# How to distribute the solving of a linear system on multiple Procs?

**URL:** <https://discourse.julialang.org/t/how-to-distribute-the-solving-of-a-linear-system-on-multiple-procs/82359>\
**Category:** General Usage\
**Tags:** question, linearalgebra, distributions\
**Created:** [June 7, 2022, 7:24am UTC](https://discourse.julialang.org/t/how-to-distribute-the-solving-of-a-linear-system-on-multiple-procs/82359 "2022-06-07T07:24:06Z")\
**Posts on this page:** 1\
**Page:** 1

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**Author:** ![Eurel](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/eurel/32/35982_2.png) [@Eurel](https://discourse.julialang.org/u/Eurel)\
**Post date:** [June 7, 2022, 7:24am UTC](https://discourse.julialang.org/t/how-to-distribute-the-solving-of-a-linear-system-on-multiple-procs/82359/1 "2022-06-07T07:24:06Z")

</div>

I intend to solve a linear system on a cluster and expect some scaling.  
I tried to combine DistributedArrays.jl with IterativeSolvers.jl on my local machine but it would seem the overhead isn’t worth it.

```julia
using DistributedArrays, IterativeSolvers

a = rand(128,128); a_d = distribute(a)
v = rand(128)

@time gmres(a,v) # 0.001 seconds
@time gmres(a_d,v) # 124 seconds

```

Are there iteratives or direct solvers that would easily utilize parallel resources ?