<commit_before>homepage: https://github.com/AccelerateHS/accelerate/
changelog-type: markdown
hash: b2b585e3ce482dfd6cb84cdb390a14045ab831c563462352ef8eb41f12f385ff
test-bench-deps:
  base: ! '>=4.7'
  doctest: ! '>=0.11'
  accelerate: -any
maintainer: <NAME> <<EMAIL>>
synopsis: An embedded language for accelerated array processing
changelog: ! "# Change Log\n\nNotable changes to the project will be documented in
  this file.\n\nThe format is based on [Keep a Changelog](http://keepachangelog.com/)
  and the\nproject adheres to the [Haskell Package Versioning\nPolicy (PVP)](https://pvp.haskell.org)\n\n##
  [1.2.0.0] - 2018-04-03\n### Changed\n  * Internal debugging/RTS options handling
  has been changed. Compiling this package now implies that backends are also compiled
  in debug mode (no need to set the `-fdebug` cabal flag for those packages as well).\n
  \ * Complex numbers are stored in the C-style array-of-struct representation.\n
  \ * Improve numeric handling of complex numbers.\n  * Coercions (`bitcast`) now
  occur between the underlying representation types\n  * Front-end performance improvements\n\n###
  Added\n  * Support for half-precision floating-point numbers.\n  * Support for struct-of-array-of-struct
  representations. Currently this is limited to fields of 2,3,4,8, or 16-elements
  wide.\n  * Add equivalents for `Data.Functor`, `Data.Semigroup` (ghc-8+)\n  * Add
  instances and helper functions for `Maybe` and `Either` types\n  * Add rank generalised
  versions of `take`, `drop`, `head`, `tail`, `init`, `slit`, `reverse` and `transpose`.\n
  \ * Implement counters and reporting for `-ddump-gc-stats`\n\n### Contributors\n\nSpecial
  thanks to those who contributed patches as part of this release:\n\n  * <NAME> (@tmcdonell)\n  * <NAME> (@ryanglscott)\n  * <NAME> (@Haskell-mouse)\n\n\n##
  [1.1.1.0] - 2017-09-26\n### Changed\n  * Improve and colourise the pretty-printer\n\n\n##
  [1.1.0.0] - 2017-09-21\n### Added\n  * Additional EKG monitoring hooks ([#340])\n\n
  \ * Operations from `RealFloat`\n\n### Changed\n  * Changed type of `scanl'`, `scanr'`
  to return an `Acc` tuple, rather than a\n    tuple of `Acc` arrays.\n  * Specialised
  folds `sum`, `product`, `minimum`, `maximum`, `and`, `or`,\n    `any`, `all` now
  reduce along the innermost dimension only, rather than\n    reducing all elements.
  You can recover the old behaviour by first\n    `flatten`-ing the input array.\n
  \ * Add new stencil boundary condition `function`, to apply the given function\n
  \   to out-of-bounds indices.\n\n### Fixed\n  * [#390]: Wrong number of arguments
  in printf\n\n\n## [1.0.0.0] - 2017-03-31\n  * Many API and internal changes\n  *
  Bug fixes and other enhancements\n\n\n## [0.15.1.0]\n  * Fix type of `allocateArray`\n\n\n##
  [0.15.0.0]\n  * Bug fixes and performance improvements.\n\n\n## [0.14.0.0]\n  *
  New iteration constructs.\n  * Additional Prelude-like functions.\n  * Improved
  code generation and fusion optimisation.\n  * Concurrent kernel execution in the
  CUDA backend.\n  * Bug fixes.\n\n\n## [0.13.0.0]\n  * New array fusion optimisation.\n
  \ * New foreign function interface for array and scalar expressions.\n  * Additional
  Prelude-like functions.\n  * New example programs.\n  * Bug fixes and performance
  improvements.\n\n\n## [0.12.0.0]\n  * Full sharing recovery in scalar expressions
  and array computations.\n  * Two new example applications in package `accelerate-examples`
  (both including a graphical frontend):\n    * A real-time Canny edge detection\n
