Let learned resource estimates replace dynamic sampling in anchorMC

[sawenzel]

anchorMC.sh passes --dynamic-resources unconditionally, so resource estimates learned by a pilot job could only ever be added on top of runtime sampling, never used instead of it. This adds an ALIEN_O2DPG_RESOURCES hook, mirroring the existing ALIEN_O2DPG_FILEGRAPH one.

When the variable names a file, --update-resources <file> is passed and --dynamic-resources is not. Without it the invocation is byte-for-byte what it was.

The file is the json-stat output of MC/utils/o2dpg_sim_metrics.py:

o2dpg_sim_metrics.py json-stat -p pipeline_metric_<pid>.log -o learned.json -w workflow.json
export ALIEN_O2DPG_RESOURCES=${PWD}/learned.json

Tested on the GRID

Nine anchored jobs (2024 pp apass1, run 553185, 2 TF) pinned to ALICE::CERN::CERN-SIRIUS, in three arms of three: legacy runner with dynamic sampling, new runner with dynamic sampling, and new runner with learned estimates plus early file removal. All nine returned ANCHORMC_RC=0.

With the hook set, the runner logs the injection actually taking effect — 74 MEM, 74 CPU and 46 walltime overrides, replacing the workflow's placeholder defaults:

INFO Applying learned resource estimates from: /workdir/learned.json
INFO   MEM  geomprefetch    500.0 MB -> 1203.3 MB
INFO   CPU  geomprefetch    0.000 cores -> 0.892 cores

Walltime could not distinguish the arms: the within-arm spread (617–1887 s in one arm at fixed SPLITID on one CE) is far larger than any difference between arm means (1041 / 1106 / 916 s). That is a statement about GRID variance, not about this change.

🤖 Generated with Claude Code

[github-actions]

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