https://github.com/alpaka-group/cupla

C++ User interface for the Platform independent Library Alpaka :arrows_clockwise:

https://github.com/alpaka-group/cupla

Science Score: 36.0%

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
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    Found .zenodo.json file
  • DOI references
  • Academic publication links
  • Committers with academic emails
    4 of 13 committers (30.8%) from academic institutions
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (13.0%) to scientific vocabulary

Keywords from Contributors

cpp17 header-only heterogeneous-parallel-programming hip openacc openmp rocm tbb adios file-handling
Last synced: 10 months ago · JSON representation

Repository

C++ User interface for the Platform independent Library Alpaka :arrows_clockwise:

Basic Info
  • Host: GitHub
  • Owner: alpaka-group
  • License: other
  • Language: C++
  • Default Branch: dev
  • Homepage:
  • Size: 6.17 MB
Statistics
  • Stars: 39
  • Watchers: 10
  • Forks: 18
  • Open Issues: 19
  • Releases: 5
Created over 10 years ago · Last pushed almost 2 years ago
Metadata Files
Readme Changelog License

README.md

cupla - C++ User interface for the Platform Independent Library alpaka

Code Status dev

cupla Release

cupla [qχɑpˈlɑʔ] is a simple user interface for the platform independent parallel kernel acceleration library alpaka. It follows a similar concept as the NVIDIA® CUDA® API by providing a software layer to manage accelerator devices. alpaka is used as backend for cupla.

Please keep in mind that a first, "find & replace" port from CUDA to cupla(x86) will result in rather bad performance. In order to reach decent performance on x86 systems you just need to add the alpaka element level to your kernels.

(Read as: add some tiling to your CUDA kernels by letting the same thread compute a fixed number of elements (N=4..16) instead of just computing one element per thread. Also, make the number of elements in your tiling a compile-time constant and your CUDA code (N=1) will just stay with the very same performance while adding single-source performance portability for, e.g., x86 targets).

Software License

cupla is licensed under LGPLv3 or later.

For more information see LICENSE.md.

Dependencies

  • cmake 3.22.0 or higher (depends on the used alpaka version)
  • alpaka 1.0.0 or newer
    • alpaka is loaded as git subtree within cupla, see INSTALL.md

Usage

  • See our notes in INSTALL.md.
  • Checkout the guide how to port your project.
  • Checkout the tuning guide for a step further to performance portable code.
  • Checkout the interoperability guide to learn more on how to use cupla with software developed with an alpaka compatible interface.

cupla can be used as a header-only library and without the CMake build system

Contributing

Any pull request will be reviewed by a maintainer.

Thanks to all active and former contributors.

Trademarks Disclaimer

All product names and trademarks are the property of their respective owners. CUDA® is a trademark of the NVIDIA Corporation.

Owner

  • Name: alpaka
  • Login: alpaka-group
  • Kind: organization
  • Location: Dresden, Germany

Abstraction Library for Parallel Kernel Acceleration

GitHub Events

Total
  • Watch event: 1
Last Year
  • Watch event: 1

Committers

Last synced: over 1 year ago

All Time
  • Total Commits: 260
  • Total Committers: 13
  • Avg Commits per committer: 20.0
  • Development Distribution Score (DDS): 0.369
Past Year
  • Commits: 1
  • Committers: 1
  • Avg Commits per committer: 1.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
René Widera r****a@h****e 164
Third Party c****a@h****e 23
Axel Huebl a****l@p****a 13
Simeon Ehrig s****g@h****e 12
mxmlnkn m****n@g****e 11
Sergei Bastrakov s****v@g****m 8
Vincent Ridder v****r@m****e 5
Ridder r****0@h****e 5
Matthias Werner m****1@t****e 5
Matthias Werner M****1@t****e 5
Andrea Bocci a****i@c****h 4
Hauke Mewes h****s@g****m 3
Jeffrey Kelling j****g@h****e 2
Committer Domains (Top 20 + Academic)

Issues and Pull Requests

Last synced: 12 months ago

All Time
  • Total issues: 13
  • Total pull requests: 92
  • Average time to close issues: 5 months
  • Average time to close pull requests: 13 days
  • Total issue authors: 9
  • Total pull request authors: 6
  • Average comments per issue: 2.77
  • Average comments per pull request: 1.16
  • Merged pull requests: 85
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 1
  • Average time to close issues: N/A
  • Average time to close pull requests: about 2 months
  • Issue authors: 0
  • Pull request authors: 1
  • Average comments per issue: 0
  • Average comments per pull request: 1.0
  • Merged pull requests: 1
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • SimeonEhrig (3)
  • fwyzard (2)
  • ivandrodri (2)
  • psychocoderHPC (1)
  • vvolkl (1)
  • frobnitzem (1)
  • sbastrakov (1)
  • mxmlnkn (1)
  • jyoung3131 (1)
Pull Request Authors
  • psychocoderHPC (74)
  • SimeonEhrig (11)
  • tdd11235813 (4)
  • sbastrakov (3)
  • jkelling (2)
  • fwyzard (1)
Top Labels
Issue Labels
bug (5) question (4) install (3) example (1) refactoring (1) continuous integration (1) testing/CI (1)
Pull Request Labels
documentation (28) enhancement (27) bug (15) refactoring (11) testing/CI (9) continuous integration (3) example (2) warning (2) question (1) install (1)

Dependencies

alpaka/docs/requirements.txt pypi
  • Jinja2 <3.0
  • breathe ==4.16.0
  • markupsafe <2.0.0
  • pygments *
  • rst2pdf *
  • sphinx ==3.0.3
  • sphinx_rtd_theme >=0.3.1
  • sphinxcontrib.programoutput *
alpaka/script/job_generator/requirements.txt pypi
  • allpairspy ==2.5.0
  • alpaka-job-coverage >=1.2.1
  • pyaml *
  • typeguard *
  • types-PyYAML *