  \   * An interactive fluid flow simulator\n  * Bug fixes.\n\n\n## [0.11.0.0]\n  *
  New Prelude-like functions `zip*`, `unzip*`, `fill`, `enumFrom*`, `tail`,\n    `init`,
  `drop`, `take`, `slit`, `gather*`, `scatter*`, and `shapeSize`.\n  * New simplified
  AST (in package `accelerate-backend-kit`) for backend writers\n    who want to avoid
  the complexities of the type-safe AST.\n\n\n## [0.10.0.0]\n  * Complete sharing
  recovery for scalar expressions (but currently disabled by default).\n  * Also bug
  fixes in array sharing recovery and a few new convenience functions.\n\n\n## [0.9.0.0]\n
  \ * Streaming computations\n  * Precompilation\n  * Repa-style array indices\n  *
  Additional collective operations supported by the CUDA backend: `stencil`s,\n    more
  `scan`s, rank-polymorphic `fold`, `generate`.\n  * Conversions to other array formats\n
  \ * Bug fixes\n\n\n## 0.8.1.0\n  * Bug fixes and some performance tweaks.\n\n\n##
  0.8.0.0\n  * More collective operations supported by the CUDA backend: `replicate`,\n
  \   `slice` and `foldSeg`. Frontend and interpreter support for `stencil`.\n  *
  Bug fixes.\n\n\n## [0.7.1.0]\n  * Initial release of the CUDA backend\n\n\n[1.2.0.0]:
  \         https://github.com/AccelerateHS/accelerate/compare/v1.1.0.0...v1.2.0.0\n[1.1.1.0]:
  \         https://github.com/AccelerateHS/accelerate/compare/v1.1.0.0...v1.1.1.0\n[1.1.0.0]:
  \         https://github.com/AccelerateHS/accelerate/compare/1.0.0.0...v1.1.0.0\n[1.0.0.0]:
  \         https://github.com/AccelerateHS/accelerate/compare/0.15.1.0...1.0.0.0\n[0.15.1.0]:
  \        https://github.com/AccelerateHS/accelerate/compare/0.15.0.0...0.15.1.0\n[0.15.0.0]:
  \        https://github.com/AccelerateHS/accelerate/compare/0.14.0.0...0.15.0.0\n[0.14.0.0]:
  \        https://github.com/AccelerateHS/accelerate/compare/0.13.0.0...0.14.0.0\n[0.13.0.0]:
  \        https://github.com/AccelerateHS/accelerate/compare/0.12.0.0...0.13.0.0\n[0.12.0.0]:
  \        https://github.com/AccelerateHS/accelerate/compare/0.11.0.0...0.12.0.0\n[0.11.0.0]:
  \        https://github.com/AccelerateHS/accelerate/compare/0.10.0.0...0.11.0.0\n[0.10.0.0]:
  \        https://github.com/AccelerateHS/accelerate/compare/0.9.0.0...0.10.0.0\n[0.9.0.0]:
  \         https://github.com/AccelerateHS/accelerate/compare/0_8_1_0...0.9.0.0\n[0.7.1.0]:
  \         https://github.com/AccelerateHS/accelerate/compare/0_6_0_0...0_7_1_0\n\n[#340]:
  \            https://github.com/AccelerateHS/accelerate/issues/340\n[#390]:             https://github.com/AccelerateHS/accelerate/issues/390\n\n"
basic-deps:
  exceptions: ! '>=0.6'
  bytestring: ! '>=0.10.2'
  ansi-wl-pprint: ! '>=0.6'
  unix: -any
  base: ! '>=4.7 && <4.12'
  tasty-hedgehog: ! '>=0.1'
  tasty-expected-failure: ! '>=0.11'
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  unique: -any
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  lens: ! '>=4.0'
  hashtables: ! '>=1.2.3'
  ghc-prim: -any
  cryptonite: ! '>=0.21'
  mtl: ! '>=2.0'
  hashable: ! '>=1.1'
  tasty-hunit: ! '>=0.9'
  transformers: ! '>=0.3'
  tasty: ! '>=0.11'
  deepseq: ! '>=1.3'
  half: ! '>=0.2'
  template-haskell: -any
  vector: ! '>=0.10'
  directory: ! '>=1.0'
all-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'
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- '0.13.0.3'
- '0.13.0.4'
- '0.13.0.5'
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- '0.15.0.0'
- '0.15.1.0'
- '1.0.0.0'
- '1.1.0.0'
- '1.1.1.0'
- '1.2.0.0'
author: ! '<NAME>,

