Science Score: 77.0%
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✓CITATION.cff file
Found CITATION.cff file -
✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
✓DOI references
Found 1 DOI reference(s) in README -
✓Academic publication links
Links to: ieee.org, zenodo.org -
✓Committers with academic emails
18 of 218 committers (8.3%) from academic institutions -
○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (15.4%) to scientific vocabulary
Keywords
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Repository
CUDA programming in Julia.
Basic Info
- Host: GitHub
- Owner: JuliaGPU
- License: other
- Language: Julia
- Default Branch: master
- Homepage: https://juliagpu.org/backends/cuda/
- Size: 59.6 MB
Statistics
- Stars: 1,309
- Watchers: 19
- Forks: 248
- Open Issues: 324
- Releases: 110
Topics
Metadata Files
README.md
CUDA.jl
CUDA programming in Julia
The CUDA.jl package is the main programming interface for working with NVIDIA CUDA GPUs using Julia. It features a user-friendly array abstraction, a compiler for writing CUDA kernels in Julia, and wrappers for various CUDA libraries.
Quick start
Before all, make sure you have a recent NVIDIA driver. On Windows, also make sure you have the Visual C++ redistributable installed. You do not need to install the CUDA Toolkit.
CUDA.jl can be installed with the Julia package manager. From the Julia REPL, type ] to
enter the Pkg REPL mode and run:
pkg> add CUDA
Or, equivalently, via the Pkg API:
julia
julia> import Pkg; Pkg.add("CUDA")
For an overview of the CUDA toolchain in use, you can run the following command after importing the package:
```julia julia> using CUDA
julia> CUDA.versioninfo() ```
This may take a while, as it will precompile the package and download a suitable version of the CUDA toolkit. If your GPU is not fully supported, the above command (or any other command that initializes the toolkit) will issue a warning.
For quick testing, you can also use the juliagpu/cuda.jl container
image from the GitHub
Container Registry, which provides Julia, a precompiled version of CUDA.jl, and a matching
CUDA toolkit:
sh
docker run -it --rm --gpus=all ghcr.io/juliagpu/cuda.jl:latest # other tags available too
For more usage instructions and other information, please refer to the documentation.
Requirements
The latest development version of CUDA.jl requires Julia 1.10 or higher. If you are using an older version of Julia, you need to use a previous version of CUDA.jl. This will happen automatically when you install the package using Julia's package manager.
Note that CUDA.jl may not work with a custom build of Julia; it is recommended that you install Julia using the official binaries or juliaup.
The latest version of CUDA.jl also has certain requirements that cannot be enforced by the package manager:
- Host platform: only 64-bit Linux and Windows are supported;
- Device hardware: only NVIDIA GPUs with compute capability 3.5 (Kepler) or higher are supported;
- NVIDIA driver: a driver for CUDA 11.0 or newer is required;
- CUDA toolkit (in case you need to use your own): only CUDA toolkit 11.4 or newer are supported.
If you cannot meet these requirements, you may need to install an older version of CUDA.jl:
- CUDA.jl v5.8 is the last version with support for CUDA 11, and consequently Kepler GPUs (removed in v5.9)
- CUDA.jl v5.3 is the last version with support for PowerPC (removed in v5.4)
- CUDA.jl v4.4 is the last version with support for CUDA 11.0-11.3 (deprecated in v5.0)
- CUDA.jl v4.0 is the last version to work with CUDA 10.2 (removed in v4.1)
- CUDA.jl v3.8 is the last version to work with CUDA 10.1 (removed in v3.9)
- CUDA.jl v1.3 is the last version to work with CUDA 9-10.0 (removed in v2.0)
Supporting and Citing
Much of the software in this ecosystem was developed as part of academic research. If you would like to help support it, please star the repository as such metrics may help us secure funding in the future. If you use our software as part of your research, teaching, or other activities, we would be grateful if you could cite our work. The CITATION.bib file in the root of this repository lists the relevant papers.
Project Status
The package is tested against, and being developed for, Julia 1.10 and above. Main development and testing happens on x86 Linux, but the package is expected to work on Windows and ARM and as well.
Questions and Contributions
Usage questions can be posted on the Julia Discourse forum under the GPU domain and/or in the #gpu channel of the Julia Slack.
Contributions are very welcome, as are feature requests and suggestions. Please open an issue if you encounter any problems.
