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HealpixMPI.jl

HealpixMPI.jl: an MPI-parallel implementation of the Healpix tessellation scheme in Julia - Published in JOSS (2024)

https://github.com/leeobianchi/healpixmpi.jl

Science Score: 98.0%

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Repository

an MPI-parallel implementation of the Healpix tessellation scheme in Julia

Basic Info
  • Host: GitHub
  • Owner: LeeoBianchi
  • License: gpl-2.0
  • Language: Julia
  • Default Branch: main
  • Homepage:
  • Size: 1.7 MB
Statistics
  • Stars: 6
  • Watchers: 2
  • Forks: 2
  • Open Issues: 0
  • Releases: 3
Created about 3 years ago · Last pushed almost 2 years ago
Metadata Files
Readme Changelog License Citation

README.md

Codecov Build Status Dev status

HealpixMPI.jl: an MPI-parallel implementation of the Healpix tessellation scheme in Julia

Welcome to HealpixMPI.jl, an MPI-parallel implementation of the main functionalities of HEALPix spherical tessellation scheme, entirely coded in Julia.

This package constitutes a natural extension of the package Healpix.jl, providing an MPI integration of its main functionalities, allowing for simultaneous shared-memory (multithreading) and distributed-memory (MPI) parallelization leading to high performance sperical harmonic transforms.

Read the full documentation for further details.

Installation

From the Julia REPL, run

julia import Pkg Pkg.add("HealpixMPI")

Usage Example

The example shows the necessary steps to set up and perform an MPI-parallel alm2map SHT with HealpixMPI.jl.

Set up

We set up the necessary MPI communication and initialize Healpix.jl structures: ````julia using MPI using Random using Healpix using HealpixMPI

MPI set-up

MPI.Init() comm = MPI.COMMWORLD crank = MPI.Commrank(comm) csize = MPI.Comm_size(comm) root = 0

initialize Healpix structures

NSIDE = 64 lmax = 3*NSIDE - 1 if crank == root hmap = HealpixMap{Float64, RingOrder}(NSIDE) #empty map halm = Alm(lmax, lmax, randn(ComplexF64, numberOfAlms(lmax))) #random alm else hmap = nothing halm = nothing end ````

Distribution

The distributed HealpixMPI.jl data types are filled through an overload of MPI.Scatter!: ````julia

initialize empty HealpixMPI structures

dmap = DMap{RR}(comm) dalm = DAlm{RR}(comm)

fill them

MPI.Scatter!(hmap, dmap) MPI.Scatter!(halm, dalm) ````

SHT

We perform the SHT through an overload of Healpix.alm2map and, if needed, we MPI.Gather! the result in a HealpixMap:

julia alm2map!(d_alm, d_map; nthreads = 16) MPI.Gather!(d_map, h_map)

This allows the user to adjust at run time the number of threads to use, typically to be set to the number of cores of your machine.

Polarization

Since v1.0.0 HealpixMPI.jl supports polarized SHT's. There are two different ways to distribute a PolarizedHealpixMap using MPI.Scatter!, i.e. passing one or two DMap output objects respectively, as shown in the following example: julia MPI.Scatter!(h_map, out_d_pol_map) #here out_d_pol_map is a DMap object containing only the Q and U components of the input h_map MPI.Scatter!(h_map, out_d_map, out_d_pol_map) #here out_d_map contains the I component, while out_d_pol_map Q and U

Of course, the distribution of a polarized set of alms, represented in Healpix.jl by an AbstractArray{Alm{T}, 1}, works in a similar way: julia MPI.Scatter!(h_alms, out_d_pol_alms) #here both h_alms and out_d_pol_alms should only contain the E and B components MPI.Scatter!(h_alms, out_d_alm, out_d_pol_alms) #here h_alms should contain [T,E,B], shared by out_d_alm (T) and out_d_pol_alm (E and B)

This allows the SHTs to be performed on the DMap and DAlm resulting objects directly, regardless of the field being polarized or not, as long as the number of components in the two objects is matching. The functions alm2map and adjoint_alm2map will get authomatically the correct spin value for the given transform: julia alm2map!(d_alm, d_map) #spin-0 transform alm2map!(d_pol_alm, d_pol_map) #polarized transform

Run

In order to exploit MPI parallelization run the code through mpirun or mpiexec as shell $ mpiexec -n {Ntask} julia {your_script.jl}

To run a code on multiple nodes, specify a machine file machines.txt as shell $ mpiexec -machinefile machines.txt julia {your_script.jl}

How to Cite

If you make use of HealpixMPI.jl for your work, please remember to cite it properly.

In order to do so, click on the Cite this repository menu in the About section of this repository. Alternatively, use the following BibTeX entry:

@article{Bianchi_HealpixMPI_jl_an_MPI-parallel_2024, author = {Bianchi, Leo A.}, doi = {10.21105/joss.06467}, journal = {Journal of Open Source Software}, publisher = {The Open Journal}, month = may, number = {97}, pages = {6467}, title = {{HealpixMPI.jl: an MPI-parallel implementation of the Healpix tessellation scheme in Julia}}, url = {https://joss.theoj.org/papers/10.21105/joss.06467}, volume = {9}, year = {2024} }

Owner

  • Name: Leo Alessandro Bianchi
  • Login: LeeoBianchi
  • Kind: user
  • Location: Oslo, Norway
  • Company: UniMi / UiO

Computational (Astro-)Physics / Cosmology / CMB student @ University of Milan. Currently on research period @ University of Oslo

JOSS Publication

HealpixMPI.jl: an MPI-parallel implementation of the Healpix tessellation scheme in Julia
Published
May 20, 2024
DOI
Volume 9, Issue 97, Page 6467
Authors
Leo A. Bianchi ORCID
Dipartimento di Fisica Aldo Pontremoli, Università degli Studi di Milano, Milan, Italy, Institute of Theoretical Astrophysics, University of Oslo, Blindern, Oslo, Norway
Editor
Prashant Jha ORCID
Tags
SHT Healpix parallel computing cosmology
View PDF Review Thread Software Archive

Citation (CITATION.cff) 

cff-version: "1.2.0"
authors:
- family-names: Bianchi
  given-names: Leo A.
  orcid: "https://orcid.org/0009-0002-6351-5426"
doi: 10.5281/zenodo.11192548
message: If you use this software, please cite our article in the
  Journal of Open Source Software.
preferred-citation:
  authors:
  - family-names: Bianchi
    given-names: Leo A.
    orcid: "https://orcid.org/0009-0002-6351-5426"
  date-published: 2024-05-20
  doi: 10.21105/joss.06467
  issn: 2475-9066
  issue: 97
  journal: Journal of Open Source Software
  publisher:
    name: Open Journals
  start: 6467
  title: "HealpixMPI.jl: an MPI-parallel implementation of the Healpix
    tessellation scheme in Julia"
  type: article
  url: "https://joss.theoj.org/papers/10.21105/joss.06467"
  volume: 9
title: "HealpixMPI.jl: an MPI-parallel implementation of the Healpix
  tessellation scheme in Julia"

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juliahub.com: HealpixMPI

an MPI-parallel implementation of the Healpix tessellation scheme in Julia

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