  <NAME>,

  <NAME>,

  <NAME>,

  <NAME>,

  <NAME>,

  <NAME>'
latest: '1.2.0.0'
description-type: markdown
description: ! "An Embedded Language for Accelerated Array Computations\n=======================================================\n\n[![Travis](https://img.shields.io/travis/AccelerateHS/accelerate/master.svg?label=linux)](https://travis-ci.org/AccelerateHS/accelerate)\n[![AppVeyor](https://img.shields.io/appveyor/ci/tmcdonell/accelerate/master.svg?label=windows)](https://ci.appveyor.com/project/tmcdonell/accelerate)\n[![Stackage
  LTS](https://stackage.org/package/accelerate/badge/lts)](https://stackage.org/lts/package/accelerate)\n[![Stackage
  Nightly](https://stackage.org/package/accelerate/badge/nightly)](https://stackage.org/nightly/package/accelerate)\n[![Hackage](https://img.shields.io/hackage/v/accelerate.svg)](https://hackage.haskell.org/package/accelerate)\n[![Gitter](https://img.shields.io/gitter/room/nwjs/nw.js.svg)](https://gitter.im/AccelerateHS/Lobby)\n\n\n`Data.Array.Accelerate`
  defines an embedded language of array 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 are online-compiled and executed on a range of architectures.\n\nFor
  more details, see our papers:\n\n * [Accelerating Haskell Array Codes with Multicore
  GPUs][CKLM+11]\n * [Optimising Purely Functional GPU Programs][MCKL13] ([slides][MCKL13-slides])\n
  * [Embedding Foreign Code][CMCK14]\n * [Type-safe Runtime Code Generation: Accelerate
  to LLVM][MCGN15] ([slides][MCGN15-slides]) ([video][MCGN15-video])\n\nThere are
  also slides from some fairly recent presentations:\n\n * [Embedded Languages for
  High-Performance Computing in Haskell][Embedded]\n * [GPGPU Programming in Haskell
  with Accelerate][YLJ13-slides] ([video][YLJ13-video]) ([workshop][YLJ13-workshop])\n\nChapter
  6 of <NAME>'s book [Parallel and Concurrent Programming in Haskell][Mar13]
  contains a tutorial introduction to Accelerate.\n\n[Trevor's PhD thesis][Trevor-thesis]
  details the design and implementation of frontend optimisations and CUDA backend.\n\n\n**Table
  of Contents**\n\n- [An Embedded Language for Accelerated Array Computations](#an-embedded-language-for-accelerated-array-computations)\n
  \ - [A simple example](#a-simple-example)\n  - [Availability](#availability)\n  -
  [Additional components](#additional-components)\n  - [Requirements](#requirements)\n
  \ - [Documentation](#documentation)\n  - [Examples](#examples)\n  - [Mailing list
  and contacts](#mailing-list-and-contacts)\n  - [Citing Accelerate](#citing-accelerate)\n
  \ - [What's missing?](#whats-missing)\n\nA simple example\n----------------\n\nAs
  a simple example, consider the computation of a dot product of two vectors of single-precision<commit_msg>Update from Hackage at 2018-10-07T11:34:50Z<commit_after>homepage: https://github.com/AccelerateHS/accelerate/
changelog-type: markdown
hash: bb1928efe602545df4043692916ed427c959110cbd678d03c3f9c3be25d1ae88
test-bench-deps:
  base: ! '>=4.7'
  doctest: ! '>=0.11'
  accelerate: -any
maintainer: <NAME> <<EMAIL>>
synopsis: An embedded language for accelerated array processing
changelog: ! "# Change Log\n\nNotable changes to the project will be documented in
  this file.\n\nThe format is based on [Keep a Changelog](http://keepachangelog.com/)
