quokka

Two-moment AMR radiation hydrodynamics (with self-gravity, particles, and chemistry) on CPUs/GPUs for astrophysics

https://github.com/quokka-astro/quokka

Science Score: 46.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
  • Academic publication links
    Links to: arxiv.org
  • Committers with academic emails
    4 of 13 committers (30.8%) from academic institutions
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (11.1%) to scientific vocabulary

Keywords

adaptive-mesh-refinement amrex astrochemistry astrophysics cuda gpu hydrodynamics particles rocm self-gravity

Keywords from Contributors

mesh yolov5s optimizer parallel interpretability pipeline-testing datacleaner data-profilers python-version-management exoplanet
Last synced: 6 months ago · JSON representation

Repository

Two-moment AMR radiation hydrodynamics (with self-gravity, particles, and chemistry) on CPUs/GPUs for astrophysics

Basic Info
Statistics
  • Stars: 53
  • Watchers: 5
  • Forks: 16
  • Open Issues: 140
  • Releases: 3
Topics
adaptive-mesh-refinement amrex astrochemistry astrophysics cuda gpu hydrodynamics particles rocm self-gravity
Created about 6 years ago · Last pushed 6 months ago
Metadata Files
Readme Contributing License Citation Codeowners

README.md

Quality Gate Status Bugs Lines of Code OpenSSF Best Practices OpenSSF Scorecard Cite AMReX yt-project Ask DeepWiki

QUOKKA

Quadrilateral, Umbra-producing, Orthogonal, Kangaroo-conserving Kode for Astrophysics!

The Quokka methods paper is now available: https://arxiv.org/abs/2110.01792

For detailed instructions on installing the code, please refer to the Quokka Documentation. You can start a Discussion for technical support, or open an Issue for any bug reports.

Quokka is a two-moment radiation hydrodynamics code that uses the piecewise-parabolic method, with AMR and subcycling in time. Runs on CPUs (MPI+vectorized) or NVIDIA GPUs (MPI+CUDA) with a single-source codebase. Written in C++17. (100% Fortran-free.)

Here is a a Kelvin-Helmholz instability simulated with Quokka on a 512x512 uniform grid:

Animated GIF of KH Instability

This is a 3D Rayleigh-Taylor instability simulated on a $256^3$ grid:

Image of 3D RT instability

Quokka also features advanced Adaptive Quokka Refinement:tm: technology:

Image of Quokka with Baby in Pouch

Dependencies

  • C++ compiler (with C++17 support)
  • CMake 3.16+
  • Python 3.8+
  • MPI library with GPU-aware support (OpenMPI, MPICH, or Cray MPI)
  • HDF5 1.10+ (serial version)
  • CUDA 11.7+ (optional, for NVIDIA GPUs)
  • ROCm 6.3+ (optional, for AMD GPUs)
  • ADIOS2 2.9+ with GPU-aware support (optional, for writing terabyte-sized or larger outputs)

Problems?

If you run into problems, please start a Discussion for technical support. If you discover a bug, please let us know by opening an Issue.

Owner

  • Name: quokka-astro
  • Login: quokka-astro
  • Kind: organization
  • Location: Australia

The home of the Quokka AMR astrophysics code.

Committers

Last synced: about 2 years ago

All Time
  • Total Commits: 1,156
  • Total Committers: 13
  • Avg Commits per committer: 88.923
  • Development Distribution Score (DDS): 0.646
Past Year
  • Commits: 170
  • Committers: 8
  • Avg Commits per committer: 21.25
  • Development Distribution Score (DDS): 0.588
Top Committers
Name Email Commits
Ben Wibking b****g@g****m 409
Benjamin Wibking b****g@a****u 397
Ben Wibking b****n@w****m 205
dependabot[bot] 4****] 48
Piyush Sharda 3****a 27
Mark Krumholz m****z@a****u 20
Neco Kriel 4****l 17
pre-commit-ci[bot] 6****] 15
ChongChong He c****9@g****m 8
Aditi 4****n 4
Ben Wibking w****1@a****u 2
ChongChong He c****4@u****u 2
Conrad Chan 8****n 2
Committer Domains (Top 20 + Academic)

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 243
  • Total pull requests: 688
  • Average time to close issues: 4 months
  • Average time to close pull requests: 13 days
  • Total issue authors: 5
  • Total pull request authors: 10
  • Average comments per issue: 1.99
  • Average comments per pull request: 4.61
  • Merged pull requests: 491
  • Bot issues: 2
  • Bot pull requests: 222
Past Year
  • Issues: 113
  • Pull requests: 360
  • Average time to close issues: 26 days
  • Average time to close pull requests: 2 days
  • Issue authors: 4
  • Pull request authors: 9
  • Average comments per issue: 0.99
  • Average comments per pull request: 3.66
  • Merged pull requests: 244
  • Bot issues: 1
  • Bot pull requests: 133
Top Authors
Issue Authors
  • BenWibking (185)
  • chongchonghe (40)
  • psharda (15)
  • dependabot[bot] (2)
  • aditivijayan (1)
Pull Request Authors
  • BenWibking (254)
  • dependabot[bot] (199)
  • chongchonghe (151)
  • psharda (41)
  • pre-commit-ci[bot] (22)
  • aditivijayan (11)
  • AstroKriel (5)
  • lizmcole (3)
  • step-security-bot (1)
  • devin-ai-integration[bot] (1)
Top Labels
Issue Labels
enhancement (146) bug (36) CI (23) particles (15) documentation (12) MHD (10) bug: wrong answer/failure/crash (10) priority:high (9) Setonix (9) compiler bug (9) AMDGPU (7) dependencies (6) github_actions (6) bug: usability (6) floating-point (4) I/O (4) good first issue (4) hydro (3) submodules (3) lgtm (3) size:XS (2) user experience (2) viz (2) docker (1) question (1) blocking-release (1) SYCL (1) downstream (1) invalid (1) size:M (1)
Pull Request Labels
lgtm (284) dependencies (211) size:XS (156) submodules (118) github_actions (67) size:L (49) size:M (38) enhancement (33) size:S (32) particles (29) documentation (20) python (16) size:XL (14) bug (13) CI (13) do not merge (13) size:XXL (12) bug: wrong answer/failure/crash (11) docker (10) Setonix (7) AMDGPU (6) I/O (6) blocking-release (4) MHD (3) priority:high (2) bug: usability (1) viz (1) MPI bug (1) user experience (1)

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