Name: accelerate Version: 0.7.1.0 Cabal-version: >= 1.6 Tested-with: GHC >= 6.12.1 Build-type: Simple Synopsis: An embedded language for accelerated array processing Description: This library defines an embedded language for regular, multi-dimensional array computations with multiple backends to facilitate high-performance implementations. Currently, there are two backends: (1) an interpreter that serves as a reference implementation of the intended semantics of the language and (2) a CUDA backend generating code for CUDA-capable NVIDIA GPUs. . To use the CUDA backend, you need to have CUDA version 3.x installed. The CUDA backend still misses some features of the full language; in particular, the array operations 'replicate', 'slice', and 'foldSeg' are not yet supported. . Known bugs in this version: http://trac.haskell.org/accelerate/query?status=new&status=assigned&status=reopened&status=closed&version=0.7.1.0&order=priority . * New in 0.7.1.0: the CUDA backend and a number of scalar functions License: BSD3 License-file: LICENSE Author: Manuel M T Chakravarty, Gabriele Keller, Sean Lee, Trevor L. McDonell Maintainer: Manuel M T Chakravarty Homepage: http://www.cse.unsw.edu.au/~chak/project/accelerate/ Bug-reports: http://trac.haskell.org/accelerate Category: Compilers/Interpreters, Concurrency, Data Stability: Experimental -- Should be in the Library stanza, and only enabled for the CUDA backend, -- but Cabal does not support that. Data-dir: cubits Data-files: accelerate_cuda_extras.h accelerate_cuda_utils.h backpermute.inl fold.inl map.inl permute.inl zipWith.inl thrust/scan_safe.inl Extra-source-files: INSTALL examples/simple/DotP.hs examples/simple/Filter.hs examples/simple/Main.hs examples/simple/Makefile examples/simple/SAXPY.hs examples/simple/SMVM.hs examples/simple/Square.hs examples/simple/Sum.hs examples/simple/Time.hs examples/rasterize/RasterizeAcc.hs examples/rasterize/rasterize-test1.txt examples/rasterize/rasterize-test2.txt examples/rasterize/rasterize-test3.txt examples/rasterize/rasterize-test4.txt examples/rasterize/rasterize.hs Flag llvm Description: enable the LLVM backend (sequential) Default: False Flag cuda Description: enable the CUDA parallel backend for NVIDIA GPUs Default: True Library Build-depends: array, base == 4.*, ghc-prim, haskell98, pretty If flag(llvm) Build-depends: llvm >= 0.6.8 if flag(cuda) Build-depends: binary, bytestring, containers, cuda >= 0.2 && < 0.3, directory, fclabels, filepath, language-c >= 0.3 && < 0.4, monads-fd, transformers >= 0.2 && < 0.3, unix Exposed-modules: Data.Array.Accelerate Data.Array.Accelerate.Interpreter -- If flag(llvm) -- Exposed-modules: Data.Array.Accelerate.LLVM If flag(cuda) Exposed-modules: Data.Array.Accelerate.CUDA Other-modules: Data.Array.Accelerate.Array.Data Data.Array.Accelerate.Array.Delayed Data.Array.Accelerate.Array.Representation Data.Array.Accelerate.Array.Sugar Data.Array.Accelerate.Analysis.Type Data.Array.Accelerate.AST Data.Array.Accelerate.Debug Data.Array.Accelerate.Language Data.Array.Accelerate.Pretty Data.Array.Accelerate.Smart Data.Array.Accelerate.Tuple Data.Array.Accelerate.Type Paths_accelerate -- If flag(llvm) -- Other-modules: Data.Array.Accelerate.LLVM.CodeGen If flag(cuda) CPP-options: -DACCELERATE_CUDA_BACKEND Other-modules: Data.Array.Accelerate.CUDA.Analysis.Hash Data.Array.Accelerate.CUDA.Analysis.Launch Data.Array.Accelerate.CUDA.Array.Data Data.Array.Accelerate.CUDA.Array.Device Data.Array.Accelerate.CUDA.CodeGen.Data Data.Array.Accelerate.CUDA.CodeGen.Skeleton Data.Array.Accelerate.CUDA.CodeGen.Tuple Data.Array.Accelerate.CUDA.CodeGen.Util Data.Array.Accelerate.CUDA.CodeGen Data.Array.Accelerate.CUDA.Compile Data.Array.Accelerate.CUDA.Execute Data.Array.Accelerate.CUDA.State Ghc-options: -O2 -Wall -fno-warn-orphans -fno-warn-name-shadowing Extensions: FlexibleContexts, FlexibleInstances, ExistentialQuantification, GADTs, TypeFamilies, ScopedTypeVariables, DeriveDataTypeable, BangPatterns, PatternGuards, TypeOperators, RankNTypes source-repository head type: darcs location: http://code.haskell.org/accelerate