  and the\nproject adheres to the [Haskell Package Versioning\nPolicy (PVP)](https://pvp.haskell.org)\n\n##
  [1.2.0.1] - 2018-10-06\n### Fixed\n  * Build fix for ghc-8.6\n\n## [1.2.0.0] - 2018-04-03\n###
  Changed\n  * Internal debugging/RTS options handling has been changed. Compiling
  this package now implies that backends are also compiled in debug mode (no need
  to set the `-fdebug` cabal flag for those packages as well).\n  * Complex numbers
  are stored in the C-style array-of-struct representation.\n  * Improve numeric handling
  of complex numbers.\n  * Coercions (`bitcast`) now occur between the underlying
  representation types\n  * Front-end performance improvements\n\n### Added\n  * Support
  for half-precision floating-point numbers.\n  * Support for struct-of-array-of-struct
  representations. Currently this is limited to fields of 2,3,4,8, or 16-elements
  wide.\n  * Add equivalents for `Data.Functor`, `Data.Semigroup` (ghc-8+)\n  * Add
  instances and helper functions for `Maybe` and `Either` types\n  * Add rank generalised
  versions of `take`, `drop`, `head`, `tail`, `init`, `slit`, `reverse` and `transpose`.\n
  \ * Implement counters and reporting for `-ddump-gc-stats`\n\n### Contributors\n\nSpecial
  thanks to those who contributed patches as part of this release:\n\n  * <NAME> (@tmcdonell)\n  * <NAME> (@ryanglscott)\n  * <NAME> (@Haskell-mouse)\n\n\n##
  [1.1.1.0] - 2017-09-26\n### Changed\n  * Improve and colourise the pretty-printer\n\n\n##
  [1.1.0.0] - 2017-09-21\n### Added\n  * Additional EKG monitoring hooks ([#340])\n\n
  \ * Operations from `RealFloat`\n\n### Changed\n  * Changed type of `scanl'`, `scanr'`
  to return an `Acc` tuple, rather than a\n    tuple of `Acc` arrays.\n  * Specialised
  folds `sum`, `product`, `minimum`, `maximum`, `and`, `or`,\n    `any`, `all` now
  reduce along the innermost dimension only, rather than\n    reducing all elements.
  You can recover the old behaviour by first\n    `flatten`-ing the input array.\n
  \ * Add new stencil boundary condition `function`, to apply the given function\n
  \   to out-of-bounds indices.\n\n### Fixed\n  * [#390]: Wrong number of arguments
  in printf\n\n\n## [1.0.0.0] - 2017-03-31\n  * Many API and internal changes\n  *
  Bug fixes and other enhancements\n\n\n## [0.15.1.0]\n  * Fix type of `allocateArray`\n\n\n##
  [0.15.0.0]\n  * Bug fixes and performance improvements.\n\n\n## [0.14.0.0]\n  *
  New iteration constructs.\n  * Additional Prelude-like functions.\n  * Improved
  code generation and fusion optimisation.\n  * Concurrent kernel execution in the
  CUDA backend.\n  * Bug fixes.\n\n\n## [0.13.0.0]\n  * New array fusion optimisation.\n
  \ * New foreign function interface for array and scalar expressions.\n  * Additional
  Prelude-like functions.\n  * New example programs.\n  * Bug fixes and performance
  improvements.\n\n\n## [0.12.0.0]\n  * Full sharing recovery in scalar expressions
  and array computations.\n  * Two new example applications in package `accelerate-examples`
  (both including a graphical frontend):\n    * A real-time Canny edge detection\n
  \   * An interactive fluid flow simulator\n  * Bug fixes.\n\n\n## [0.11.0.0]\n  *
  New Prelude-like functions `zip*`, `unzip*`, `fill`, `enumFrom*`, `tail`,\n    `init`,
  `drop`, `take`, `slit`, `gather*`, `scatter*`, and `shapeSize`.\n  * New simplified
