# The accelerate package

`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: http://hackage.haskell.org/package/accelerate-cuda

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: https://github.com/AccelerateHS/accelerate-backend-kit

2. Another OpenCL backend: https://github.com/HIPERFIT/accelerate-opencl

3. A backend to the Repa array library: https://github.com/blambo/accelerate-repa

4. An infrastructure for generating LLVM code, with backends targeting multicore CPUs and NVIDIA GPUs: https://github.com/AccelerateHS/accelerate-llvm/

*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:
http://en.wikipedia.org/wiki/CUDA#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: https://github.com/AccelerateHS/accelerate/wiki

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

An implementation of the Canny edge detection algorithm

An interactive Mandelbrot set generator

A particle-based simulation of stable fluid flows

An

*n*-body simulation of gravitational attraction between solid particlesA cellular automata simulation

A "password recovery" tool, for dictionary lookup of MD5 hashes

A simple interactive ray tracer

*Mailing list and contacts*

Mailing list: accelerate-haskell@googlegroups.com (discussion of both use and development welcome).

Sign up for the mailing list here: http://groups.google.com/group/accelerate-haskell

Bug reports and issue tracking: https://github.com/AccelerateHS/accelerate/issues

*Hackage note*

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

`Data.Array.Accelerate``Data.Array.Accelerate.Interpreter``Data.Array.Accelerate.Data.Complex`

## Properties

Versions | 0.4.0, 0.5.0.0, 0.6.0.0, 0.7.1.0, 0.8.0.0, 0.8.1.0, 0.9.0.0, 0.9.0.1, 0.10.0.0, 0.12.0.0, 0.12.1.0, 0.12.2.0, 0.13.0.0, 0.13.0.1, 0.13.0.2, 0.13.0.3, 0.13.0.4, 0.13.0.5, 0.14.0.0, 0.15.0.0, 0.15.1.0 |
---|---|

Change log | changelog.md |

Dependencies | array (>=0.3 && <0.6), base (>=4.7 && <4.10), 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] |

License | BSD3 |

Author | Manuel M T Chakravarty, Robert Clifton-Everest, Gabriele Keller, Sean Lee, Ben Lever, Trevor L. McDonell, Ryan Newtown, Sean Seefried |

Maintainer | Manuel M T Chakravarty <chak@cse.unsw.edu.au> |

Stability | Experimental |

Category | Compilers/Interpreters, Concurrency, Data, Parallelism |

Home page | https://github.com/AccelerateHS/accelerate/ |

Bug tracker | https://github.com/AccelerateHS/accelerate/issues |

Source repository | this: git clone git://github.com/AccelerateHS/accelerate.git -b release/0.15(tag 0.15.1.0) |

Uploaded | Fri May 1 07:20:57 UTC 2015 by TrevorMcDonell |

Updated | Mon Jun 6 04:36:59 UTC 2016 by TrevorMcDonell to revision 1 |

Distributions | LTSHaskell:0.15.1.0, NixOS:0.15.1.0, Stackage:0.15.1.0, Tumbleweed:0.15.1.0 |

Downloads | 9707 total (34 in the last 30 days) |

Votes | |

Status | Docs available [build log] Last success reported on 2015-05-01 [all 1 reports] |

## Modules

*Data**Array*- Data.Array.Accelerate
- Data.Array.Accelerate.AST
*Analysis*- Data.Array.Accelerate.Analysis.Match
- Data.Array.Accelerate.Analysis.Shape
- Data.Array.Accelerate.Analysis.Stencil
- Data.Array.Accelerate.Analysis.Type

*Array*- Data.Array.Accelerate.Array.Data
- Data.Array.Accelerate.Array.Representation
- Data.Array.Accelerate.Array.Sugar

*Data*- Data.Array.Accelerate.Debug
- Data.Array.Accelerate.Error
- Data.Array.Accelerate.Interpreter
- Data.Array.Accelerate.Pretty
- Data.Array.Accelerate.Smart
- Data.Array.Accelerate.Trafo
- Data.Array.Accelerate.Tuple
- Data.Array.Accelerate.Type

- Data.Array.Accelerate

[Index]

## Flags

Name | Description | Default | Type |
---|---|---|---|

debug | Enable tracing message flags. These are read from the command-line arguments, which is convenient but may cause problems interacting with the user program, so are disabled by default. The available options are: * -ddump-sharing: print sharing recovery information * -ddump-simpl-stats: dump statistics counts from the simplifier phase * -ddump-simpl-iterations: dump the program after each iteration of the simplifier * -dverbose: other, uncategorised messages | Disabled | Automatic |

more-pp | Enable HTML and Graphviz pretty printing. | Disabled | Automatic |

bounds-checks | Enable bounds checking | Enabled | Automatic |

unsafe-checks | Enable bounds checking in unsafe operations | Disabled | Automatic |

internal-checks | Enable internal consistency checks | Disabled | Automatic |

Use -f <flag> to enable a flag, or -f -<flag> to disable that flag. More info

## Downloads

- accelerate-0.15.1.0.tar.gz [browse] (Cabal source package)
- Package description (included in the package)