# Julia is slower than matlab when it comes to matrix diagonalization?

**URL:** <https://discourse.julialang.org/t/julia-is-slower-than-matlab-when-it-comes-to-matrix-diagonalization/108658>\
**Category:** General Usage\
**Tags:** question, eigs, eigenvalue-problem\
**Created:** [January 11, 2024, 3:42am UTC](https://discourse.julialang.org/t/julia-is-slower-than-matlab-when-it-comes-to-matrix-diagonalization/108658 "2024-01-11T03:42:27Z")\
**Posts on this page:** 1\
**Showing post:** 15

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**Author:** ![PetrKryslUCSD](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/petrkryslucsd/32/215825_2.png) [@PetrKryslUCSD](https://discourse.julialang.org/u/PetrKryslUCSD)\
**Post date:** [January 11, 2024, 10:45pm UTC](https://discourse.julialang.org/t/julia-is-slower-than-matlab-when-it-comes-to-matrix-diagonalization/108658/15 "2024-01-11T22:45:47Z")

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I’ve had mixed success with [ArnoldiMethod](https://github.com/JuliaLinearAlgebra/ArnoldiMethod.jl/issues/114). The modes were not at all mass-orthogonal. Still not sure why.

[KrylovKit](https://github.com/Jutho/KrylovKit.jl/issues/73) does not converge at all.

As far as I know Arpack is still the only package in julia that actually works.

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