Owner
- Name: JuliaGPU
- Login: JuliaGPU
- Kind: organization
- Website: https://juliagpu.org/
- Repositories: 48
- Profile: https://github.com/JuliaGPU
GPU Computing in Julia
Citation (CITATION.bib)
% primary paper, detailing the GPU compiler and relevant aspects
@article{besard2018juliagpu,
author = {Besard, Tim and Foket, Christophe and De Sutter, Bjorn},
title = {Effective Extensible Programming: Unleashing {Julia} on {GPUs}},
journal = {IEEE Transactions on Parallel and Distributed Systems},
year = {2018},
doi = {10.1109/TPDS.2018.2872064},
ISSN = {1045-9219},
archivePrefix = {arXiv},
eprint = {1712.03112},
primaryClass = {cs.PL},
}
% specific paper on array programming for heterogeneous systems
@article{besard2019prototyping,
title = {Rapid software prototyping for heterogeneous and distributed platforms},
author = {Besard, Tim and Churavy, Valentin and Edelman, Alan and De Sutter, Bjorn},
journal = {Advances in Engineering Software},
volume = {132},
pages = {29--46},
year = {2019},
publisher = {Elsevier}
}
Committers
Last synced: 9 months ago
Top Committers
| Name | Commits | |
|---|---|---|
| Tim Besard | t****d@g****m | 5,207 |
| Mike J Innes | m****s@g****m | 180 |
| Katharine Hyatt | k****t@f****g | 163 |
| github-actions[bot] | 4****] | 162 |
| Valentin Churavy | v****y@g****m | 108 |
| Alexis Montoison | 3****n | 89 |
| Andreas Noack | a****n@g****m | 34 |
| Tim Besard | t****d@e****e | 30 |
| Pieter Verstraete | p****r@p****e | 25 |
| SimonDanisch | s****h@g****m | 21 |
| William Moses | gh@w****m | 19 |
| Dahua Lin | l****a@g****m | 18 |
| Rogerluo | r****8@g****m | 17 |
| chengchingwen | a****5@h****m | 17 |
| Mus | m****m@o****m | 15 |
| Yasser Deceukelier | y****r@u****e | 15 |
| Harmen Stoppels | h****s@g****m | 14 |
| Jutho Haegeman | j****n@u****e | 14 |
| Qin Yu | q****5@o****m | 12 |
| James Douglas | 6****z | 11 |
| Zentrik | Z****k | 11 |
| Jarrett Revels | j****s@g****m | 10 |
| Yueh-Hua Tu | a****2@g****m | 9 |
| Lucas C Wilcox | l****s@s****m | 9 |
| femtocleaner[bot] | f****] | 9 |
| Andrei Zhabinski | f****d@g****m | 9 |
| David Sanders | d****s@g****m | 9 |
| xaellison | x****n@g****m | 9 |
| marius | m****a@g****m | 8 |
| Daniel Wennberg | d****g@g****m | 8 |
| and 188 more... | ||
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 472
- Total pull requests: 938
- Average time to close issues: 11 months
- Average time to close pull requests: 15 days
- Total issue authors: 250
- Total pull request authors: 94
- Average comments per issue: 3.23
- Average comments per pull request: 2.11
- Merged pull requests: 699
- Bot issues: 0
- Bot pull requests: 61
Past Year
- Issues: 131
- Pull requests: 410
- Average time to close issues: 8 days
- Average time to close pull requests: 3 days
- Issue authors: 88
- Pull request authors: 38
- Average comments per issue: 1.61
- Average comments per pull request: 2.17
- Merged pull requests: 304
- Bot issues: 0
- Bot pull requests: 14
Top Authors
Issue Authors
- maleadt (105)
- lpawela (8)
- simonbyrne (7)
- huiyuxie (6)
- ChrisRackauckas (6)
- kmp5VT (6)
- albertomercurio (5)
- vpuri3 (5)
- vchuravy (5)
- RainerHeintzmann (4)
- CarloLucibello (4)
- avik-pal (4)
- amontoison (4)
- kshyatt (4)
- wsmoses (3)
Pull Request Authors
- maleadt (310)
- kshyatt (157)
- amontoison (76)
- github-actions[bot] (55)
- wsmoses (45)
- vchuravy (39)
- christiangnrd (19)
- Zentrik (12)
- bjarthur (8)
- lpawela (8)
- dkarrasch (7)
- nikopj (7)
- xaellison (6)
- dependabot[bot] (6)
- albertomercurio (6)
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 7
-
Total downloads:
- julia 3,961 total
-
Total dependent packages: 267
(may contain duplicates) -
Total dependent repositories: 0
(may contain duplicates) - Total versions: 380
juliahub.com: CUDA
CUDA programming in Julia.
- Homepage: https://juliagpu.org/backends/cuda/
- Documentation: https://docs.juliahub.com/General/CUDA/stable/
- License: MIT
-
Latest release: 5.8.3
published 7 months ago
Rankings
proxy.golang.org: github.com/juliagpu/cuda.jl
- Documentation: https://pkg.go.dev/github.com/juliagpu/cuda.jl#section-documentation
- License: other
-
Latest release: v5.5.2+incompatible
published over 1 year ago
Rankings
proxy.golang.org: github.com/JuliaGPU/CUDA.jl
- Documentation: https://pkg.go.dev/github.com/JuliaGPU/CUDA.jl#section-documentation
- License: other
-
Latest release: v5.8.3+incompatible
published 7 months ago
Rankings
juliahub.com: cuTENSOR
CUDA programming in Julia.
- Homepage: https://juliagpu.org/backends/cuda/
- Documentation: https://docs.juliahub.com/General/cuTENSOR/stable/
- License: MIT
-
Latest release: 2.2.3
published 10 months ago
Rankings
juliahub.com: cuDNN
CUDA programming in Julia.
- Homepage: https://juliagpu.org/backends/cuda/
- Documentation: https://docs.juliahub.com/General/cuDNN/stable/
- License: MIT
-
Latest release: 1.4.3
published 10 months ago
Rankings
juliahub.com: cuStateVec
CUDA programming in Julia.
- Homepage: https://juliagpu.org/backends/cuda/
- Documentation: https://docs.juliahub.com/General/cuStateVec/stable/
- License: MIT
-
Latest release: 1.3.3
published 10 months ago
Rankings
juliahub.com: cuTensorNet
CUDA programming in Julia.
- Homepage: https://juliagpu.org/backends/cuda/
- Documentation: https://docs.juliahub.com/General/cuTensorNet/stable/
- License: MIT
-
Latest release: 1.3.3
published 10 months ago
Rankings
Dependencies
- actions/checkout v3 composite
- julia-actions/setup-julia v1 composite
- JuliaRegistries/TagBot v1 composite
- julia 1.8-bullseye build