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| No. |
Time |
User |
SHA256 |
| -r1 (cuda-0.7.5.2-r1) |
2017-01-06T04:35:49Z |
TrevorMcDonell |
dd05fcdff465dcbe7252532e3b9ba481d76548611e02bc28fce734378c093dee
|
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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"
This release tested with versions 6.0, 6.5, 7.0, and 7.5 of the CUDA toolkit.
[/NOTES:/]
The setup script for this package requires at least Cabal-1.22. To upgrade,
execute one of:
* cabal users: @cabal install Cabal --constraint="Cabal >= 1.22"@
* 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.markdown>
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"
This release tested with versions 6.0, 6.5, 7.0, and 7.5 of the CUDA toolkit.
[/NOTES:/]
The setup script for this package requires at least Cabal-1.22. To upgrade,
execute one of:
* cabal users: @cabal install Cabal --constraint="Cabal >= 1.22"@
* 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.markdown>
|
| -r0 (cuda-0.7.5.2-r0) |
2017-01-06T04:30:29Z |
TrevorMcDonell |
e84346bafa7405e269d4a7f0a9f6684c7a2eedd8b8380d654acd66762eb4de81
|
|
|