https://github.com/project-codeflare/codeflare
Simplifying the definition and execution, scaling and deployment of pipelines on the cloud.
Science Score: 10.0%
This score indicates how likely this project is to be science-related based on various indicators:
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○CITATION.cff file
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○codemeta.json file
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○.zenodo.json file
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○DOI references
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○Academic publication links
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✓Committers with academic emails
2 of 19 committers (10.5%) from academic institutions -
○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (14.0%) to scientific vocabulary
Keywords
Repository
Simplifying the definition and execution, scaling and deployment of pipelines on the cloud.
Basic Info
- Host: GitHub
- Owner: project-codeflare
- License: apache-2.0
- Language: Jupyter Notebook
- Default Branch: develop
- Homepage: https://codeflare.dev
- Size: 1.14 MB
Statistics
- Stars: 232
- Watchers: 4
- Forks: 38
- Open Issues: 17
- Releases: 1
Topics
Metadata Files
README.md
Simplified and efficient AI/ML on the hybrid cloud
CodeFlare provides a simple, user-friendly abstraction for developing, scaling, and managing resources for distributed AI/ML on the Hybrid Cloud platform with OpenShift Container Platform.
📦 Stack Components and Features
CodeFlare stack consists of the following main components. This project is organized as a metarepo, gathering pointers and artifacts to deploy and use the stack.
Simplified user experience: CodeFlare SDK and CLI to define, develop, and control remote distributed compute jobs and infrastructure from either a python-based environment or command-line interface
Efficient resource management: Multi-Cluster Application Dispatcher (MCAD) for queueing, resource quotas, and management of batch jobs. And Instascale for on-demand resource scaling of an OpenShift cluster
Automated and streamlined deployment: CodeFlare Operator for automating deployment and configuration of the Project CodeFlare stack
With CodeFlare stack, users automate and simplify the execution and scaling of the steps in the life cycle of model development, from data pre-processing, distributed model training, model adaptation and validation.
Through transparent integration with Ray and PyTorch frameworks, and the rich library ecosystem that run on them, CodeFlare enables data scientists to spend more time on model development and minimum time on resource deployment and scaling.
See below our stack and how to get started.
⚙️ Project CodeFlare Ecosystem
In addition to running standalone, Project CodeFlare is deployed as part of and integrated with the Open Data Hub, leveraging OpenShift Container Platform.
With OpenShift, CodeFlare can be deployed anywhere, from on-prem to cloud, and integrate easily with other cloud-native ecosystems.
🛠️ Getting Started
Learning
Watch this video for an introduction to Project CodeFlare and what the stack can do.
Quick Start
To get started using the Project CodeFlare stack, try this end-to-end example!
For more basic walk-throughs and in-depth tutorials, see our demo notebooks!
Development
See more details in any of the component repos linked above, or get started by taking a look at the project board for open tasks/issues!
Architecture
We attempt to document all architectural decisions in our ADR documents. Start here to understand the architectural details of Project CodeFlare.
🎉 Getting Involved and Contributing
Join our Slack community to get involved or ask questions.
Blog
CodeFlare related blogs are published on our Medium publication.
License
CodeFlare is an open-source project with an Apache 2.0 license.
Owner
- Name: CodeFlare
- Login: project-codeflare
- Kind: organization
- Repositories: 15
- Profile: https://github.com/project-codeflare
Scaling complex pipelines anywhere
GitHub Events
Total
- Watch event: 13
- Fork event: 1
Last Year
- Watch event: 13
- Fork event: 1
Committers
Last synced: 9 months ago
Top Committers
| Name | Commits | |
|---|---|---|
| CARLOS ANDRADE COSTA | c****t@u****m | 133 |
| Raghu Ganti | r****i@u****m | 44 |
| Yuan-Chi Chang | y****i@u****m | 38 |
| Kun-Lung Wu | k****u@K****e | 5 |
| Twinkle Jain | j****t@h****u | 5 |
| Bobbins228 | m****4@g****m | 5 |
| dmatch01 | d****1 | 2 |
| Kun-Lung Wu | k****u@u****m | 2 |
| msrivats@us.ibm.com | m****m@m****e | 2 |
| Daniele Zonca | d****a@r****m | 1 |
| DHAVAL PATEL | d****r@g****m | 1 |
| Erik Erlandson | e****s@r****m | 1 |
| Gray Cannon | g****2 | 1 |
| Kun-Lung Wu | k****8@g****m | 1 |
| asm582 | a****2@n****u | 1 |
| aviolante | v****e@g****m | 1 |
| Twinkle Jain | T****n@i****m | 1 |
| Raghu Ganti | r****i@R****l | 1 |
| frreiss | f****s@u****m | 1 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 9 months ago
All Time
- Total issues: 25
- Total pull requests: 25
- Average time to close issues: 6 days
- Average time to close pull requests: 4 days
- Total issue authors: 8
- Total pull request authors: 16
- Average comments per issue: 1.16
- Average comments per pull request: 0.28
- Merged pull requests: 21
- 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: N/A
- Issue authors: 0
- Pull request authors: 1
- Average comments per issue: 0
- Average comments per pull request: 0.0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- raghukiran1224 (15)
- asm582 (4)
- pmoogi-redhat (1)
- sroecker (1)
- cmisale (1)
- KastanDay (1)
- dmatch01 (1)
- klwuibm (1)
Pull Request Authors
- yuanchi2807 (4)
- raghukiran1224 (3)
- chcost (3)
- miyadav (2)
- JainTwinkle (2)
- dmatch01 (2)
- asm582 (1)
- danielezonca (1)
- aviolante (1)
- larsks (1)
- Bobbins228 (1)
- gfcannon12 (1)
- klwuibm (1)
- sroecker (1)
- DhavalRepo18 (1)
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 1
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Total downloads:
- pypi 85 last-month
- Total docker downloads: 28
- Total dependent packages: 0
- Total dependent repositories: 9
- Total versions: 3
- Total maintainers: 1
pypi.org: codeflare
Codeflare pipelines
- Homepage: https://github.com/project-codeflare/codeflare
- Documentation: https://codeflare.readthedocs.io/
- License: Apache v2.0
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Latest release: 0.1.2.dev0
published over 4 years ago
Rankings
Maintainers (1)
Dependencies
- autodoc *
- numpy *
- numpydoc *
- pandas *
- pickle5 *
- ray *
- recommonmark >=0.6.0
- scikit-learn *
- sklearn *
- sphinx >=1.8
- sphinx-markdown-tables *
- sphinx-version-warning *
- sphinx_rtd_theme *
- graphviz *
- numpy *
- pandas *
- pickle5 *
- pytest *
- ray *
- scikit-learn *
- setuptools *
- sklearn *
- ray *
- ${base_image} latest build