accelerate-fft: FFT using the Accelerate library

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Rank-polymorphic discrete Fourier transform (DFT), computed with a fast Fourier transform (FFT) algorithm using the Accelerate library. Note that optimised implementations are available via foreign libraries (enabled by default).

Refer to the main Accelerate package for more information: http://hackage.haskell.org/package/accelerate


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Flags

Automatic Flags
NameDescriptionDefault
llvm-ptx

Use CUFFT-based implementation in the LLVM.PTX backend

Enabled
llvm-cpu

Use FFTW-based implementation in the LLVM.Native backend

Enabled

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

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Versions [RSS] 0.13.0.0, 0.14.0.0, 0.15.0.0, 0.15.1.0, 1.0.0.0, 1.1.0.0, 1.2.0.0, 1.3.0.0
Change log CHANGELOG.md
Dependencies accelerate (>=1.3), accelerate-llvm (>=1.3), accelerate-llvm-native (>=1.3), accelerate-llvm-ptx (>=1.3), base (>=4.9 && <5), bytestring (>=0.9), carray (>=0.1.5), containers (>=0.5), cuda (>=0.5), cufft (>=0.9), fft (>=0.1.8), file-embed (>=0.0.10), hashable (>=1.0), lens-accelerate (>=0.2), mtl (>=2.2), unordered-containers (>=0.2) [details]
Tested with ghc >=7.10
License BSD-3-Clause
Author The Accelerate Team
Maintainer Trevor L. McDonell <trevor.mcdonell@gmail.com>
Category Accelerate, Math
Home page https://github.com/AccelerateHS/accelerate-fft
Bug tracker https://github.com/AccelerateHS/accelerate/issues
Source repo head: git clone git://github.com/AccelerateHS/accelerate-fft.git
this: git clone git://github.com/AccelerateHS/accelerate-fft.git(tag v1.3.0.0)
Uploaded by TrevorMcDonell at 2020-08-28T14:24:10Z
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Reverse Dependencies 2 direct, 0 indirect [details]
Downloads 7341 total (32 in the last 30 days)
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Readme for accelerate-fft-1.3.0.0

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henlo, my name is Theia

FFT components for the Accelerate language

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FFT library for the embedded array language Accelerate. 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 feel free to contact me through GitHub or gitter.im.