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15 changes: 0 additions & 15 deletions doc/build/build.md
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Expand Up @@ -250,21 +250,6 @@ Julia uses a custom fork of libuv. It is a small dependency, and can be safely b

As a high-performance numerical language, Julia should be linked to a multi-threaded BLAS and LAPACK, such as OpenBLAS or ATLAS, which will provide much better performance than the reference `libblas` implementations which may be default on some systems.

### Intel MKL

**Note:** If you are building Julia for the sole purpose of incorporating Intel MKL, it may be beneficial to first try [MKL.jl](https://github.com/JuliaComputing/MKL.jl). This package will automatically download MKL and rebuild Julia's system image against it, sidestepping the need to set up a working build environment just to add MKL functionality. MKL.jl replaces OpenBLAS with MKL for dense linear algebra functions called directly from Julia, but SuiteSparse and other C/Fortran libraries will continue to use the BLAS they were linked against at build time. If you want SuiteSparse to use MKL, you will need to build from source.

For a 64-bit architecture, the environment should be set up as follows:
```sh
# bash
source /path/to/intel/bin/compilervars.sh intel64
```
Add the following to the `Make.user` file:

USE_INTEL_MKL = 1

It is highly recommended to start with a fresh clone of the Julia repository.

## Source distributions of releases

Each pre-release and release of Julia has a "full" source distribution and a "light" source
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