Spec: docs/superpowers/specs/2026-05-21-per-horizon-cfc-inference-design.md
Plan: docs/superpowers/plans/2026-05-21-per-horizon-cfc-inference-plan.md
Spec went through 2 critical-review passes (32 total findings, all resolved).
Bucketing source: CfC.tau (per-channel, trained, log-uniform init at HIDDEN_DIM=128).
Atomic refactor reverts MTER scaffolding. 5 ISV-driven controllers. All-on-device
transition (no bulk DtoH). Single fused per-branch kernel. Compact ragged heads_w_skip.
Validated via 3 Argo smokes (training stability, CRT.diag inference differentiation,
fxt-backtest end-to-end).
Also committing historical record: superseded MTER spec/plan, intervention A
plan, ISV λ controller spec/plan, GPU log ring spec/plan. Per spec §5.3 these
stay as audit trail; not in build path.
Plan has 18 tasks, full TDD with bite-sized steps, ready for
subagent-driven-development execution.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Per project_crt_diag_findings.md — CRT.diag + diag.2 empirically
falsified all three hypotheses about why the model's per-event output
doesn't track horizon-specific dynamics. Labels ARE differentiated per
horizon, AUC=0.66 IS per-event measured, but per-event predictions
behave identically across all 5 horizons (2.5-event mean run length
raw, 3.3-event after aggressive Wiener-α EMA smoothing). h6000
predictions should change every thousands of events, not every 3.3.
Diagnosis: training dynamics issue. The BCE loss provides no signal
pushing toward horizon-coherent predictions. Adjacent-event labels at
horizon K share K-1/K of the forward window so SHOULD produce similar
predictions, but the loss doesn't require this.
Intervention A (this spec, minimum-scope): output smoothness
regularizer
L_smooth[h] = λ[h] × mean_t (p[h](t) - p[h](t-1))²
With horizon-weighted λ (stronger for h6000 than h30): forces h6000
predictions to change slowly while leaving h30 responsive.
Implementation surface:
- multi_horizon_heads.cu backward: extend grad_probs with smoothness
gradient
- perception.rs trainer step: prev_probs_d buffer, per-horizon (p[t]
- p[t-1])² accumulation
- heads.rs: SMOOTHNESS_LAMBDA constant per horizon
- alpha_train.rs: --smoothness-base-lambda CLI flag
Validation gate (CRT.train Gate):
MUST: per-horizon AUC ≥ baseline - 0.02 (no signal destruction)
WIN: h6000 mean_run_len ≥ 100 events; h6000/h30 ratio ≥ 10× (horizons
actually differentiated post-training)
STRETCH: CRT.1 controller smoke shows mean PnL CORRELATED with
conviction (vs anti-correlated in lnfwd)
Future work if intervention A doesn't pass WIN:
B: horizon-conditional output structure (architecture change)
C: curriculum on horizon (multi-day training)
D: different label generation (majority-vote vs single-point)
Status: Design — awaiting user review before plan.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Empirical trigger: Phase A as designed in v2 failed Gate 1 catastrophically
on both smoke vjmwc (commit 3d8f12deb) and lkrdf (commit fe2498769 with
amplification clamp). Both produced ~155k trades (62× baseline), 9100%
max-drawdown (175× baseline), and Sharpe -15.7. The clamp had effectively
zero impact on the outcome, confirming the bug is structural not formulaic.
Architectural finding: the v2 phase split (A: continuous control / B:
signal-driven position management) is artificial. They are the same
mechanism. A scalar EMA on max(|p-0.5|) cannot smooth direction jitter
between horizons; only the multi-horizon ISV-weighted conviction formula
(v2 §4.4, deferred to Phase B in v2) is structurally coherent.
