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ALCF CI bridge holds a GitHub Actions runner for the whole Aurora pipeline

Abierto
  • ¿Algo no está bien?
#663 0 comentarios 1 reacción 0 asignados Ver en GitHub

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Evaluación

Dificultad
5/5
Tiempo estimado
Más de una semana
Aptitud para principiantes
35/100
Tipo de issue
Nueva funcionalidad
Claridad
Bastante claro
Estado de actividad
Activo
Stack tecnológico
github-actions, gitlab, julia
Área
ci-cd, devops

Línea de trabajo

Start by reading .github/workflows/alcf.yml and the existing log-fetching step, then compare the push-model examples linked in the issue. The proposal spans GitHub Actions and GitLab CI, including dispatch authentication, status reporting, and cancellation behavior. Done means the bridge exits promptly, completion reports the matching pipeline result, and the final status and logs remain visible; the open design questions need resolution first.

Escrito por el modelo de indexación a partir del texto del issue.

Descripción

The ALCF bridge (.github/workflows/alcf.yml) keeps an ubuntu-latest runner alive for the entire Aurora pipeline: after triggering the mirror sync it polls GitLab every 30 s for the pipeline to appear (up to 40 min), then every 60 s until it finishes, with a 330 min timeout to cover the PBS queue wait. Since 2026-09-07 that was 81 jobs and ~3,500 runner-minutes, median 27 min per job, and at least one hit the timeout.

Minutes are free for public repos, but:

  • JuliaGPU is on the free org plan, so every sleeping bridge job holds one of the 20 concurrent job slots shared by all JuliaGPU repositories;
  • Aurora queue time counts against a GitHub Actions timeout, so a busy queue turns into a red check;
  • adopting "the newest pipeline for this SHA" is fragile, which is what needed the re-run workaround in #648.
How others do it

CUDA.jl's benchmark workflow used to wait on Buildkite the same way, and switched to a push model (JuliaGPU/CUDA.jl@7934bfd7): the last Buildkite step calls POST /repos/JuliaGPU/CUDA.jl/dispatches with a benchmarks_complete event, and Benchmark.yml runs on: repository_dispatch, only once results exist. Oceananigans does the same (pipeline-benchmarks.yml). AMDGPU.jl and Metal.jl still poll Buildkite from their Benchmark.yml (via EnricoMi/download-buildkite-artifact-action), and Metal already ran into Buildkite's API rate limit doing so.

Proposal
  1. Keep the trigger side in GitHub Actions (mirror sync, label-gated fork push, fresh pipeline via trigger token on re-run), but have it exit right away after posting a pending commit status on the head SHA, linking to the GitLab pipeline.
  2. Add a final GitLab job (when: always, on the login-node shell runner) that sends a repository_dispatch (e.g. alcf_complete, with pipeline id, SHA and status), using a fine-grained PAT scoped to oneAPI.jl stored as a masked GitLab CI/CD variable.
  3. A short workflow on: repository_dispatch fetches the GitLab job logs (as the current log step does, since the instance requires an ALCF login) and sets the final status/check run on that SHA, linking to its own run.

This frees the runner, decouples Aurora queue time from GitHub timeouts, and matches results by pipeline id instead of guessing. Since the token lives on the GitLab side, fork PRs get results too (unlike CUDA.jl, where fork PRs can't decrypt the dispatch token).

Things to sort out:

  • a pipeline that is cancelled (or whose runner dies) never runs the final job, so its status would stay pending; either accept that or add a scheduled sweep;
  • re-running the GitHub check would now mean triggering a new pipeline, close to what #648 already does;
  • whether ALCF allows outbound HTTPS to api.github.com from CI jobs (the codecov upload suggests so) and storing a GitHub PAT in GitLab variables;
  • if the ALCF GitLab is Premium, its built-in GitHub integration can post pipeline statuses natively, though that wouldn't solve log visibility.

cc @michel2323

Lenguaje dominante
Julia
Estrellas
217
Forks
37
Merge medio
17 h 9 min
PR fusionados (30 d)
28

Preparar el entorno

Este proyecto no incluye contenedor de desarrollo, Dockerfile ni guía de contribución, así que la configuración corre por tu cuenta: empieza por su README y consulta nuestra guía para la primera contribución para los pasos generales.

Primeros pasos

  1. Lee el issue completo y luego la guía de contribución del proyecto.
  2. Comenta en el issue que vas a ocuparte — evita que dos personas hagan lo mismo.
  3. Haz un fork del repositorio y trabaja en una rama.
  4. Abre un pull request que haga referencia al número del issue.

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