{"id":16668446,"url":"https://github.com/ekzhang/archax","last_synced_at":"2025-06-22T00:40:56.283Z","repository":{"id":107896612,"uuid":"542369827","full_name":"ekzhang/archax","owner":"ekzhang","description":"Experiments in multi-architecture parallelism for deep learning with JAX","archived":false,"fork":false,"pushed_at":"2022-12-11T02:24:00.000Z","size":1493,"stargazers_count":3,"open_issues_count":0,"forks_count":0,"subscribers_count":2,"default_branch":"main","last_synced_at":"2025-03-13T00:19:27.265Z","etag":null,"topics":["cpu","gpu","jax","machine-learning","ml","parallelism","pipeline","tpu"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/ekzhang.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2022-09-28T02:13:29.000Z","updated_at":"2023-04-01T18:42:33.000Z","dependencies_parsed_at":"2023-03-24T02:03:21.372Z","dependency_job_id":null,"html_url":"https://github.com/ekzhang/archax","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/ekzhang/archax","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ekzhang%2Farchax","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ekzhang%2Farchax/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ekzhang%2Farchax/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ekzhang%2Farchax/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/ekzhang","download_url":"https://codeload.github.com/ekzhang/archax/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ekzhang%2Farchax/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":261217464,"owners_count":23126258,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["cpu","gpu","jax","machine-learning","ml","parallelism","pipeline","tpu"],"created_at":"2024-10-12T11:25:20.130Z","updated_at":"2025-06-22T00:40:51.268Z","avatar_url":"https://github.com/ekzhang.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# archax\n\n**Experiments in multi-architecture parallelism for deep learning with JAX.**\n\n![Example JAX computation graph](https://gist.githubusercontent.com/ekzhang/146eb9d1a09fd264da9f6a177e970146/raw/a8165a2a1e1da4a7b6a75eccb89f75cf191430c8/optimized_hlo.svg)\n\nWhat if we could create a new kind of multi-architecture parallelism library for deep learning compilers, supporting expressive frontends like JAX? This would optimize a mix of pipeline and operator parallelism on accelerated devices. Use both CPU, GPU, and/or TPU in the same program, and automatically interleave between them.\n\nExperiments are given in this repository, dated and annotated with brief descriptions.\n\n## License\n\nAll code and notebooks in this repository are distributed under the terms of the [MIT](https://spdx.org/licenses/MIT.html) license.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fekzhang%2Farchax","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fekzhang%2Farchax","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fekzhang%2Farchax/lists"}