User-validated mental model: signal vector at any moment IS a forward
prediction of the trade trajectory; optimal position = inventory implied
by current beliefs; trade actions are sparse because most events
produce only fractional adjustments to a stable optimum. Continuous
evaluation, discrete action.
v3 phase structure (replaces v2 A/B/C/D):
CRT.1 Unified Inventory Controller (was A+B merged)
CRT.2 Adaptive Risk Envelope (was Layer C, unchanged)
CRT.3 Online Weight Adaptation (was Layer D, unchanged)
CRT.1 components:
- forward_step every event (already shipped: A0.5)
- decision_stride deleted (already shipped: A1)
- Multi-horizon ISV-weighted conviction (§4.4 promoted from Phase B)
- Wiener-α EMA on multi-horizon conviction (§4.2 promoted)
- target_lots = direction × |conviction_ema| × envelope_max
- No-trade band in seed_inflight: skip if |delta| < delta_floor (NEW)
- open_trade_state 24→64 expansion (§7 promoted from Phase B)
- Conviction-degradation exit emergent from target→0; composite-signal
safety layer (§4.3) preserved as circuit-breaker
What survives from v2 commits on the branch:
a0e81fbdf forward_step incremental SSM (A0.5)
92f8b10ed forward_step_into eliminates GPU↔CPU round-trip
045850e8f delete decision_stride field (A1)
3d8f12deb buffer-level seed bit-identity test
What gets superseded in CRT.1 implementation:
1d889d2de A2 scalar conviction-EMA with aggregate rescale — replaced
by multi-horizon §4.4 formula
fe2498769 A2.1 clamp on broken rescale — same reason
The three conviction-EMA device slots (conviction_ema_d et al.) STAY
in LobSimCuda — the EMA mechanism is reused on the multi-horizon
conviction scalar. The `final_size *= scale` rescale step is deleted.
Gate restructure:
v2 Gate 1 (Layer A standalone) — REMOVED
v2 Gate 2 (Layer B) — PROMOTED as Gate CRT.1
v2 Gate 3/4 — unchanged as CRT.2/CRT.3
Status: Design v3 — awaiting plan rewrite before implementation.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Self-critical review of v1 (commit 0f3484325) found 12 issues. All
fixed inline. Spec marked Status: Design v2 with explicit changelog.
LOAD-BEARING FIXES
1. §4.4 conviction cold-start: removed backwards "uniform fallback"
branch that maintained trading authority when net_edge=0 across
all horizons (exactly when model has no edge). Replaced with ε
floor on net_edge_h. Single formula, smooth bootstrap, no regime
switch.
3. §4.3 exit logic: 5 OR conditions → 1 composite exit_signal scalar
(max of degradation, disagreement, pnl_decay terms). SL/trail and
8h circuit-breaker stay orthogonal as safety, not exit policy.
Attribution per term recorded in §7 state for observability.
6. §9 Gate 2: PF > 1.0 (2.5× improvement, unrealistic) → tiered
MUST (no-regression) + WIN (real lift, four candidate criteria) +
explicit STOP condition if MUST passes without WIN.
7. §9.1.1: alpha-realization metric defined explicitly as
realized_pnl / max(unrealized during signal-validity window).
Was hand-waved in v1; now formulated.
TRACTABLE INLINE FIXES
2. §7 open_trade_state: 128 → 64 bytes. Diagnostic-only fields
(scale_up/down counts, max/min target reached) moved to a
separate audit buffer (single source of truth keeps state lean).
4. §5.1 envelope: multiplicative formula → additive bounded
contributions. tanh(sharpe), min(dd/cap), clamp(vol). No single
factor can crash envelope to zero. Floor (envelope_floor lots)
and hard-cap (envelope_hard_cap) remain.
5. §5.2 threshold: hand-waved "self-tune toward PF" → explicit
3-arm bandit (lower, current, higher percentile) every K_eval
closed trades, Wiener-α EMA target with floor, bounded
[0.5, 0.95].
8. §3.4 + §3.6: Layer A wall-time ≤ 5× → ≤ 2× (controller is
light, 5× would indicate structural bug, not config tuning).
9. §4.2: explicit Wiener-α formula for conviction EMA with floor
at 0.4 per pearl_wiener_alpha_floor_for_nonstationary.
