# Options for large-scale dense linear algebra

**URL:** <https://discourse.julialang.org/t/options-for-large-scale-dense-linear-algebra/78227>\
**Category:** Julia at Scale\
**Tags:** hpc\
**Created:** [March 21, 2022, 5:12pm UTC](https://discourse.julialang.org/t/options-for-large-scale-dense-linear-algebra/78227 "2022-03-21T17:12:42Z")\
**Posts on this page:** 2\
**Page:** 1

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**Author:** ![wcwitt](https://avatars.discourse-cdn.com/v4/letter/w/5f8ce5/32.png) [@wcwitt](https://discourse.julialang.org/u/wcwitt)\
**Post date:** [March 21, 2022, 5:12pm UTC](https://discourse.julialang.org/t/options-for-large-scale-dense-linear-algebra/78227/1 "2022-03-21T17:12:42Z")

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My team is trying to identify options for dense-matrix distributed linear algebra on ~100s-1000s of CPU cores spread over multiple nodes. We are hoping for at least QR and Cholesky factorization, as well as linear equation solvers.

Initially, we expected to use [`ScaLAPACK.jl`](https://github.com/JuliaParallel/ScaLAPACK.jl), but it does not seem to be maintained actively. [I see](https://discourse.julialang.org/t/distributed-memory-qr-tsqr-linear-algebra/9849/2) someone recommended [`Elemental.jl`](https://github.com/JuliaParallel/Elemental.jl) in this forum a few years ago - is that the best choice? Are there others?

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**Author:** ![goerch](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/goerch/32/29122_2.png) [@goerch](https://discourse.julialang.org/u/goerch)\
**Post date:** [March 22, 2022, 10:18am UTC](https://discourse.julialang.org/t/options-for-large-scale-dense-linear-algebra/78227/2 "2022-03-22T10:18:06Z")

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[ScaLAPACK](http://www.netlib.org/scalapack/) or [PLAPACK](https://www.cs.utexas.edu/users/plapack/)? You’d need to interface with `@ccall`, however (and this is exactly what `ScaLAPACK.jl` tries (tried?) to do).