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hackage.haskell.org : accelerate

Data.Array.Accelerate defines an embedded array language for 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 may then be online compiled and executed on a range of architectures. As a simple example, consider the computation of a dot product of two vectors of floating point numbers: 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 online-compiled for performance - for example, using Data.Array.Accelerate.LLVM.PTX it may be on-the-fly off-loaded to the GPU. See the Data.Array.Accelerate module for further information. The following supported add-ons are available as separate packages. Install them from Hackage with cabal install <package> accelerate-llvm-native: Backend supporting parallel execution on multicore CPUs. accelerate-llvm-ptx: Backend supporting parallel execution on CUDA-capable 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 accelerate-examples: Computational kernels and applications demonstrating the use of Accelerate. accelerate-io*: Fast conversions between Accelerate arrays and other array and data formats. accelerate-fft: Discrete Fourier transforms, with FFI bindings to optimised implementations. accelerate-blas: Numeric linear algebra, with FFI bindings to optimised implementations. accelerate-bignum: Fixed-width large integer arithmetic. containers-accelerate: Container types for use with Accelerate. hashable-accelerate: Class for types which can be converted to a hash value. colour-accelerate: Colour representations in Accelerate (RGB, sRGB, HSV, and HSL). gloss-accelerate: Generate gloss pictures from Accelerate. gloss-raster-accelerate: Parallel rendering of raster images and animations. lens-accelerate: Lens operators for Accelerate types. linear-accelerate: Linear vector spaces in Accelerate. mwc-random-accelerate: Generate Accelerate arrays filled with high quality pseudorandom numbers. Haddock documentation is included in the package The accelerate-examples package demonstrates a range of computational kernels and several complete applications, including: An implementation of the Canny edge detection algorithm Interactive Mandelbrot and Julia set generators A particle-based 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 cellular automata simulation A "password recovery" tool, for dictionary lookup of MD5 hashes lulesh-accelerate is an implementation of the Livermore Unstructured Lagrangian Explicit Shock Hydrodynamics (LULESH) mini-app. LULESH represents a typical hydrodynamics code such as ALE3D, but is highly simplified and hard-coded to solve the Sedov blast problem on an unstructured hexahedron mesh. Gitter chat: https://gitter.im/AccelerateHS/Lobby Mailing list: [email protected] (discussion of both use and development welcome). Sign up for the mailing list here: http://groups.google.com/group/accelerate-haskell Bug reports and issue tracking: https://github.com/AccelerateHS/accelerate/issues

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purl: pkg:hackage/accelerate
Keywords: accelerate, bsd3, compilers-interpreters, concurrency, data, library, parallelism, cuda, gpu, gpu-computing, hacktoberfest, haskell, llvm, parallel-computing
License: BSD-3-Clause
Latest release: over 14 years ago
First release: over 14 years ago
Dependent packages: 2
Dependent repositories: 203
Downloads: 31,892 total
Stars: 887 on GitHub
Forks: 118 on GitHub
Total Commits: 2978
Committers: 41
Average commits per author: 72.634
Development Distribution Score (DDS): 0.393
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Last synced: 11 days ago

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