10. §6.2.1: shadow eval defined explicitly with backtest-mode (last
15% of fold) and live-mode (parallel-prediction-only) variants.
Promotion criteria spelled out (PF, Sharpe, tail loss).
11. §6.2: Layer D loss explicit (primary = value regression on
realized PnL conditional on state; secondary = EWC++ regularizer
toward base). Was three losses with no specified combination.
12. §10.5: adapter regime over-fit risk added with sample-count
down-weighting, cross-regime shadow eval, periodic adapter reset
as hard backstop.
GREENFIELDS (per user direction)
- §3.3: decision_stride field DELETED from YAML + Rust (not
deprecated). No backwards-compat shim. Per
feedback_no_legacy_aliases.
- §7.1: open_trade_state 24→64 byte migration is atomic, no old
layout shim.
- §8: boundary matrix decision_stride row marked REMOVED, not
DEPRECATED.
§13 pearl conformance: per-section pearl application (not bulk
citation). Added pearl_audit_unboundedness_for_implicit_asymmetry,
pearl_no_deferrals_for_complementary_fixes acknowledgement (layers
are sequenced amplifications, not parallel fixes), and the new
pearl_stop_checks_run_at_deadline_cadence from S2.
Status: Design v2 — awaiting user review before writing-plans.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Three follow-ups from cluster smoke gp74n (trade_vol pearl validation):
1. Max-hold force-close: max_hold_ns added as per-backtest config
(default 0 = disabled). Fires force-flat (3, 0) when current_ts -
entry_ts >= max_hold_ns, BEFORE SL/trail check. Tested via
max_hold_forces_close. Sweep YAML sets 60s cap to bound the long
tail observed in gp74n (263985s pathological hold).
2. exit_px defensive sanity check: 500/1024 gp74n trades reported
exit_px = ±i32::MAX/100 (float→int saturation sentinel from likely
NaN segment_realized). Defensive fix in pnl_track_step: if exit_px
is non-finite or diverges from entry_px by >10%, fall back to
entry_px with zero realised_pnl. Root cause to be traced separately.
3. Spec §9.2 criteria revision: mean_hold<30s replaced with p95<600s
+ max<=max_hold_ns. The 30s threshold reflected the pre-pearl
sub-cost churning bug, not a real feature criterion. p95 catches
long-tail pathology while letting alpha-driven exit timing breathe.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Replaces the Task 12 `2.0f * cost` floor (hardcoded multiplier) with
trade_vol = sqrt(realised_return_var) bootstrapped from cost². Per
pearl_trade_level_vol_for_stop_distance.md: microstructure ATR is the
wrong time scale for trade-level stop decisions; per-horizon
realised_return_var is the right one, with cost² as a structural cold-
start sentinel.
cost now appears exactly once — inside the sqrt as a bootstrap sentinel,
never as a distance multiplier. The 2.0f literal is eliminated;
controller is fully ISV-driven.
var_avg accumulates realised_return_var in the same single-pass horizon
loop as ema_loss/ema_win. Cold-start (var_avg=0): trade_vol = cost.
Post-bootstrap: sqrt(var_avg) dominates.
Test retargeted: cost_floor_prevents_sub_cost_stops →
trade_vol_floor_prevents_sub_cost_stops, with boundaries straddling
trade_vol=cost=0.125 instead of the prior 2*cost=0.25 (no-fire Δ=0.08,
fire Δ=0.20).
Spec §5, §10, §11, §12 amended.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Cluster smoke w7b4p showed 44864 closed trades in 1M events at 200ms
latency — physically impossible without sub-cost churning. Root cause:
sl_distance = max(pnl_ema_loss, atr) ≈ 0.05 at cold-start, but round-trip
cost = 2 × 0.125 = 0.25. Every stop-out guaranteed loss > 5× distance;
EMA converges sub-cost.
