- Pin endpoint.model=gpt-5.5, base_url=https://ai.gahow.org/v1, wire_api=chat.completions
in both ablation specs so both arms uniformly use the current ~/.codex model (the
prior runs used the stale ai.prism.uno/gpt-5.4 that config.toml has since moved off).
- run_ablation_pair_d1.sh re-reads the codex token from auth.json right before each arm
instead of capturing it once at launch (the stale-at-use capture 401'd naive 2/3).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Smoke on the real-output substrate measured feasible sampling_u = 0.0156 (TP2)
and 0.0742 (TP4, per-GPU 0.618 = 2.24x TP2). search.high=0.25 made the binary
search waste its two top probes (u=0.125/0.0625, always infeasible, admitting the
most long-output requests) on every trial. 0.15 keeps ~2x headroom over the TP4
boundary (0.0742) and trims ~15-20% of per-trial cost with identical feasibility
results; if a runtime-tuned config ever saturates 0.15 the harness search-high
saturation stop fires (informative, not silent).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Replace the out=128 / scale=0.5 ablation substrate with a paper-faithful one:
- Use the trace's real output_length (drop completion_tokens_override=128). The
0-8k chat window has p50=531 / p99=2436 / max=35168 output tokens, so decode
(TPOT) becomes the dominant bottleneck instead of an artificial 128-token cap.
- replay_time_scale=0.8775, chosen by criterion-A: binary-search the smallest
scale whose A-family L-C-A similarity to the real (scale=1.0) arrivals stays
>= tau (0.90). The old scale=0.5 had sim_A=0.56, distorting the arrival axis
far below the tau bar used everywhere else. New calibrator:
scripts/calibrate_time_scale.py.
- Per-probe Stop-A-consistent drain deadline (worker._probe_drain_deadline): the
wall-clock a *feasible* config needs to drain the LCA-admitted set
(last_arrival + worst-case TTFT + p99_out * TPOT budget + margin). With real
outputs decode dominates wall-clock, so the old fixed 320s cap would truncate
the Stop-A offered window mid-decode. early_stop_max_elapsed_s (1000s) is now a
hard ceiling; the per-probe deadline governs. The lag cap still cuts overload.
12-iter paired driver (both arms on dash1, removes the dash0/dash1 host confound):
scripts/run_ablation_pair_d1.sh. 115 tests pass.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
scale=0.2 made TP1 uniformly infeasible (no baseline); bound decode to 128 tokens and
use mild 2x compression so TP1 registers a real, fast baseline, with 6 probes to span
TP1's low and TP4's high feasibility boundaries. Both configs identical except use_harness.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
First TP1 baseline probe under scale=0.2 ran ~6min (severe overload, 260
preemptions on the lighter half of the trace; TP1 is decode-bound and the
arrival-lag early-stop does not cut a decode-drain-bound probe). Cut
search.max_probes 5->3 to bound binary-search steps per trial. Caps stay
at elapsed=180/lag=30. Both configs still differ only in use_harness +
study_id.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
At replay_time_scale=0.2 the 600s arrival window compresses to 120s, so
the inherited 900s wall-clock elapsed cap let overloaded TP1 probes burn
~15min each (the tractability hazard the brief flagged). Scale the caps
proportionately to the time axis: early_stop_max_elapsed_s 900->180,
early_stop_max_lag_s 120->30. Feasible probes (~120s arrival + drain)
finish well inside 180s; overloaded probes die in ~3min. Both configs
still differ only in use_harness + study_id. Adds the ablation doc
skeleton and a read-only trajectory-extraction helper.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Two configs identical except llm.use_harness and study_id, for the
controlled harness-ON vs naive-OFF tuning-trajectory ablation on dense
Qwen3.5-27B. Faster substrate (replay_time_scale=0.2, search.high=0.25,
max_probes=5) keeps the ablation tractable; Stop-A stays enabled.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
