From 411870d64f00181ea41a8059f4b53f5b232447c0 Mon Sep 17 00:00:00 2001 From: Yuren Hao Date: Sun, 12 Jul 2026 05:44:18 -0500 Subject: E-tier wave-1 ledger (RESULT 14 + HW map rows) + cost model v2 recalibrated on measured H200 datapoint Co-Authored-By: Claude Fable 5 Claude-Session: https://claude.ai/code/session_014FAPDWQ49M5Ye3NpTndTpn --- docs/campaign/CASCADE_ABLATION_PLAN.md | 24 ++++++++++++++++++++++++ 1 file changed, 24 insertions(+) (limited to 'docs/campaign/CASCADE_ABLATION_PLAN.md') diff --git a/docs/campaign/CASCADE_ABLATION_PLAN.md b/docs/campaign/CASCADE_ABLATION_PLAN.md index 61860f6..8b52369 100644 --- a/docs/campaign/CASCADE_ABLATION_PLAN.md +++ b/docs/campaign/CASCADE_ABLATION_PLAN.md @@ -538,3 +538,27 @@ s1 alone beat the BP mean). Ledger of the residual-0.05 epoch gap after three pr Carry `--bsign_rand` and a future centered mode as Stage-2 A/B flags; the gap question re-opens at 300M/real-corpus where it means something. Effort pivots to: (1) Stage-2 data pipeline (FineWeb-Edu + 32k tokenizer), (2) E-tier tolerance suite on the idle farm (hardware track / UIUC outreach feed). + +### RESULT 14 (2026-07-12): E-TIER WAVE-1 — full analog-fault tolerance ledger at stage1b s55000. +`etier_probe.py`, farm GPUs 2/3/7 (shards A/B/C), stage1b_ep_muon_s55000.pt (clean valCE 1.2678), +B=8 eval batches; metrics = faulted valCE (Δ vs clean), cos(EP_faulted, BP_faulted) [self-consistency +of the learning signal under fault], cos(EP_faulted, BP_clean) [direction vs the ideal update]. + +| fault (component) | mild | medium | severe | verdict | +|---|---|---|---|---| +| wq — weight quant (crossbar #3) | 8b: +0.004 / 0.956 | 6b: +0.051 / 0.812 | 4b: +2.23 / 0.05 | **8b FREE, 6b marginal, 4b dead → ≥7b effective is the binding spec** | +| fnoise — fwd additive state noise (softmax/relax #5) | 1e-3: 0.000 / 0.975 | 3e-3: 0.000 / 0.974 | 1e-2: +0.001 / 0.970 | **FREE at 1% — looped-era 1e-3 cliff does NOT transfer to cascade** | +| divmis — divisive-norm mismatch (#4/#7) | 1%: 0.000 / 0.971 | 3%: +0.003 / 0.948 | 10%: +0.042 / 0.785 | 3% (routine matching) FREE; 10% marginal | +| rope — phase error rad (#2) | 0.01: 0.000 / 0.973 | 0.03: +0.001 / 0.967 | 0.1: +0.012 / 0.923 | 0.03 rad FREE; ~2° I/Q accuracy suffices | +| gilbert — gate gain error (#6) | 1%: 0.000 / 0.974 | 3%: 0.000 / 0.971 | 10%: +0.006 / 0.945 | **FREE at 10%** — translinear practice is comfortably inside | +| fbnoise — nudge/error-channel noise | 1e-2: 0.969 / 0.975 | **1e-1: 0.951 / 0.957** | 3e-1: 0.764 / 0.768 | **10% relative noise on the ERROR CHANNEL is FREE** (cos 0.95) — the r-indifference/large-nudge gift, now measured on cascade | + +Reading: (a) the only hard constraint is crossbar weight precision (≥7b effective — inside standard +SRAM-CIM capability; 6b rescue = wave-2 quant-aware co-training); (b) everything dynamic — forward +noise 1%, error-channel noise 10%, gate/divider/phase mismatch at routine device tolerances — is +FREE at this scale. cos(EP,BP_faulted) stays ~0.97 under every non-fatal fault: the EP estimator +tracks whatever network the faults define, i.e. learning co-adapts to the fault (the analog-training +thesis in one number). CAVEAT: static probes at a trained checkpoint (eval CE + one-step gradient +direction), not training-under-fault; wave-2 = co-training with faults injected from step 0 +(expectation from the literature and from (c): tolerances IMPROVE). Feeds COMPONENT_HW_MAP.md +(per-row status updated) + UIUC outreach dossier. -- cgit v1.2.3