Amendment: triple-max sl_distance = max(pnl_ema_loss, atr, 2*cost);
trail_distance = max(pnl_ema_win, atr, 2*cost). cost is an ISV-discipline
strategy anchor (already per-backtest from P4 — no new state slot, no
tuned constants). Added cost_per_lot_per_side_per_b param to both decision
kernel signatures and threaded cost_per_lot_per_side_d through both launch
sites in step_decision_with_latency.
Test: cost_floor_prevents_sub_cost_stops validates unrealized in (ATR, 0.25)
does NOT fire SL; unrealized > 0.25 DOES fire. Spec amended (§10, §12).
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
- StopRules struct + sl_tp_rules field + all literals deleted; the ISV
stop controller (Tasks 2-9) replaces this dead data path.
- use_cold_start_stopgap propagation deleted across harness,
batched_config, fxt-backtest, sweep_smoke.yaml, and 5 test files.
- Q1 stopgap branch in harness.rs deleted; replaced with the original
simple strategy-upload loop.
- decision_floor_coldstart test retargeted: cold_start_persistent_
bullish_with_default_stops_never_closes -> ..._now_closes, asserts
trades > 0 AND |pos| <= max_lots (99 trades, pos=1 on local GPU).
- CBSW spec + plan prefixed with SUPERSEDED headers.
Per feedback_single_source_of_truth_no_duplicates +
feedback_no_partial_refactor: contract change migrates every consumer
in one commit. No legacy wrappers; no version suffixes.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Issues caught in self-review and fixed:
1. Encoding ambiguity: stop-fire writing (2, 0) would have silently
collapsed weak-alpha no-op semantics with force-flat. Introduced
distinct side=3 = force-flat; preserved side=2 = no-op for entry
path. Updated §3 + §5 + §7 truth table.
2. trail_hwm reset on close was implied in §4 but missing from §8's
touched-files list. Added pnl_track.cu modification (§7.1) +
added to §8 Added list.
3. __device__ helper enforcement: §3 now mandates stop_check_isv()
as a shared __device__ function called from both decision kernels,
not duplicated code.
4. Kernel arg additions enumerated explicitly in new §4.1 table —
every kernel-launch site gets named, no "thread through every kernel"
hand-wave.
5. seed_inflight_limits_batched (resting_orders.cu:439–475) named
explicitly in §1 + §7 — the actual kernel that needs the position-
target-semantics fix.
6. In-flight order summation: naive delta = target_signed - pos was
strictly worse than the original additive bug under non-zero
latency (would produce pos = pre + K·delta after fills). Fixed
§7 algorithm to compute effective_position by scanning all
active∈{1, 2} slots and summing their signed sizes. Added
position_target_not_additive_with_latency test.
7. ATR α=0.4 honest justification in §10: not strictly derived from
pearl_wiener_alpha_floor_for_nonstationary (which is about co-
adapting control loops, not passive observation); chosen as a
pragmatic project-wide constant matching isv_kelly_update_on_close.
8. CUDA Graph host-branch-free affirmation added to §3 — explicit
compatibility with P5 graph capture.
9. Cold-start symmetry caveat (§5): at n_trades_seen=0 both EMAs are
0 so sl_distance == trail_distance == atr — asymmetry only
emerges post-bootstrap. Acknowledged honestly.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Replaces StopRules::default()-all-zeros (the actual cause of the cluster
smoke's n_trades=0, falsifying the CBSW dilution diagnosis) with an
ISV-driven SL + trail-stop controller folded into the existing decision
kernel(s). Per-backtest ATR EMA on mid-price + per-horizon pnl_ema_*
drive distances under max(real, floor) per
pearl_blend_formulas_must_have_permanent_floor. No new kernel; single
source of truth in step_decision*. Folds in the position-target
semantics fix (200-event local repro showed position_lots=199 from
additive-vs-target order semantics) — same commit.
Removes: StopRules, sl_tp_rules, Q1 stopgap field/branch,
use_cold_start_stopgap propagation. Marks CBSW spec + plan SUPERSEDED.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Critical review surfaced 11 actionable issues in the v1 spec; 10 fixed
inline (#11 — legacy-comparison test — dropped per user decision since
empirical legacy behavior is already known: n_trades=0).
