hpc-orchestration

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HPC Orchestration

HPC编排

Use this skill as the repository-level execution layer above solver-specific HPC skills.
将此技能用作求解器专属HPC技能之上的仓库级执行层。

Start

开始

  1. Read
    references/cluster-operations-manual.md
    first for any end-to-end cluster workflow.
  2. Read
    references/lifecycle-manual.md
    when coordinating solver skills with orchestration stages.
  3. Read
    references/scheduler-and-parallelism.md
    when choosing scheduler directives or MPI sizing.
  4. Read
    references/slurm-launch-patterns.md
    when the main decision is how to launch work inside a Slurm allocation.
  5. Read
    references/environment-and-storage-hygiene.md
    when environment modules, scratch policy, or filesystem behavior may decide workflow reliability.
  6. Read
    references/data-transfer-and-staging.md
    when files must be synchronized, staged, archived, or verified.
  7. Read
    references/software-build-and-reproducibility.md
    when compilation, package stacks, or rebuildability are in scope.
  8. Read
    references/interactive-debugging-and-profiling.md
    when the task needs live diagnosis, scaling studies, or profiler evidence.
  9. Read
    references/remote-development-and-notebooks.md
    when VS Code Remote SSH, Jupyter, or port forwarding is involved.
  10. Read
    references/container-workflows.md
    when Apptainer or Singularity-style execution is in scope.
  11. Read
    references/public-protocol.md
    when aligning solver skills with the repository lifecycle contract.
  12. Read
    references/error-pattern-dictionary.md
    when scheduler, monitoring, or log-tracking failures occur.
  1. 对于任何端到端集群工作流,请先阅读
    references/cluster-operations-manual.md
  2. 当协调求解器技能与编排阶段时,请阅读
    references/lifecycle-manual.md
  3. 当选择调度器指令或MPI规模时,请阅读
    references/scheduler-and-parallelism.md
  4. 当主要决策是如何在Slurm分配内启动工作时,请阅读
    references/slurm-launch-patterns.md
  5. 当环境模块、临时存储策略或文件系统行为可能影响工作流可靠性时,请阅读
    references/environment-and-storage-hygiene.md
  6. 当需要同步、暂存、归档或验证文件时,请阅读
    references/data-transfer-and-staging.md
  7. 当涉及编译、包栈或可重建性时,请阅读
    references/software-build-and-reproducibility.md
  8. 当任务需要实时诊断、扩展研究或性能分析器证据时,请阅读
    references/interactive-debugging-and-profiling.md
  9. 当涉及VS Code Remote SSH、Jupyter或端口转发时,请阅读
    references/remote-development-and-notebooks.md
  10. 当涉及Apptainer或Singularity风格的执行时,请阅读
    references/container-workflows.md
  11. 当使求解器技能与仓库生命周期契约保持一致时,请阅读
    references/public-protocol.md
  12. 当出现调度器、监控或日志跟踪故障时,请阅读
    references/error-pattern-dictionary.md

Additional References

额外参考资料

Load these on demand:
  • references/tools-and-scripts.md
    for shared execution tool roles
  • references/ecosystem-roadmap.md
    for repository-wide coverage goals
  • references/legacy-template.md
    when adapting an older solver skill draft into the current format
按需加载以下内容:
  • references/tools-and-scripts.md
    :用于共享执行工具的角色说明
  • references/ecosystem-roadmap.md
    :用于仓库范围的覆盖目标
  • references/legacy-template.md
    :用于将旧版求解器技能草案适配为当前格式

Reusable Templates

可复用模板

Use
assets/templates/
when a concrete scheduler scaffold is needed:
  • slurm-basic.sh
  • slurm-array.sh
  • slurm-packed-single-node.sh
  • slurm-apptainer.sh
  • slurm-perf-report.sh
  • pbs-basic.sh
  • lsf-basic.sh
  • rsync-stage-in.sh
  • jupyter-lab-compute.sh
  • ssh-config-compute-proxy.example
当需要具体的调度器脚手架时,请使用
assets/templates/
中的内容:
  • slurm-basic.sh
  • slurm-array.sh
  • slurm-packed-single-node.sh
  • slurm-apptainer.sh
  • slurm-perf-report.sh
  • pbs-basic.sh
  • lsf-basic.sh
  • rsync-stage-in.sh
  • jupyter-lab-compute.sh
  • ssh-config-compute-proxy.example

Shared Scripts

共享脚本

Use
scripts/
for deterministic orchestration tasks:
  • hpc_job_submitter.py
  • hpc_job_monitor.py
  • hpc_log_tracker.py
  • hpc_slurm_deploy.py
对于确定性编排任务,请使用
scripts/
中的内容:
  • hpc_job_submitter.py
  • hpc_job_monitor.py
  • hpc_log_tracker.py
  • hpc_slurm_deploy.py

Guardrails

防护规则

  • Do not run heavy MPI workloads on login nodes.
  • Do not separate queue submission from runtime monitoring in a production workflow.
  • Do not resubmit unchanged failing jobs when a solver-specific error dictionary exists.
  • Do not choose core counts without a scale-based heuristic.
  • 不要在登录节点上运行重型MPI工作负载。
  • 在生产工作流中,不要将队列提交与运行时监控分离。
  • 当存在求解器专属错误字典时,不要重新提交未修改的失败作业。
  • 不要在没有基于规模的启发式方法的情况下选择核心数量。