# Acceleration of Intel MKL on AMD Ryzen CPU's

**URL:** <https://discourse.julialang.org/t/acceleration-of-intel-mkl-on-amd-ryzen-cpus/31287>\
**Category:** Performance\
**Tags:** performance, mkl, linearalgebra\
**Created:** [November 19, 2019, 9:35pm UTC](https://discourse.julialang.org/t/acceleration-of-intel-mkl-on-amd-ryzen-cpus/31287 "2019-11-19T21:35:18Z")\
**Posts on this page:** 1\
**Showing post:** 31

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**Author:** ![aasdelat](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/aasdelat/32/45268_2.png) [@aasdelat](https://discourse.julialang.org/u/aasdelat)\
**Post date:** [April 12, 2024, 9:58pm UTC](https://discourse.julialang.org/t/acceleration-of-intel-mkl-on-amd-ryzen-cpus/31287/31 "2024-04-12T21:58:17Z")

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I want to use one aocl routine to accelerate svd on Ryzen, but this seems not to be the topic for this thread, so I have opened another one. For the interested ones:

> [@AOCL (not MKL) AMD acceleration on Ryzen CPU's](https://discourse.julialang.org/t/aocl-not-mkl-amd-acceleration-on-ryzen-cpus/112890):
>
> Hi: I am interested in calling a lapack routine, dgesvd, that makes a singular value decomposition of a matrix. The library LinearAlgebra.jl already does it, but it is a generic library that does not take full advantage of the concrete CPU you use. For Intel CPU’s, there is MKL, that can be used in Julia by means of the MKL.jl library. In order to use it, you simply import these libraries in the following order: using MKL using LinearAlgebra In this way, the library LinearAlgebra will call …

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_[View the full topic](https://discourse.julialang.org/t/acceleration-of-intel-mkl-on-amd-ryzen-cpus/31287)._