Performance:
1. expf → piecewise-linear ramp (~5× cheaper on GPU, no transcendental
in the hot path). Operationally equivalent: monotonic, saturating,
midpoint at K. Side-benefit: pure max-confidence at cold-start
(sq=0 instead of sigmoid's 11.9% leakage).
2. Single fused per-horizon pass replaces the two-loop sketch.
3. Tier 2 scope narrowed to decision_policy_default ONLY. The bytecode
VM (decision_policy_program) stays unchanged — runs only for custom
strategy experiments, never in production policy. Halves Tier 2's
surface area + test cost.
4. __device__ helpers cbsw_signal_quality + cbsw_weight introduced for
single source of truth.
Correctness bugs (silently present in v1 sketch, would have shipped):
5. strong_h and sq_min_active initializers added (were referenced
before init in the per-horizon loop).
6. Attribution mask at cold-start was setting all 5 bits because every
w[h] >= floor > 1e-9; trades would pollute ALL horizons'
recent_sharpe. Fix: binary split — at sq_min_active < 0.5 attribute
only to strong_h; at mature, attribute per weights > floor + epsilon.
7. sq_min was "min over h", which permanently locked the aggregator
into cold-start mode if any horizon never gets attributed (e.g.,
h6000-only-trading regime). Fix: sq_min_active = min over h with
n_trades_seen > 0; cold horizons don't gate maturity.
8. Opposing-horizons case now correctly fires on the strongest single
horizon at cold-start (piecewise-linear sq=0 → pure max-conf), with
explicit design-choice note explaining why this conservatism trade-
off favors firing.
Spec hygiene:
9. Rate validation committed to a measurement gate (Q2 ev/s ≥ 95% of
Q1 ev/s) instead of back-of-envelope estimate.
10. Kernel ABI explicitly stated as unchanged → feedback_no_partial_
refactor compliance is trivial at the kernel boundary.
12. Tier 1's use_cold_start_stopgap field is DROPPED in Q2 atomically
(not orphaned), and DoD checklist includes a grep-zero gate for
feedback_no_legacy_aliases compliance.
Risks updated: removed the sigmoid-narrowing risk (irrelevant now);
added register-pressure risk with the rate-gate mitigation; added
explicit "cold-start may lose on noisy trades" risk with empirical
escalation path (bump kelly_floor 0.20 → 0.40 if Q2 smoke shows large
negative PnL).
Math walk-throughs rewritten for piecewise-linear (different numbers
at cold-start): cold = pure max-conf, mature = pure weighted-sharpe,
clean separation at sq_min_active threshold.
Awaiting review of the revised spec before writing-plans dispatch.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
The post-trunk-grows threshold-tuning smoke (81decf40f) produced
n_trades=0 despite the model having a HEALTHY max-conviction
distribution (74.6% of decisions ≥ 0.30, 26.7% ≥ 0.70, full spread
across [0,1]). Diagnosis: the linear-weighted-mean aggregator in
decision_policy_default is structurally dilution-bound at cold-start
— single-horizon strong signals get washed out when uniform-floor
weights produce mean-over-horizons aggregation.
Solution: Conviction-Bootstrapped Sharpe Weighting (CBSW). Hybrid
max-confidence × weighted-sharpe with a per-horizon sigmoid transition
keyed on n_trades_seen vs MIN_TRADES_FOR_VAR_CAP. Cold-start: sig_mag
(decision-time conviction) drives weights AND max-confidence aggregator
fires single-horizon trades. Mature: recent_sharpe (historical) drives
weights AND linear-mean aggregator emphasizes strong-Sharpe horizons.
Permanent floor preserved per pearl_blend_formulas_must_have_permanent_floor.
Mirrors DQN bootstrap pattern (pearl_thompson_for_distributional_action_
selection): when historical estimates are uncertain, use available
signal as the bootstrap. Sig_mag is the ISV signal at decision time;
recent_sharpe is the ISV signal at trade-close time. Transition
self-terminates based on data accumulation, not time constants.