  AST (in package `accelerate-backend-kit`) for backend writers\n    who want to avoid
  the complexities of the type-safe AST.\n\n\n## [0.10.0.0]\n  * Complete sharing
  recovery for scalar expressions (but currently disabled by default).\n  * Also bug
  fixes in array sharing recovery and a few new convenience functions.\n\n\n## [0.9.0.0]\n
  \ * Streaming computations\n  * Precompilation\n  * Repa-style array indices\n  *
  Additional collective operations supported by the CUDA backend: `stencil`s,\n    more
  `scan`s, rank-polymorphic `fold`, `generate`.\n  * Conversions to other array formats\n
  \ * Bug fixes\n\n\n## 0.8.1.0\n  * Bug fixes and some performance tweaks.\n\n\n##
  0.8.0.0\n  * More collective operations supported by the CUDA backend: `replicate`,\n
  \   `slice` and `foldSeg`. Frontend and interpreter support for `stencil`.\n  *
  Bug fixes.\n\n\n## [0.7.1.0]\n  * Initial release of the CUDA backend\n\n\n[1.2.0.1]:
  \         https://github.com/AccelerateHS/accelerate/compare/v1.2.0.0...v1.2.0.1\n[1.2.0.0]:
  \         https://github.com/AccelerateHS/accelerate/compare/v1.1.0.0...v1.2.0.0\n[1.1.1.0]:
  \         https://github.com/AccelerateHS/accelerate/compare/v1.1.0.0...v1.1.1.0\n[1.1.0.0]:
  \         https://github.com/AccelerateHS/accelerate/compare/1.0.0.0...v1.1.0.0\n[1.0.0.0]:
  \         https://github.com/AccelerateHS/accelerate/compare/0.15.1.0...1.0.0.0\n[0.15.1.0]:
  \        https://github.com/AccelerateHS/accelerate/compare/0.15.0.0...0.15.1.0\n[0.15.0.0]:
  \        https://github.com/AccelerateHS/accelerate/compare/0.14.0.0...0.15.0.0\n[0.14.0.0]:
  \        https://github.com/AccelerateHS/accelerate/compare/0.13.0.0...0.14.0.0\n[0.13.0.0]:
  \        https://github.com/AccelerateHS/accelerate/compare/0.12.0.0...0.13.0.0\n[0.12.0.0]:
  \        https://github.com/AccelerateHS/accelerate/compare/0.11.0.0...0.12.0.0\n[0.11.0.0]:
  \        https://github.com/AccelerateHS/accelerate/compare/0.10.0.0...0.11.0.0\n[0.10.0.0]:
  \        https://github.com/AccelerateHS/accelerate/compare/0.9.0.0...0.10.0.0\n[0.9.0.0]:
  \         https://github.com/AccelerateHS/accelerate/compare/0_8_1_0...0.9.0.0\n[0.7.1.0]:
  \         https://github.com/AccelerateHS/accelerate/compare/0_6_0_0...0_7_1_0\n\n[#340]:
  \            https://github.com/AccelerateHS/accelerate/issues/340\n[#390]:             https://github.com/AccelerateHS/accelerate/issues/390\n\n"
basic-deps:
  exceptions: ! '>=0.6'
  bytestring: ! '>=0.10.2'
  ansi-wl-pprint: ! '>=0.6'
  unix: -any
  base: ! '>=4.7 && <4.13'
  tasty-hedgehog: ! '>=0.1'
  tasty-expected-failure: ! '>=0.11'
  unordered-containers: ! '>=0.2'
  unique: -any
  filepath: ! '>=1.0'
  hedgehog: ! '>=0.5'
  constraints: ! '>=0.9'
  base-orphans: ! '>=0.3'
  containers: ! '>=0.3'
  terminal-size: ! '>=0.3'
  ansi-terminal: ! '>=0.6.2'
  lens: ! '>=4.0'
  hashtables: ! '>=1.2.3'
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  mtl: ! '>=2.0'
  hashable: ! '>=1.1'
  tasty-hunit: ! '>=0.9'
  transformers: ! '>=0.3'
  tasty: ! '>=0.11'
  deepseq: ! '>=1.3'
  half: ! '>=0.2'
  template-haskell: -any
  vector: ! '>=0.10'
  directory: ! '>=1.0'
all-versions:
- '0.4.0'
- '0.5.0.0'
- '0.6.0.0'
- '0.7.1.0'
- '0.8.0.0'
- '0.8.1.0'
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- '1.2.0.1'
author: ! '<NAME>,

