accelerate-fft: FFT using the Accelerate library

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

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, but must be explicitly enabled.

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


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Versions [RSS] [faq] 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 (>=1.0 && <1.2), accelerate-llvm (>=1.0 && <1.2), accelerate-llvm-native (>=1.0 && <1.2), accelerate-llvm-ptx (>=1.0 && <1.2), base (>=4.7 && <4.11), bytestring (>=0.9), carray (>=0.1.5), cuda (>=0.5), cufft (>=0.1.2), fft (>=0.1.8), file-embed (>=0.0.10), storable-complex (>=0.2) [details]
License BSD-3-Clause
Author Manuel M T Chakravarty, Gabriele Keller, Trevor L. McDonell, Robert Clifton-Everest
Maintainer Trevor L. McDonell <tmcdonell@cse.unsw.edu.au>
Category Compilers/Interpreters, Concurrency, Data, Parallelism
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 1.1.0.0)
Uploaded by TrevorMcDonell at 2017-09-21T07:45:45Z
Distributions NixOS:1.3.0.0
Downloads 6461 total (46 in the last 30 days)
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Modules

[Index]

Manual Flags

NameDescriptionDefault
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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Maintainer's Corner

For package maintainers and hackage trustees

Candidates


Readme for accelerate-fft-1.1.0.0

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FFT Component for the Accelerate Array Language

Build Status Hackage

FFT library for the embedded array language Accelerate. This will use optimised backend implementations where available. For details on Accelerate, refer to the main repository.