3-tier delivery (one spec, atomic commits):
Q1: Bytecode VM stopgap — upload max-confidence 7-instruction
program per backtest. Validates diagnosis; zero kernel work.
Q2: Kernel CBSW — replace weight + aggregator in both decision
kernels. 5 new regression tests covering cold/mature/transition.
Q3: New memory pearl pearl_conviction_bootstrap_for_kelly_aggregation
capturing the lesson.
Q4: Cross-reference from parallelism spec (deployability sweep
depends on CBSW being live to produce meaningful verdict).
The parallelism work (P1-P6) is fully working — confirmed by the
threshold-tuning smoke completing end-to-end (Succeeded status, 500k
decisions, artifacts written, aggregator parquet emitted). What's
blocked is the deployability VERDICT, because the dilution bug means
all variants would show n_trades=0 regardless of cost/latency/threshold.
CBSW unblocks the verdict.
Awaiting review before transitioning to writing-plans for Q1-Q4
implementation plan.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Critical review surfaced 9 issues; all fixed inline:
1. §1 — Reframed "140× amortization" as "amortization on forward; sim
runs parallel". True win is on the ~2ms forward shared across 140
cells, not on sim work which scales linearly with n_backtests.
2. §2 — Made the 1h target vs firm bound explicit (≤1h target, ≤2h
firm). Acknowledges Graph capture realistic speedup is 1.2-1.5×,
not 2×.
3. §5 — Dropped atomicAdd. Plain `+=` under the single-writer-per-block
convention (existing pattern across sim kernels). No race.
4. §4 — Documented max-over-horizons threshold rationale (vs per-
horizon or aggregate-conviction). Flagged per-horizon as a follow-up
tweak if dilution pathway matters in the verdict.
5. §7 P5 + §10 risk — Captured-vs-uncaptured tolerance is 1e-5 relative,
NOT strict bit-identity. CUDA Graph capture can reorder reductions
harmlessly by 1 ULP; strict bit-identity would be a false-positive.
6. §8 — Made explicit that parallel_sim_equivalence + independence
tests are BOTH required. Equivalence alone is necessary but not
sufficient (a shadow-backtest[0] bug still passes equivalence).
7. §3.3 — Specified output schema: `cell_W{n}/sim_<variant_name>/`
with summary.json carrying a resolved `sim_config` block (verdict
emitter reads that, not the directory name).
8. §7 P4 — Enumerated apply_fill_to_pos call sites + added grep-verify
step before commit, so no fill path silently loses cost.
9. §9 — Tightened rate-validation gates with hard targets (P2 ≤90s,
P5 ≤60s) instead of generous minute envelopes. Added §9.1 stride=8
fallback as explicit Plan-B if Graph capture under-delivers.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Brainstormed live with claude-opus-4-7. Targets ≤1h wall-clock per
4-quarter sweep on 1-3 L40S pods (vs ~750 GPU-hours naive). Three
multiplicative levers: per-backtest sim parameter matrix (~140×),
CUDA Graph capture (~2×), pod-level parallelism (~3×). Verified by
code-read during scoping:
- forward_only has no graph capture (X11 plan said so, X11 commit
didn't ship it)
- two host-roundtrip loops in sim.rs need GPU-ization for batching
to pay off (dispatch_latent_market_orders + close-detection)
- cost system is a literal-zero placeholder in pnl_track.cu:92
7-commit atomic ladder (P1-P7), each gated by tests + a measured rate
target. bf16 explicitly deferred to follow-up.
Awaiting review before transitioning to writing-plans for the
implementation plan.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Supersedes the 2026-05-19 deployability spec (commit 07d5de504). The
prior spec assumed CfcTrunk::save_checkpoint was the producer-side
wiring point — discovered at execution time that alpha_train trains via
PerceptionTrainer (full v2: VSN + Mamba2 ×2 + LN ×2 + attn-pool + CfC +
heads), not the simpler CfcTrunk. The existing LOB backtester loads
CheckpointV1 envelopes that only know about CfC weights, so there is no
producer for a checkpoint containing the full v2 model.
