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PencilFFTs

Fast Fourier transforms of MPI-distributed Julia arrays

https://github.com/jipolanco/pencilffts.jl

Science Score: 67.0%

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Keywords

fft high-performance-computing julia mpi

Keywords from Contributors

interpretability hack standardization meshing numerical interaction interface parallel robust numerical-methods
Last synced: 6 months ago · JSON representation ·

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Fast Fourier transforms of MPI-distributed Julia arrays

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  • Stars: 80
  • Watchers: 6
  • Forks: 7
  • Open Issues: 13
  • Releases: 44
Topics
fft high-performance-computing julia mpi
Created over 6 years ago · Last pushed 6 months ago
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Readme License Citation

README.md

PencilFFTs

Stable Dev DOI

Build Status Coverage

Fast Fourier transforms of MPI-distributed Julia arrays.

This package provides multidimensional FFTs and related transforms on MPI-distributed Julia arrays via the PencilArrays package.

The name of this package originates from the decomposition of 3D domains along two out of three dimensions, sometimes called pencil decomposition. This is illustrated by the figure below, where each coloured block is managed by a different MPI process. Typically, one wants to compute FFTs on a scalar or vector field along the three spatial dimensions. In the case of a pencil decomposition, 3D FFTs are performed one dimension at a time (along the non-decomposed direction, using a serial FFT implementation). Global data transpositions are then needed to switch from one pencil configuration to the other and perform FFTs along the other dimensions.


Pencil decomposition of 3D domains

Features

  • distributed N-dimensional FFTs of MPI-distributed Julia arrays, using the PencilArrays package;

  • FFTs and related transforms (e.g. DCTs / Chebyshev transforms) may be arbitrarily combined along different dimensions;

  • in-place and out-of-place transforms;

  • high scalability up to (at least) tens of thousands of MPI processes.

Installation

PencilFFTs can be installed using the Julia package manager:

julia> ] add PencilFFTs

Quick start

The following example shows how to apply a 3D FFT of real data over 12 MPI processes distributed on a 3 × 4 grid (same distribution as in the figure above).

```julia using MPI using PencilFFTs using Random

MPI.Init()

dims = (16, 32, 64) # input data dimensions transform = Transforms.RFFT() # apply a 3D real-to-complex FFT

Distribute 12 processes on a 3 × 4 grid.

comm = MPI.COMMWORLD # we assume MPI.Commsize(comm) == 12 proc_dims = (3, 4)

Create plan

plan = PencilFFTPlan(dims, transform, proc_dims, comm)

Allocate and initialise input data, and apply transform.

u = allocate_input(plan) rand!(u) uF = plan * u

Apply backwards transform. Note that the result is normalised.

v = plan \ uF @assert u ≈ v ```

For more details see the tutorial.

Performance

The performance of PencilFFTs is comparable to that of widely adopted MPI-based FFT libraries implemented in lower-level languages. As seen below, with its default settings, PencilFFTs generally outperforms the Fortran P3DFFT libraries.


Strong scaling of PencilFFTs

See the benchmarks section of the docs for details.

Owner

  • Name: Juan Ignacio Polanco
  • Login: jipolanco
  • Kind: user
  • Location: Grenoble, France

CNRS researcher

Citation (CITATION.cff) 

cff-version: 1.1.0
message: "If you use this software, please cite it as below."
authors:
  - family-names: Polanco
    given-names: Juan Ignacio
    affiliation: Univ Lyon, CNRS, École Centrale de Lyon, LMFA
    orcid: https://orcid.org/0000-0001-7705-753X
    website: https://jipolanco.gitlab.io
title: "PencilFFTs.jl: FFTs of MPI-distributed Julia arrays"
version: 0.12.4
doi: 10.5281/zenodo.3618781
date-released: 2021-07-30
repository-code: https://github.com/jipolanco/PencilFFTs.jl
license: MIT

GitHub Events

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Last Year
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Committers

Last synced: 9 months ago

All Time
  • Total Commits: 719
  • Total Committers: 6
  • Avg Commits per committer: 119.833
  • Development Distribution Score (DDS): 0.025
Past Year
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  • Avg Commits per committer: 2.333
  • Development Distribution Score (DDS): 0.286
Top Committers
Name Email Commits
Juan Ignacio Polanco j****c@g****m 701
github-actions[bot] 4****] 6
dependabot[bot] 4****] 4
Gregory L. Wagner g****r@g****m 3
Juan Ignacio Polanco j****o@o****u 3
François Bignonnet 1****t 2
Committer Domains (Top 20 + Academic)
oca.eu: 1

Issues and Pull Requests

Last synced: 7 months ago

All Time
  • Total issues: 25
  • Total pull requests: 50
  • Average time to close issues: 2 months
  • Average time to close pull requests: 7 days
  • Total issue authors: 11
  • Total pull request authors: 7
  • Average comments per issue: 5.56
  • Average comments per pull request: 0.88
  • Merged pull requests: 47
  • Bot issues: 0
  • Bot pull requests: 11
Past Year
  • Issues: 0
  • Pull requests: 2
  • Average time to close issues: N/A
  • Average time to close pull requests: about 5 hours
  • Issue authors: 0
  • Pull request authors: 2
  • Average comments per issue: 0
  • Average comments per pull request: 2.0
  • Merged pull requests: 2
  • Bot issues: 0
  • Bot pull requests: 1
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Top Authors
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  • glwagner (4)
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  • ali-ramadhan (1)
  • erny123 (1)
  • f-fathurrahman (1)
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  • musoke (1)
  • JuliaTagBot (1)
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Pull Request Authors
  • jipolanco (32)
  • dependabot[bot] (8)
  • github-actions[bot] (7)
  • glwagner (3)
  • fbignonnet (3)
  • matinraayai (1)
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  • Total dependent packages: 2
  • Total dependent repositories: 0
  • Total versions: 44
juliahub.com: PencilFFTs

Fast Fourier transforms of MPI-distributed Julia arrays

  • Versions: 44
  • Dependent Packages: 2
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  • Downloads: 26 Total
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Dependent repos count: 9.9%
Stargazers count: 10.0%
Average: 13.5%
Dependent packages count: 16.6%
Forks count: 17.4%
Last synced: 6 months ago

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