Science Score: 72.0%
This score indicates how likely this project is to be science-related based on various indicators:
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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
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✓Academic publication links
Links to: ieee.org -
✓Committers with academic emails
8 of 10 committers (80.0%) from academic institutions -
✓Institutional organization owner
Organization llnl has institutional domain (software.llnl.gov) -
○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (11.7%) to scientific vocabulary
Keywords
Repository
High-performance, GPU-aware communication library
Basic Info
- Host: GitHub
- Owner: LLNL
- License: other
- Language: C++
- Default Branch: master
- Homepage: https://aluminum.readthedocs.io/en/latest/
- Size: 1.37 MB
Statistics
- Stars: 86
- Watchers: 6
- Forks: 22
- Open Issues: 3
- Releases: 21
Topics
Metadata Files
README.md
Aluminum
Aluminum is a high-performance communication library for CPUs, GPUs, and other accelerator platforms. It leverages existing libraries, such as MPI, NCCL, and RCCL, plus its own infrastructure, to deliver performance and accelerator-centric communication.
Aluminum is open-source and maintained by the Lawrence Livermore National Laboratory.
If you use Aluminum, please cite our paper:
@inproceedings{dryden2018aluminum,
title={Aluminum: An Asynchronous, {GPU}-Aware Communication Library Optimized for Large-Scale Training of Deep Neural Networks on {HPC} Systems},
author={Dryden, Nikoli and Maruyama, Naoya and Moon, Tim and Benson, Tom and Yoo, Andy and Snir, Marc and Van Essen, Brian},
booktitle={Proceedings of the Workshop on Machine Learning in HPC Environments (MLHPC)},
year={2018}
}
Features
- Support for blocking and non-blocking collective and point-to-point operations
- Accelerator-centric communication
- Supported communication backends:
MPI: Uses the Message Passing Interface and supports any hardware your underlying MPI library supports.NCCL: Uses either Nvidia's NCCL library for Nvidia GPUs or AMD's RCCL library for AMD GPUs.HostTransfer: Uses MPI plus the CUDA or HIP runtime to support Nvidia or AMD GPUs without specialized libraries.
Getting Started
For full details, see the Aluminum documentation.
For basic usage examples, see the examples.
Building and Installation
Aluminum is available via Spack or can be installed manually from source.
Source builds need a recent CMake, C++ compiler (with support for C++17), MPI, and hwloc. Accelerator backends need the appropriate runtime libraries.
A basic out-of-source build can be done with
mkdir build && cd build
cmake /path/to/Aluminum/source
For full details on building, configuration, testing, and benchmarking, see the documentation.
Authors
- Nikoli Dryden
- Naoya Maruyama
- Tom Benson
- Andy Yoo
See also contributors.
License
Aluminum is licensed under the Apache License, Version 2.0. See LICENSE for details.
Owner
- Name: Lawrence Livermore National Laboratory
- Login: LLNL
- Kind: organization
- Email: github-admin@llnl.gov
- Location: Livermore, CA, USA
- Website: https://software.llnl.gov
- Twitter: LLNL_OpenSource
- Repositories: 520
- Profile: https://github.com/LLNL
For over 70 years, the Lawrence Livermore National Laboratory has applied science and technology to make the world a safer place.
Citation (CITATION.cff)
cff-version: 1.2.0
title: "Aluminum Communication Library"
message: "If you use Aluminum, please cite it as"
authors:
- family-names: Dryden
given-names: Nikoli
- family-names: Maruyama
given-names: Naoya
- family-names: Moon
given-names: Tim
- family-names: Benson
given-names: Tom
- family-names: Yoo
given-names: Andy
- family-names: Van Essen
given-names: Brian
- family-names: McNeish
given-names: Corey
- family-names: Snir
given-names: Marc
preferred-citation:
title: "Aluminum: An Asynchronous, GPU-Aware Communication Library Optimized for Large-Scale Training of Deep Neural Networks on HPC Systems"
year: "2018"
type: conference-paper
collection-title: "Proceedings of the Workshop on Machine Learning in HPC Environments"
authors:
- family-names: Dryden
given-names: Nikoli
- family-names: Maruyama
given-names: Naoya
- family-names: Moon
given-names: Tim
- family-names: Benson
given-names: Tom
- family-names: Yoo
given-names: Andy
- family-names: Snir
given-names: Marc
- family-names: Van Essen
given-names: Brian
GitHub Events
Total
- Watch event: 2
- Delete event: 2
- Issue comment event: 1
- Push event: 5
- Pull request review event: 2
- Pull request event: 4
- Fork event: 2
- Create event: 2
Last Year
- Watch event: 2
- Delete event: 2
- Issue comment event: 1
- Push event: 5
- Pull request review event: 2
- Pull request event: 4
- Fork event: 2
- Create event: 2
Committers
Last synced: 9 months ago
Top Committers
| Name | Commits | |
|---|---|---|
| Nikoli Dryden | n****n | 389 |
| Thomas R. Benson | b****1@l****v | 124 |
| Naoya Maruyama | m****3@l****v | 58 |
| Byung Suk Yoo | a****o@s****v | 19 |
| Brian C. Van Essen | v****1@l****v | 4 |
| Tim Moon | m****3@l****v | 4 |
| andy-yoo | a****o@l****v | 1 |
| NOBLES5E | a****n@m****m | 1 |
| Byung Suk Yoo | a****o@r****v | 1 |
| Byung Suk Yoo | a****o@r****v | 1 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 36
- Total pull requests: 103
- Average time to close issues: 9 months
- Average time to close pull requests: 22 days
- Total issue authors: 8
- Total pull request authors: 3
- Average comments per issue: 0.64
- Average comments per pull request: 0.18
- Merged pull requests: 99
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 0
- Pull requests: 3
- Average time to close issues: N/A
- Average time to close pull requests: about 4 hours
- Issue authors: 0
- Pull request authors: 1
- Average comments per issue: 0
- Average comments per pull request: 0.67
- Merged pull requests: 3
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- ndryden (22)
- naoyam (3)
- yurivict (3)
- benson31 (3)
- hanfluid (2)
- lxz12 (1)
- dmcdougall (1)
- tbennun (1)
Pull Request Authors
- ndryden (78)
- benson31 (32)
- NOBLES5E (2)
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 1
- Total downloads: unknown
- Total dependent packages: 3
- Total dependent repositories: 0
- Total versions: 12
- Total maintainers: 2
spack.io: aluminum
Aluminum provides a generic interface to high-performance communication libraries, with a focus on allreduce algorithms. Blocking and non- blocking algorithms and GPU-aware algorithms are supported. Aluminum also contains custom implementations of select algorithms to optimize for certain situations.
- Homepage: https://github.com/LLNL/Aluminum
- License: []
-
Latest release: 1.0.0
published almost 4 years ago
Rankings
Dependencies
- breathe ==4.35.0
- sphinx ==6.1.3
- sphinx-rtd-theme ==1.2.0