New scope: one bigger spec covering refactor + deployability end-to-end.
Phase 1 (X0–X19, code commits): grow CfcTrunk to own the full v2
inference graph; restructure PerceptionTrainer to wrap a trunk + add
training-only state (grads, AdamW). Discipline: bit-equivalence golden
fixture (X0) gates every refactor commit (X1–X11). CheckpointV2
envelope (X12) replaces V1. Verdict emitter (X17) reuses the tiered
classification (Pass-robust / Pass-nominal / Fail-inconclusive / Fail /
Fail-degenerate) from the superseded spec.
Phase 2 (Argo runtime): production training → smoke gate → threshold
pre-registration → 560-cell deployability sweep → verdict + memory
update.
Hard gate before Phase 2: post-refactor fold-0 smoke must reproduce
recorded 3-fold A/B numbers (best_mean_auc 0.7529, best_h6000 0.7639,
both within ±0.010 absolute) from project_ml_alpha_v2_ab_verdict
memory. Prior spec marked SUPERSEDED in its header, kept in history as
audit trail.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
User revisions to design spec from this session:
1. §2.1 — split anchor into realistic (200 ms, 1 tick) and stress (400 ms,
1.5 tick). Realistic remains the hard verdict gate; stress grades the Pass
into Pass-robust vs Pass-nominal.
2. §2.2 — expand metrics from Sharpe-only to four: annualized daily Sharpe
and max-drawdown are hard gates (median across windows > 1.0 and < 20%
respectively); Sortino and profit factor are diagnostics. Per-window
summary.json schema extended.
3. §2.6 — verdict emitter rewrites to two-anchor logic, tiered output:
Pass-robust / Pass-nominal / Fail-inconclusive / Fail / Fail-degenerate.
4. §3.3 — added max-dd computation and zero-trade-window failure modes.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Closes the wiring gap between the existing real-LOB backtest system (C1–C19 on
this branch) and the v2 ml-alpha model. alpha_train.rs currently never calls
save_checkpoint, so the LOB harness/sweep/aggregate machinery has never been
pointed at a real trained model.
Design defines a single-pass falsifiable deployability gate: produce a
production checkpoint (cv-n-folds=1, cv-train-window=4 → train on 2024
quarters, val on 2025-Q1, hold out 2025-Q2..2026-Q1), pre-register one
threshold on the W0 val window, then evaluate median Sharpe across 4
held-out walk-forward quarters at the realistic Scaleway→IBKR anchor (200ms
RTT, 1-tick all-in cost). Pass iff median > 1.0; inconclusive in [0.8, 1.0]
counts as fail; smoke gate halts the full sweep on any wiring failure.
Approved through brainstorming. Awaiting user spec-review before plan
handoff.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
The motivating "50% saturation hit-rate" observation came from gm67g
fold 0 (Option-2 config, commit 004b662c8 — itself a -0.003 mean_auc
regression vs ISV-σ at 410ab6b0e). Re-running the same diagnostic on
the actual production baseline (ISV-σ 3 folds: rxm5t/r57lx/x24d6,
logs retrieved from MinIO argo-logs bucket) on 215 horizon-epoch
observations:
saturated λ→AUC up: 8/13 = 61.5% median Δauc = +0.0025
non-saturated→AUC up: 96/202 = 47.5% median Δauc = -0.0012
difference: +14pp in favor of the controller working
The BCE-z-score controller is empirically correlated with the
optimization target. No evidence it's misaligned with AUC. Spec
premise falsified.
Spec retained in tree as historical record. The diagnostic
methodology itself (saturation→Δauc analysis on archived MinIO logs)
is the durable artifact and is documented in the supersede block.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
The current λ controller boosts horizons by BCE-EMA z-score, which conflates
three distinct causes of high BCE — only one of which (under-trained
horizon) benefits from boosting. The other two (intrinsically harder
horizon, calibration drift) are unaffected by gradient-magnitude lifts.
