accelerate-blas: Numeric Linear Algebra in Accelerate

[ accelerate, bsd3, library, math ] [ Propose Tags ]

Linear systems, matrix decompositions, and other numerical computations for use in Accelerate. Most operations are implemented efficiently via FFI calls to BLAS and LAPACK

For further information refer to the main Accelerate package: http://hackage.haskell.org/package/accelerate


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Flags

Automatic Flags
NameDescriptionDefault
llvm-cpu

Enable the LLVM backend for multicore CPUs

Enabled
llvm-ptx

Enable the LLVM PTX backend for NVIDIA GPUs

Enabled

Use -f <flag> to enable a flag, or -f -<flag> to disable that flag. More info

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Versions [RSS] 0.1.0.0, 0.1.0.1, 0.2.0.0, 0.2.0.1, 0.3.0.0
Change log CHANGELOG.md
Dependencies accelerate (>=1.3), accelerate-llvm (>=1.3), accelerate-llvm-native (>=1.3), accelerate-llvm-ptx (>=1.3), base (>=4.7), blas-hs (>=0.1), bytestring (>=0.9), containers (>=0.5), cublas (>=0.3), cuda (>=0.8), file-embed (>=0.0.10), llvm-hs-pure (>=4.1), mtl (>=2.2) [details]
License BSD-3-Clause
Author Trevor L. McDonell
Maintainer Trevor L. McDonell <trevor.mcdonell@gmail.com>
Category Accelerate, Math
Source repo head: git clone https://github.com/tmcdonell/accelerate-blas
this: git clone https://github.com/tmcdonell/accelerate-blas(tag v0.3.0.0)
Uploaded by TrevorMcDonell at 2020-08-28T14:23:59Z
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Reverse Dependencies 1 direct, 0 indirect [details]
Downloads 3481 total (16 in the last 30 days)
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Readme for accelerate-blas-0.3.0.0

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henlo, my name is Theia

Numeric linear algebra in Accelerate

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Linear systems, matrix decompositions, and other numerical computations for use in Accelerate. Most operations are implemented efficiently via FFI calls to BLAS and LAPACK. For details on Accelerate, refer to the main repository.

The following build flags control whether optimised implementations are used. Note that enabling these (which is the default) will require the corresponding Accelerate backend as a dependency:

  • llvm-ptx: For NVIDIA GPUs
  • llvm-cpu: For multicore CPUs

Contributions and bug reports are welcome! Please get in touch to let us know which missing operations you would like to see added to the library. Please feel free to contact me through GitHub or gitter.im.