  <NAME>,

  <NAME>,

  <NAME>,

  <NAME>,

  <NAME>,

  <NAME>'
latest: '1.2.0.1'
description-type: markdown
description: ! "An Embedded Language for Accelerated Array Computations\n=======================================================\n\n[![Travis](https://img.shields.io/travis/AccelerateHS/accelerate/master.svg?label=linux)](https://travis-ci.org/AccelerateHS/accelerate)\n[![AppVeyor](https://img.shields.io/appveyor/ci/tmcdonell/accelerate/master.svg?label=windows)](https://ci.appveyor.com/project/tmcdonell/accelerate)\n[![Stackage
  LTS](https://stackage.org/package/accelerate/badge/lts)](https://stackage.org/lts/package/accelerate)\n[![Stackage
  Nightly](https://stackage.org/package/accelerate/badge/nightly)](https://stackage.org/nightly/package/accelerate)\n[![Hackage](https://img.shields.io/hackage/v/accelerate.svg)](https://hackage.haskell.org/package/accelerate)\n[![Gitter](https://img.shields.io/gitter/room/nwjs/nw.js.svg)](https://gitter.im/AccelerateHS/Lobby)\n\n\n`Data.Array.Accelerate`
  defines an embedded language of array 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 are online-compiled and executed on a range of architectures.\n\nFor
  more details, see our papers:\n\n * [Accelerating Haskell Array Codes with Multicore
  GPUs][CKLM+11]\n * [Optimising Purely Functional GPU Programs][MCKL13] ([slides][MCKL13-slides])\n
  * [Embedding Foreign Code][CMCK14]\n * [Type-safe Runtime Code Generation: Accelerate
  to LLVM][MCGN15] ([slides][MCGN15-slides]) ([video][MCGN15-video])\n\nThere are
  also slides from some fairly recent presentations:\n\n * [Embedded Languages for
  High-Performance Computing in Haskell][Embedded]\n * [GPGPU Programming in Haskell
  with Accelerate][YLJ13-slides] ([video][YLJ13-video]) ([workshop][YLJ13-workshop])\n\nChapter
  6 of <NAME>'s book [Parallel and Concurrent Programming in Haskell][Mar13]
  contains a tutorial introduction to Accelerate.\n\n[Trevor's PhD thesis][Trevor-thesis]
  details the design and implementation of frontend optimisations and CUDA backend.\n\n\n**Table
  of Contents**\n\n- [An Embedded Language for Accelerated Array Computations](#an-embedded-language-for-accelerated-array-computations)\n
  \ - [A simple example](#a-simple-example)\n  - [Availability](#availability)\n  -
  [Additional components](#additional-components)\n  - [Requirements](#requirements)\n
  \ - [Documentation](#documentation)\n  - [Examples](#examples)\n  - [Mailing list
  and contacts](#mailing-list-and-contacts)\n  - [Citing Accelerate](#citing-accelerate)\n
  \ - [What's missing?](#whats-missing)\n\nA simple example\n----------------\n\nAs
  a simple example, consider the computation of a dot product of two vectors of single-precision
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