feat(power): per-worker prefill/decode power + role-split joules (stacked on #1574)

[arygupt]

Stacked on #1574 — review #1574 first; this PR adds per-worker breakdown on top of the cluster-wide multinode aggregation that PR lands.

Summary

Manager-requested follow-up. Adds per-worker power attribution and role-split energy metrics for disagg runs:

• workers: [{role, worker_idx, num_gpus, avg_power_w}, ...] — per-worker breakdown in the agg JSON. role ∈ prefill / decode / agg / frontend. Multi-node workers (e.g. TP=16 decode across 4 nodes) aggregate as one entry with num_gpus=16.
• prefill_avg_power_w, decode_avg_power_w — weighted per-GPU averages within each role (disagg only).
• joules_per_input_token = prefill_energy / total_input_tokens (disagg only).
• joules_per_output_token_decode = decode_energy / total_output_tokens (disagg only).

Backward compatible: existing avg_power_w, joules_per_output_token, joules_per_total_token keep their cluster-wide semantics. Old-format unlabeled CSVs (single-node start_gpu_monitor path) emit no workers field and no role split — bit-for-bit identical to the parent PR's behavior for those callers.

Pipeline

srt-slurm perfmon (SemiAnalysisAI/srt-slurm:feat/inferencex-perfmon c4c86dc)
  → perf_samples_<role>_w<worker_idx>_<host>.csv on shared NFS
  → process_result.py (parent PR's bridge) → aggregate_power.run()
  → aggregate_power_per_worker() groups CSVs by (role, worker_idx)
  → agg JSON gets workers array + role-split joules (disagg) + existing cluster fields

Companion srt-slurm change

SemiAnalysisAI/srt-slurm c4c86dc: _start_perf_monitor derives role+worker_idx per node from backend_processes (which carries endpoint_mode and endpoint_index per Process) and labels output filenames. Allocator invariant — prefill and decode never share a node — means a single (role, worker_idx) per node is well-defined.

Files

• utils/aggregate_power.py: new _parse_role_from_filename + aggregate_power_per_worker. patch_agg_result gains extras kwarg. run() computes role-split energy and per-worker breakdown when filenames are labeled.
• utils/test_aggregate_power.py: 9 new tests.

Test plan

• 77/77 tests pass (68 existing + 9 new — filename parsing, per-worker grouping, multi-node worker aggregation, mixed labeled/unlabeled inputs, disagg E2E with role split, agg E2E without disagg-only fields, bit-for-bit backward compat)
• After parent PR merges and srt-slurm change lands, first real disagg sweep on gb300-cw emits workers array + prefill_avg_power_w / decode_avg_power_w / joules_per_input_token / joules_per_output_token_decode in the agg JSON
• InferenceX-app stage (separate PR): extend benchmark-transform.ts to surface workers array; add prefill/decode chart legend

App-side follow-up

ETL auto-captures any numeric field, so the scalar role-split fields (prefill_avg_power_w etc.) land in metrics JSONB automatically. The nested workers array needs explicit handling — that's a separate PR on InferenceX-app covering: type extension, benchmark-transform.ts mapper, chart legend with prefill/decode swatches.

Limitation (V1)

When multiple workers of the same role share a node (uncommon — happens in single-node multi-worker setups, e.g. 2 decode workers per 8-GPU node), perfmon labels by the lowest worker_idx and the aggregator currently attributes that node's full power to the lowest-idx worker. The other colocated workers would not appear in the workers list. For the GB300 multi-node disagg case (worker spans 1+ nodes, never shares), this isn't an issue.

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Note

Low Risk
Changes are confined to optional benchmark power post-processing and agg JSON fields; cluster-wide metrics stay the same for legacy CSV names, with broad test coverage.

Overview
Extends aggregate_power so multinode perf CSVs named perf_samples_<role>_w<idx>_<host>.csv (srt-slurm perfmon) drive per-worker power in the agg JSON, on top of unchanged cluster-wide avg_power_w / joules fields.

aggregate_power_per_worker keeps cluster totals via existing aggregate_power, groups labeled files by (role, worker_idx) (multi-node workers merge multiple CSVs), and returns a workers list. run() switches to that API; patch_agg_result accepts optional extras. When both prefill and decode workers are present, the agg JSON also gets role-weighted prefill_avg_power_w / decode_avg_power_w, joules_per_input_token, and joules_per_output_token_decode. Unlabeled legacy CSVs still patch only the original three keys (no workers).

Nine new tests cover filename parsing, grouping, mixed labeled/unlabeled inputs, and disagg vs agg vs old-format E2E behavior.

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[claude]

LGTM — additive per-worker breakdown on top of existing cluster-wide aggregation, backward compatible for legacy CSV names, well-covered by 9 new tests.

Extended reasoning...

Overview

Extends utils/aggregate_power.py with per-worker power attribution: a new _parse_role_from_filename helper, a new aggregate_power_per_worker function that wraps the existing aggregator and groups CSVs by (role, worker_idx) parsed from perf_samples_<role>_w<idx>_<host>.csv, a new optional extras kwarg to patch_agg_result, and an extended run() that emits a workers array plus role-split scalars (prefill_avg_power_w, decode_avg_power_w, joules_per_input_token, joules_per_output_token_decode) when both prefill and decode workers are present. utils/test_aggregate_power.py adds 9 tests.

Security risks

None. This is offline post-processing of NVIDIA/AMD SMI CSVs produced by the benchmark harness; no network calls, no auth, no user-controlled input. Filename regex is anchored and narrow.

Level of scrutiny

Low. This touches only optional benchmark power telemetry — not the inference, serving, or scheduling hot paths. The aggregator is best-effort and returns 0 on every error path so monitoring failures cannot break benchmark uploads. Cluster-wide fields (avg_power_w, joules_per_output_token, joules_per_total_token) keep their existing semantics and old-format unlabeled CSVs produce bit-for-bit identical output.

Other factors

• Tests cover filename parsing (labeled / multi-digit idx / old format), per-worker grouping with multi-node decode worker aggregation, mixed labeled+unlabeled inputs, disagg E2E with role-split joules, agg E2E without disagg-only fields, and legacy single-CSV bit-for-bit compat.
• The V1 limitation (multiple workers of the same role colocated on one node collapse to lowest worker_idx) is documented in the PR description and does not affect the target gb300-cw multi-node disagg case.
• Bug hunter found no issues.