# Yet another failed attempt to build julia with MKL

**URL:** <https://discourse.julialang.org/t/yet-another-failed-attempt-to-build-julia-with-mkl/7327>\
**Category:** General Usage\
**Created:** [November 26, 2017, 10:48pm UTC](https://discourse.julialang.org/t/yet-another-failed-attempt-to-build-julia-with-mkl/7327 "2017-11-26T22:48:47Z")\
**Posts on this page:** 1\
**Showing post:** 6

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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:** [December 25, 2017, 12:30am UTC](https://discourse.julialang.org/t/yet-another-failed-attempt-to-build-julia-with-mkl/7327/6 "2017-12-25T00:30:43Z")

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Just to throw some older tests in here:

> [@Benchmark MATLAB & Julia for Matrix Operations](https://discourse.julialang.org/t/benchmark-matlab-julia-for-matrix-operations/2000/92):
>
> To add another datapoint, here are the results on a 32-core node on our cluster, with and without threading and comparing OpenBLAS and MKL: [https://github.com/barche/julia-blas-benchmarks/blob/master/BenchmarkResults.ipynb](https://github.com/barche/julia-blas-benchmarks/blob/master/BenchmarkResults.ipynb) I also reran the HPL linpack test, here are the results: Standard HPL OpenBLAS, 32 MPI processes on a single node: 757 Gflops Standard HPL MKL, 32 MPI processes on a single node: 788 Gflops Intel HPL MKL, 32 MPI processes on a single node: 814 Gflops Intel HPL MKL, 2 MP…

[[Album] imgur.com ![](https://global.discourse-cdn.com/julialang/original/3X/1/3/132ad823d5c63d5e31e6a57c17700c6d85f930fa.jpeg "imgur.com") ](https://imgur.com/a/rBOo8)

The biggest difference seems to be if you solve a bunch of linear systems. This is noticeable for solving stiff ODEs BTW.

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