SUSE Package Hub 15 oneclick install
Install ghcaccelerate
NOTE: This oneclick installation requires that the SUSE Package Hub extension to already be enabled.
See http://packagehub.suse.com/howtouse/ for information on enabling the Package Hub extension
If the extension is not enabled, this installation will fail while trying to enable an invalid repo.
This package might depend on packages from SUSE Linux Enterprise modules. If those modules are not enabled, a package dependency error will be encountered.
SUSEPackageHub15StandardPool
Package Hub 15
Dummy repo  this will fail

ghcaccelerate
An embedded language for accelerated array processing
'Data.Array.Accelerate' defines an embedded array language for computations for
highperformance computing in Haskell. Computations on multidimensional,
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
onlinecompiled for performance  for example, using
'Data.Array.Accelerate.LLVM.PTX' it may be onthefly offloaded to the GPU.
[/Additional components/]
The following supported addons are available as separate packages.
Install them from Hackage with 'cabal install <package>'
* 'acceleratellvmnative': Backend supporting parallel execution on multicore
CPUs.
* 'acceleratellvmptx': Backend supporting parallel execution on CUDAcapable
NVIDIA GPUs. Requires a GPU with compute capability 2.0 or greater.
See the following table for supported GPUs:
<http://en.wikipedia.org/wiki/CUDA#Supported_GPUs>
* 'acceleratecuda': Backend targeting CUDAenabled NVIDIA GPUs.
Requires a GPU with compute compatibility 1.2 or greater. /NOTE: This backend
is being deprecated in favour of 'acceleratellvmptx'./
* 'accelerateexamples': Computational kernels and applications showcasing the
use of Accelerate as well as a regression test suite, supporting function and
performance testing.
* 'accelerateio': Fast conversions between Accelerate arrays and other array
formats (including vector and repa).
* 'acceleratefft': Discrete Fourier transforms, with FFI bindings to optimised
implementations.
* 'acceleratebignum': Fixedwidth large integer arithmetic.
* 'colouraccelerate': Colour representations in Accelerate (RGB, sRGB, HSV,
and HSL).
* 'glossaccelerate': Generate gloss pictures from Accelerate.
* 'glossrasteraccelerate': Parallel rendering of raster images and
animations.
* 'lensaccelerate': Lens operators for Accelerate types.
* 'linearaccelerate': Linear vector spaces in Accelerate.
* 'mwcrandomaccelerate': Generate Accelerate arrays filled with high quality
pseudorandom numbers.
[/Examples and documentation/]
Haddock documentation is included in the package
The 'accelerateexamples' 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 particlebased simulation of stable fluid flows
* An /n/body simulation of gravitational attraction between solid particles
* An implementation of the PageRank algorithm
* A simple interactive ray tracer
* A particle based simulation of stable fluid flows
* A cellular automata simulation
* A "password recovery" tool, for dictionary lookup of MD5 hashes
'luleshaccelerate' is an implementation of the Livermore Unstructured
Lagrangian Explicit Shock Hydrodynamics (LULESH) miniapp. LULESH represents a
typical hydrodynamics code such as ALE3D, but is highly simplified and
hardcoded to solve the Sedov blast problem on an unstructured hexahedron mesh.
[/Mailing list and contacts/]
* Mailing list: <acceleratehaskell'googlegroups.com> (discussion of both use
and development welcome).
* Sign up for the mailing list here:
<http://groups.google.com/group/acceleratehaskell>
* Bug reports and issue tracking:
<https://github.com/AccelerateHS/accelerate/issues> .
SUSE Package Hub 15 oneclick install
Install ghcaccelerate
NOTE: This oneclick installation requires that the SUSE Package Hub extension to already be enabled.
See http://packagehub.suse.com/howtouse/ for information on enabling the Package Hub extension
If the extension is not enabled, this installation will fail while trying to enable an invalid repo.
This package might depend on packages from SUSE Linux Enterprise modules. If those modules are not enabled, a package dependency error will be encountered.
SUSEPackageHub15StandardPool
Package Hub 15
Dummy repo  this will fail

ghcaccelerate
An embedded language for accelerated array processing
'Data.Array.Accelerate' defines an embedded array language for computations for
highperformance computing in Haskell. Computations on multidimensional,
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
onlinecompiled for performance  for example, using
'Data.Array.Accelerate.LLVM.PTX' it may be onthefly offloaded to the GPU.
[/Additional components/]
The following supported addons are available as separate packages.
Install them from Hackage with 'cabal install <package>'
* 'acceleratellvmnative': Backend supporting parallel execution on multicore
CPUs.
* 'acceleratellvmptx': Backend supporting parallel execution on CUDAcapable
NVIDIA GPUs. Requires a GPU with compute capability 2.0 or greater.
See the following table for supported GPUs:
<http://en.wikipedia.org/wiki/CUDA#Supported_GPUs>
* 'acceleratecuda': Backend targeting CUDAenabled NVIDIA GPUs.
Requires a GPU with compute compatibility 1.2 or greater. /NOTE: This backend
is being deprecated in favour of 'acceleratellvmptx'./
* 'accelerateexamples': Computational kernels and applications showcasing the
use of Accelerate as well as a regression test suite, supporting function and
performance testing.
* 'accelerateio': Fast conversions between Accelerate arrays and other array
formats (including vector and repa).
* 'acceleratefft': Discrete Fourier transforms, with FFI bindings to optimised
implementations.
* 'acceleratebignum': Fixedwidth large integer arithmetic.
* 'colouraccelerate': Colour representations in Accelerate (RGB, sRGB, HSV,
and HSL).
* 'glossaccelerate': Generate gloss pictures from Accelerate.
* 'glossrasteraccelerate': Parallel rendering of raster images and
animations.
* 'lensaccelerate': Lens operators for Accelerate types.
* 'linearaccelerate': Linear vector spaces in Accelerate.
* 'mwcrandomaccelerate': Generate Accelerate arrays filled with high quality
pseudorandom numbers.
[/Examples and documentation/]
Haddock documentation is included in the package
The 'accelerateexamples' 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 particlebased simulation of stable fluid flows
* An /n/body simulation of gravitational attraction between solid particles
* An implementation of the PageRank algorithm
* A simple interactive ray tracer
* A particle based simulation of stable fluid flows
* A cellular automata simulation
* A "password recovery" tool, for dictionary lookup of MD5 hashes
'luleshaccelerate' is an implementation of the Livermore Unstructured
Lagrangian Explicit Shock Hydrodynamics (LULESH) miniapp. LULESH represents a
typical hydrodynamics code such as ALE3D, but is highly simplified and
hardcoded to solve the Sedov blast problem on an unstructured hexahedron mesh.
[/Mailing list and contacts/]
* Mailing list: <acceleratehaskell'googlegroups.com> (discussion of both use
and development welcome).
* Sign up for the mailing list here:
<http://groups.google.com/group/acceleratehaskell>
* Bug reports and issue tracking:
<https://github.com/AccelerateHS/accelerate/issues> .