The accelerate package

[Tags: bsd3, library]

Data.Array.Accelerate defines an embedded array language for computations for high-performance computing in Haskell. Computations on multi-dimensional, regular arrays are expressed in the form of parameterised collective operations, such as maps, reductions, and permutations. These computations may then be online compiled and executed on a range of architectures.

A simple example

As a simple example, consider the computation of a dot product of two vectors of floating point numbers:

 dotp :: Acc (Vector Float) -> Acc (Vector Float) -> Acc (Scalar Float)
 dotp xs ys = fold (+) 0 (zipWith (*) xs ys)

Except for the type, this code is almost the same as the corresponding Haskell code on lists of floats. The types indicate that the computation may be online-compiled for performance - for example, using Data.Array.Accelerate.CUDA it may be on-the-fly off-loaded to the GPU.

Available backends

Currently, there are two backends:

1. An interpreter that serves as a reference implementation of the intended semantics of the language, which is included in this package.

2. A CUDA backend generating code for CUDA-capable NVIDIA GPUs:

Several experimental and/or incomplete backends also exist. If you are particularly interested in any of these, especially with helping to finish them, please contact us.

1. Cilk/ICC and OpenCL:

2. Another OpenCL backend:

3. A backend to the Repa array library:

4. An infrastructure for generating LLVM code, with backends targeting multicore CPUs and NVIDIA GPUs:

Additional components

The following support packages are available:

1. accelerate-cuda: A high-performance parallel backend targeting CUDA-enabled NVIDIA GPUs. Requires the NVIDIA CUDA SDK and, for full functionality, hardware with compute capability 1.1 or greater. See the table on Wikipedia for supported GPUs:

2. accelerate-examples: Computational kernels and applications showcasing Accelerate, as well as performance and regression tests.

3. accelerate-io: Fast conversion between Accelerate arrays and other formats, including vector and repa.

4. accelerate-fft: Computation of Discrete Fourier Transforms.

Install them from Hackage with cabal install PACKAGE

Examples and documentation

Haddock documentation is included in the package, and a tutorial is available on the GitHub wiki:

The accelerate-examples package demonstrates a range of computational kernels and several complete applications, including:

Mailing list and contacts
Hackage note

The module documentation list generated by Hackage is incorrect. The only exposed modules should be:


Dependenciesarray (>=0.3 && <0.6), base (>=4.7 && <4.9), blaze-html (>=0.5), blaze-markup (>=0.5), bytestring (>=0.9), containers (>=0.3 && <0.6), directory (>=1.0), fclabels (==2.0.*), filepath (>=1.0), ghc-prim, hashable (>=1.1 && <1.3), hashtables (>=1.0 && <1.3), mtl (>=2.0), pretty (>=1.0 && <1.2), template-haskell, text (>=0.10), unix (>=2.4), unordered-containers (==0.2.*) [details]
AuthorManuel M T Chakravarty, Robert Clifton-Everest, Gabriele Keller, Sean Lee, Ben Lever, Trevor L. McDonell, Ryan Newtown, Sean Seefried
MaintainerManuel M T Chakravarty <>
CategoryCompilers/Interpreters, Concurrency, Data, Parallelism
Home page
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Source repositorythis: git clone git:// -b release/0.15(tag
UploadedFri May 1 07:20:57 UTC 2015 by TrevorMcDonell
DistributionsLTSHaskell:, NixOS:, Stackage:
Downloads8203 total (141 in last 30 days)
0 []
StatusDocs available [build log]
Last success reported on 2015-05-01 [all 1 reports]




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