{"data":{"slug":"microsoft-pai","name":"pai","tagline":"Resource scheduling and cluster management for AI","github_url":"https://github.com/microsoft/pai","owner":"microsoft","repo":"pai","owner_avatar_url":"https://avatars.githubusercontent.com/u/6154722?v=4","primary_language":"JavaScript","stars":2686,"forks":549,"topics":["ai","artificial-intelligence","chainer","cloud","cluster-management","cluster-manager","gpu","gpu-cluster","gpu-computing","gpu-scheduler","jupyter","kubernetes","machine-learning","model-training","on-premise","pytorch","resource-management","scheduling","tensorflow"],"archived":true,"github_pushed_at":"2024-06-06T07:56:07+00:00","maintenance_label":"Archived","url":"https://www.graphcanon.com/tools/microsoft-pai","markdown_url":"https://www.graphcanon.com/tools/microsoft-pai.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/microsoft-pai","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=microsoft-pai","description":"Resource scheduling and cluster management for AI","homepage_url":"https://openpai.readthedocs.io","license":"MIT","open_issues":282,"watchers":12,"ai_summary":"Provides tools and infrastructure for managing resources, clusters, and training models in AI projects, integrating well with various deep learning frameworks like TensorFlow, PyTorch, and Chainer.","readme_excerpt":"### Contributor License Agreement\n\nThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visit https://cla.microsoft.com.\n\nWhen you submit a pull request, a CLA-bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions\nprovided by the bot. You will only need to do this once across all repos using our CLA.\n\nThis project has adopted the [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/).\nFor more information see the [Code of Conduct FAQ](https://opensource.microsoft.com/codeofconduct/faq/) or\ncontact [opencode@microsoft.com](mailto:opencode@microsoft.com) with any additional questions or comments.","github_created_at":"2017-09-25T11:24:51+00:00","created_at":"2026-07-11T23:29:05.295129+00:00","updated_at":"2026-08-03T18:00:50.664295+00:00","categories":[{"slug":"inference-serving","name":"Inference & Serving","url":"https://www.graphcanon.com/categories/inference-serving","markdown_url":"https://www.graphcanon.com/categories/inference-serving.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/inference-serving"},{"slug":"model-training","name":"Model Training","url":"https://www.graphcanon.com/categories/model-training","markdown_url":"https://www.graphcanon.com/categories/model-training.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/model-training"}],"tags":[{"slug":"ai","name":"ai"},{"slug":"artificial-intelligence","name":"artificial-intelligence"},{"slug":"gpu","name":"gpu"},{"slug":"kubernetes","name":"kubernetes"},{"slug":"machine-learning","name":"machine-learning"},{"slug":"pytorch","name":"pytorch"},{"slug":"resource-management","name":"resource-management"},{"slug":"scheduling","name":"scheduling"}],"trust":{"provenance":{"is_fork":false,"github_id":104741169,"owner_type":"Organization","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-08-03T18:00:49.297Z","maintenance":{"label":"Archived","score":8,"methodology":"github_public_v1","releases_90d":0,"days_since_push":788,"last_release_at":"2021-07-16T02:45:05Z"},"security_summary":{"status":"no_lockfile","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-07-11T23:29:07.081Z","medium_count":0,"scan_profile":"none","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-08-03T18:00:49.777Z"},"languages":{"value":["javascript"],"source":"github.language","observed_at":"2026-08-03T18:00:49.777Z"},"license_spdx":{"value":"MIT","source":"github.license","observed_at":"2026-08-03T18:00:49.777Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":null,"constraints":null,"when_to_use":["When you are working with JavaScript-based projects and need to integrate model training or serving operations within your tech stack seamlessly","If your AI project requires extensive GPU computing capabilities and efficient GPU scheduling across clusters"],"when_not_to_use":["For organizations that prefer a more comprehensive suite tailored for specific languages other than JavaScript, as the tool's focus is clearly on this language environment","When looking for solutions strictly hosted in cloud environments, as pai also supports deployment in on-premise settings which could complicate decisions if cloud dependency is critical"],"source":"enrich:decision_facts","observed_at":"2026-07-17T06:11:23.625Z"},"constraint_facets":null,"decision_summary":[{"label":"Adopt for","value":"pai is an open-source solution focused on resource scheduling and cluster management that supports deep learning frameworks including TensorFlow, PyTorch, and Chainer."}]}}