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Moved CI to GitHub Actions
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‎.github/workflows/main.yml‎

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name: julia 1.0/1.3
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on:
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- push
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- pull_request
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jobs:
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testMKLjl:
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name: Julia ${{ matrix.version }} - ${{ matrix.os }} - ${{ matrix.arch }}
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runs-on: ${{ matrix.os }}
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strategy:
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fail-fast: false
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matrix:
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version:
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- '1.0'
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- '1.3'
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os:
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- ubuntu-latest
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- macOS-latest
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# - windows-latest
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arch:
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- x64
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steps:
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- uses: actions/checkout@v2
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- uses: julia-actions/setup-julia@v1
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with:
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version: ${{ matrix.version }}
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arch: ${{ matrix.arch }}
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- run: julia --color=yes --project -e 'using Pkg; Pkg.add(PackageSpec(url=\"https://github.com/JuliaComputing/MKL.jl\")); Pkg.instantiate()'
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if: matrix.os == 'windows-latest'
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- run: julia --color=yes --project -e 'using Pkg; Pkg.add(PackageSpec(url="https://github.com/JuliaComputing/MKL.jl")); Pkg.instantiate()'
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if: matrix.os != 'windows-latest'
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- uses: julia-actions/julia-buildpkg@latest
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- uses: julia-actions/julia-runtest@latest
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testAptMKL:
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name: Julia ${{ matrix.version }} - ${{ matrix.os }} - ${{ matrix.arch }}
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runs-on: ${{ matrix.os }}
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strategy:
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matrix:
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version:
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- '1.0'
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- '1.3'
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os:
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- ubuntu-latest
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arch:
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- x64
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env:
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LD_LIBRARY_PATH: /opt/intel/compilers_and_libraries_2019.4.243/linux/mkl/lib/intel64_lin/
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steps:
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- name: Install MKL via apt
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run: |
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curl https://apt.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS-2019.PUB > GPG-PUB-KEY-INTEL-SW-PRODUCTS-2019.PUB
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sudo apt-key add GPG-PUB-KEY-INTEL-SW-PRODUCTS-2019.PUB
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rm GPG-PUB-KEY-INTEL-SW-PRODUCTS-2019.PUB
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sudo sh -c 'echo deb https://apt.repos.intel.com/mkl all main > /etc/apt/sources.list.d/intel-mkl.list'
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sudo apt-get update
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sudo apt-get install -y intel-mkl-64bit-2019.4-070
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- uses: actions/checkout@v2
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- uses: julia-actions/setup-julia@v1
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with:
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version: ${{ matrix.version }}
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arch: ${{ matrix.arch }}
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- uses: julia-actions/julia-buildpkg@latest
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- uses: julia-actions/julia-runtest@latest

