Skip to main content

Efficient and easy Fast Fourier Transform (FFT) for Python.

Project description

This package provides C++ classes and their Python wrapper classes written in Cython useful to perform Fast Fourier Transform (FFT) with different libraries, in particular

pfft and p3dfft are specialized in computing FFT efficiently on several cores of big clusters. The data is split in pencils and can be distributed on several processes.

Fluidfft provides classes to use in a transparent way all these libraries with an unified API. These classes are not limited to just performing Fourier transforms. They are also an elegant solution to efficiently perform operations on data in real and spectral spaces (gradient, divergence, rotational, sum over wavenumbers, computation of spectra, etc.) and easily deal with the data distribution (gather the data on one process, scatter the data to many processes) without having to know the internal organization of every FFT library.

Fluidfft hides the internal complication of (distributed) FFT libraries and allows the user to find (by benchmarking) and to choose the most efficient solution for a particular case. Fluidfft is therefore a very useful tool to write HPC applications using FFT, as for example pseudo-spectral simulation codes. In particular, fluidfft is used in the Computational Fluid Dynamics (CFD) framework fluidsim.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

fluidfft-0.2.3.tar.gz (104.7 kB view details)

Uploaded Source

File details

Details for the file fluidfft-0.2.3.tar.gz.

File metadata

  • Download URL: fluidfft-0.2.3.tar.gz
  • Upload date:
  • Size: 104.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No

File hashes

Hashes for fluidfft-0.2.3.tar.gz
Algorithm Hash digest
SHA256 66929c1e7694e025b903d21088300b4d7124732ba26fb3b844587205cb8c3940
MD5 6bc6ca640b2481b67afebaedcf994825
BLAKE2b-256 57791ba59db318b1ed361a5be70b3999b6195003adb574423ec9e6493fc81c33

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page