am 4

Also, p = 0.5 is way too high for typical uses of sparse matrices: see this discussion.

1 Like

Topic		Replies	Views
Finite Element Computations On A Cluster Using Petsc.jl Numerics question , package	2	2297	April 21, 2017
MPI/Distributed linear system solver? New to Julia parallel , linearalgebra	20	1236	October 26, 2023
Options for Sparse Distributed Linear Algebra Numerics	2	794	November 19, 2021
Distributed/out-of-memory/GPU calculations on sparse matrices General Usage gpu	2	1347	March 22, 2017
Distributed eigensolvers for computing eigenpairs of large sparse matrices Numerics question , package , parallel , distributed , eigenvalues	6	566	September 28, 2022