# Computational Speed

**URL:** <https://discourse.julialang.org/t/computational-speed/22572>\
**Category:** General Usage\
**Tags:** question\
**Created:** [March 31, 2019, 10:28pm UTC](https://discourse.julialang.org/t/computational-speed/22572 "2019-03-31T22:28:37Z")\
**Posts on this page:** 1\
**Showing post:** 2

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**Author:** ![Elrod](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/elrod/32/22461_2.png) [@Elrod](https://discourse.julialang.org/u/Elrod)\
**Post date:** [March 31, 2019, 10:45pm UTC](https://discourse.julialang.org/t/computational-speed/22572/2 "2019-03-31T22:45:16Z")

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Julia uses OpenBLAS, and MATLAB uses MKL. The easiest way to use Julia with MKL is probably:

> **[GitHub - JuliaLinearAlgebra/MKL.jl: Intel MKL linear algebra backend for Julia](https://github.com/JuliaLinearAlgebra/MKL.jl)**
>
> Intel MKL linear algebra backend for Julia. Contribute to JuliaLinearAlgebra/MKL.jl development by creating an account on GitHub.

EDIT:  
BLAS is multithreaded.  
If BLAS is using 8 threads, CPU time will elapse at about 8 CPU seconds per second.

Therefore, be sure to actually time both in the same way.  
For example, simply

```julia
@time begin
   MM=rand(Float64,10000,10000)
   mmm=inv(MM)
end

```

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