Metadata revisions for cuda-0.10.1.0

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No. Time User Changes
-r1 Mon Apr 29 16:40:50 UTC 2019 TrevorMcDonell
  • Changed description from

    The CUDA library provides a direct, general purpose C-like SPMD programming
    model for NVIDIA graphics cards (G8x series onwards). This is a collection
    of bindings to allow you to call and control, although not write, such
    functions from Haskell-land. You will need to install the CUDA driver and
    developer toolkit.
    
    <http://developer.nvidia.com/cuda-downloads>
    
    The setup script will look for your CUDA installation by checking, in the
    following order:
    
    1. The @CUDA_PATH@ environment variable
    
    2. Searching for @nvcc@ on the @PATH@
    
    3. Checking at @\/usr\/local\/cuda@
    
    4. @CUDA_PATH_Vx_y@ environment variable, for recent CUDA toolkit versions x.y
    
    This library provides bindings to both the CUDA Driver and Runtime APIs. To
    get started, see one of:
    
    * "Foreign.CUDA.Driver" (a short tutorial is available here)
    
    * "Foreign.CUDA.Runtime"
    
    Tested with library versions up to CUDA-9.2. See also the
    <https://travis-ci.org/tmcdonell/cuda travis-ci.org> build matrix for
    version compatibility.
    
    [/NOTES:/]
    
    The setup script for this package requires at least Cabal-1.24. To upgrade,
    execute one of:
    
    * cabal users: @cabal install Cabal --constraint="Cabal >= 1.24"@
    
    * stack users: @stack setup --upgrade-cabal@
    
    Due to an interaction between GHC-8 and unified virtual address spaces in
    CUDA, this package does not currently work with GHCi on ghc-8.0.1 (compiled
    programs should work). See the following for more details:
    
    * <https://github.com/tmcdonell/cuda/issues/39>
    
    * <https://ghc.haskell.org/trac/ghc/ticket/12573>
    
    The bug should be fixed in ghc-8.0.2 and beyond.
    
    For additional notes on installing on Windows, see:
    
    * <https://github.com/tmcdonell/cuda/blob/master/WINDOWS.md>
    
    to
    The CUDA library provides a direct, general purpose C-like SPMD programming
    model for NVIDIA graphics cards (G8x series onwards). This is a collection
    of bindings to allow you to call and control, although not write, such
    functions from Haskell-land. You will need to install the CUDA driver and
    developer toolkit.
    
    <http://developer.nvidia.com/cuda-downloads>
    
    The setup script will look for your CUDA installation by checking, in the
    following order:
    
    1. The @CUDA_PATH@ environment variable
    
    2. Searching for @nvcc@ on the @PATH@
    
    3. Checking at @\/usr\/local\/cuda@
    
    4. @CUDA_PATH_Vx_y@ environment variable, for recent CUDA toolkit versions x.y
    
    This library provides bindings to both the CUDA Driver and Runtime APIs. To
    get started, see one of:
    
    * "Foreign.CUDA.Driver" (a short tutorial is available here)
    
    * "Foreign.CUDA.Runtime"
    
    Tested with library versions up to CUDA-10.1. See also the
    <https://travis-ci.org/tmcdonell/cuda travis-ci.org> build matrix for
    version compatibility.
    
    [/NOTES:/]
    
    The setup script for this package requires at least Cabal-1.24. To upgrade,
    execute one of:
    
    * cabal users: @cabal install Cabal --constraint="Cabal >= 1.24"@
    
    * stack users: @stack setup --upgrade-cabal@
    
    Due to an interaction between GHC-8 and unified virtual address spaces in
    CUDA, this package does not currently work with GHCi on ghc-8.0.1 (compiled
    programs should work). See the following for more details:
    
    * <https://github.com/tmcdonell/cuda/issues/39>
    
    * <https://ghc.haskell.org/trac/ghc/ticket/12573>
    
    The bug should be fixed in ghc-8.0.2 and beyond.
    
    For additional notes on installing on Windows, see:
    
    * <https://github.com/tmcdonell/cuda/blob/master/WINDOWS.md>
    

-r0 Mon Apr 29 16:20:31 UTC 2019 TrevorMcDonell