# Linsolve on SparseMatrixCSC{BigFloat}

**URL:** <https://discourse.julialang.org/t/linsolve-on-sparsematrixcsc-bigfloat/60742>\
**Category:** Numerics\
**Tags:** question, diffeq, linearalgebra, sparse\
**Created:** [May 7, 2021, 8:53pm UTC](https://discourse.julialang.org/t/linsolve-on-sparsematrixcsc-bigfloat/60742 "2021-05-07T20:53:50Z")\
**Posts on this page:** 1\
**Showing post:** 2

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**Author:** ![ChrisRackauckas](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/chrisrackauckas/32/77_2.png) [@ChrisRackauckas](https://discourse.julialang.org/u/ChrisRackauckas)\
**Post date:** [May 13, 2021, 1:35am UTC](https://discourse.julialang.org/t/linsolve-on-sparsematrixcsc-bigfloat/60742/2 "2021-05-13T01:35:51Z")

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> [@MatFi](#):
>
> So I tried to use iterative solvers from [IterativeSolvers.jl](https://julialinearalgebra.github.io/IterativeSolvers.jl/) as they are purely implemented in Julia an thus can handle the sparse jacobians. But than I run into the next problem. Literally all solvers lead to instability warnings and the integration of the DAE stopped after one or two steps. My first thought was, that this is due to the Rosenbrock integrators which to my knowledge demand for precise jacobians and the iterative solvers simply could not cover these requirements, but other algs fail as well.

At what tolerance was the iterative solve to? If you don’t lower that tolerance it may be too high.

I think iterative solvers might be your only way to go until we have a generic sparse LU.

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