‎.github/workflows/nightly.yml‎

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name: julia nightly
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on:
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push:
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pull_request:
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schedule:
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- cron: '1 0 1,15 * *'
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jobs:
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testMKLjl:
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name: Julia ${{ matrix.version }} - ${{ matrix.os }} - ${{ matrix.arch }}
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runs-on: ${{ matrix.os }}
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strategy:
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fail-fast: false
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matrix:
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version:
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- 'nightly'
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os:
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- ubuntu-latest
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- macOS-latest
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# - windows-latest
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arch:
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- x64
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steps:
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- uses: actions/checkout@v2
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- uses: julia-actions/setup-julia@v1
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with:
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version: ${{ matrix.version }}
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arch: ${{ matrix.arch }}
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- run: julia --color=yes --project -e 'using Pkg; Pkg.add(PackageSpec(url=\"https://github.com/JuliaComputing/MKL.jl\")); Pkg.instantiate()'
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if: matrix.os == 'windows-latest'
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- run: julia --color=yes --project -e 'using Pkg; Pkg.add(PackageSpec(url="https://github.com/JuliaComputing/MKL.jl")); Pkg.instantiate()'
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if: matrix.os != 'windows-latest'
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- uses: julia-actions/julia-buildpkg@latest
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- uses: julia-actions/julia-runtest@latest
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testAptMKL:
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name: Julia ${{ matrix.version }} - ${{ matrix.os }} - ${{ matrix.arch }}
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runs-on: ${{ matrix.os }}
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strategy:
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matrix:
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version:
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- 'nightly'
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os:
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- ubuntu-latest
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arch:
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- x64
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env:
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LD_LIBRARY_PATH: /opt/intel/compilers_and_libraries_2019.4.243/linux/mkl/lib/intel64_lin/
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steps:
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- name: Install MKL via apt
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run: |
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curl https://apt.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS-2019.PUB > GPG-PUB-KEY-INTEL-SW-PRODUCTS-2019.PUB
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sudo apt-key add GPG-PUB-KEY-INTEL-SW-PRODUCTS-2019.PUB
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rm GPG-PUB-KEY-INTEL-SW-PRODUCTS-2019.PUB
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sudo sh -c 'echo deb https://apt.repos.intel.com/mkl all main > /etc/apt/sources.list.d/intel-mkl.list'
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sudo apt-get update
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sudo apt-get install -y intel-mkl-64bit-2019.4-070
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source /opt/intel/mkl/bin/mklvars.sh intel64
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- uses: actions/checkout@v2
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- uses: julia-actions/setup-julia@v1
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with:
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version: ${{ matrix.version }}
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arch: ${{ matrix.arch }}
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- uses: julia-actions/julia-buildpkg@latest
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- uses: julia-actions/julia-runtest@latest

‎.travis.yml‎

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‎README.md‎

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# IntelVectorMath.jl (formerly VML.jl)
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[![Build Status](https://travis-ci.com/JuliaMath/IntelVectorMath.jl.svg?branch=master)](https://travis-ci.com/JuliaMath/IntelVectorMath.jl)
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[![Build status](https://ci.appveyor.com/api/projects/status/btdduqfsxux8fhsr?svg=true)](https://ci.appveyor.com/project/Crown421/IntelVectorMath-jl)
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![](https://github.com/JuliaMath/VML.jl/workflows/julia%201.0/1.3/badge.svg)
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![](https://github.com/JuliaMath/VML.jl/workflows/julia%20nightly/badge.svg)
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This package provides bindings to the Intel MKL [Vector Mathematics Functions](https://software.intel.com/en-us/node/521751).
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This is often substantially faster than broadcasting Julia's built-in functions, especially when applying a transcendental function over a large array.
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* [x] Avoiding overloading base and optional overload function
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* [x] Travis and AppVeyor testing
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* [x] Adding CIS function
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* [ ] Updating Benchmarks
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* [x] Move Testing to GitHub Actions
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* [x] Add test for using standalone MKL
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* [ ] Update Benchmarks
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* [ ] Add tests for mutating functions
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* [ ] Add test for using standalone MKL
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## Advanced
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IntelVectorMath.jl works via Libdl which loads the relevant shared libraries. Libdl automatically finds the relevant libraries if the location of the binaries has been added to the system search paths.
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This already taken care of if you use MKL.jl, but the stand-alone may require you to source `mklvars.sh`. The default command on Mac and Ubuntu is `source /opt/intel/mkl/bin/mklvars.sh intel64`. You may want to add this to your `.bashrc`.
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This already taken care of if you use MKL.jl, but the stand-alone may require you to source `mklvars.sh` in the shell you are opening the REPL in. The default command on Mac and Ubuntu is `source /opt/intel/mkl/bin/mklvars.sh intel64`. You may want to add this to your `.bashrc`.
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Adding a new `*.conf` file in `/etc/ld.so.conf.d` also works, as the `intel-mkl-slim` package in the AUR does automatically.
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Further, IntelVectorMath.jl uses [CpuId.jl](https://github.com/m-j-w/CpuId.jl) to detect if your processor supports the newer `avx2` instructions, and if not defaults to `libmkl_vml_avx`. If your system does not have AVX this package will currently not work for you.

‎appveyor.yml‎

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