Examples and regression tests for the Accelerate library
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Latest commit ec20908 Oct 17, 2016 @tmcdonell tmcdonell update submodule 'travis-scripts'
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Examples programs using Accelerate

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Example programs using the Accelerate library. If you add new features to the base library or find a bug, please add a test case. The aim is for this program to evolve and be useful for both performance and regression testing.

If you have found a bug, please report it to: https://github.com/AccelerateHS/accelerate/issues


External dependencies

Installation of accelerate-examples and its dependencies requires several external packages. You may need to adjust the package names or versions slightly for your system.

  • Ubuntu/Debian (apt-get):

    • llvm-3.5-dev
    • libedit3-dev
    • libglut3-dev
    • libfftw3-dev
  • Mac OS (homebrew)

    • fftw
    • libffi
    • homebrew/versions/llvm35

If you want to use the CUDA GPU enabled backends accelerate-cuda or accelerate-llvm-ptx, you will also need to install the CUDA toolkit for your system. You can find an installer on NVIDIA's website here:


The recommend installation method is via stack. For example, to build using ghc-7.10:

ln -s stack-7.10.yaml stack.yaml        # only once
stack setup --upgrade-cabal             # only once, if using CUDA
stack install                           # or, 'stack build' to not install the executables globally

Before building, you may want to edit the stack.yaml file to change the build configuration. In particular, the flags section at the bottom can be used to enable or disable individual example programs and accelerate backends, as well as features such as monitoring and debug output.


Installing the development version via cabal is not recommended. However, if you must, here are some tips:

  • llvm-general must be installed with flag -fshared-llvm.
  • The development versions tend to depend on other development versions which will not be available on Hackage yet, so you will need to manually download those from github and add/build those yourself.

Adding new backends

Adding support for new Accelerate backends should require only a few minor additions to the cabal file and the file 'lib/ParseArgs.hs'. See that file for instructions, and/or follow the example of the CUDA backend (grep 'ACCELERATE_CUDA_BACKEND').