Empirical motivation (gm67g fold-0, this branch's 3-fold run):
when λ_h6000 saturated at 2.0, h6000's next-epoch AUC went UP 2/4
times and DOWN 2/4 times. 50% hit rate ⇒ the BCE saturation signal
is misaligned with the optimization objective.
This spec replaces BCE-z-score with AUC-regret:
best_auc[h] = running max of per-horizon validation AUC
regret[h] = max(0, best_auc[h] - current_auc[h])
regret_max_ema = EMA of max_h regret[h]
λ[h] = clamp(1.0, 2.0, 1 + regret[h] / regret_max_ema)
Properties:
- Aligned with the objective (AUC, not BCE)
- Naturally bounded (regret ∈ [0, 1])
- "At personal best" → λ=1.0 (no wasted boost)
- Auto-saturation by design (max-regret horizon → ceiling)
- Cold-start clean (e0: best=current, regret=0, uniform λ)
- Zero hardcoded magic beyond bootstrap epsilons
Implementation surface ~250 LOC:
- Split horizon_lambda kernel: horizon_loss_ema (per-step) +
horizon_lambda (per-epoch, AUC-regret math)
- Trainer state: drop z_max_ema, add best_auc + regret_max_ema
- Per-epoch entry point: trainer.update_lambda_from_auc()
- Extend isv snapshot log line with best_auc_h* + regret_h*
Test plan:
- Local 9/9 perception_overfit
- New synthetic-AUC unit test (controller correctness)
- Cluster 5-epoch smoke + 3-fold A/B vs Option-2 baseline (004b662c8)
- Success: mean_auc lifts ≥ +0.005 AND median sat→next-AUC delta positive
Awaiting user review before plan handoff.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Integrated design spec for the post-A/B redesign: Kendall sigma BCE
(A), L2 anchor on horizon tokens + shared Q (B), horizon-token
K-prepend replacing per-horizon Q_h (C), regime-aware MoE gate (D),
and inverted-axis attention pass (E). Bundled per
pearl_no_deferrals_for_complementary_fixes — all five axes have
orthogonal architectural scope and independent kill criteria.
Spec drops the C21-C25 per-horizon Q_h path (falsified by sweep
2026-05-18: mean_auc -0.019 vs single-Q baseline) and migrates the
existing init buffers into the new horizon-tokens prefix.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Captures the brainstormed "alternative attention pool variants"
follow-on from the original real-LOB integration brainstorm (Axis 1,
deferred from the LOB workstream as a separate model-side spec).
Design:
Replace shared learned query Q[HIDDEN_DIM] with per-horizon queries
Q_h[N_HORIZONS, HIDDEN_DIM]. Per-horizon softmax + context vectors
feed multi-horizon heads directly (PATH A) — each horizon attends
to a different part of the K=6000 LN_b output sequence. CfC k=0
state is initialised by the MEAN of per-horizon contexts so the
K-loop recurrence + state amplification (per
pearl_state_amplifies_short_horizon_into_long_horizon) survives.
Heads consume per-horizon context concat CfC h_K (residual) with a
default 75/25 weight split.
Falsifiable claim (§0): A/B-tested win means h6000 mean_auc lifts by
≥ +0.01 absolute OR per-horizon distribution shifts toward short
horizons (h1000, h300) with no net h6000 loss. The 3-fold variance
band on the current architecture (mean_auc 0.7749 ± 0.024) means a
+0.01 lift is within noise — a meaningful effect needs ≥ +0.024 or
qualitative distributional shift.
Two new kernels (per_horizon_attention_pool_fwd + _bwd) + signature
extension on multi_horizon_heads_{fwd,bwd}. Variant-toggle config flag
(SharedQuery vs PerHorizonQuery) keeps the existing path fully
functional; new variant is opt-in. CheckpointV1 → V2 with explicit
discriminant + optional q_h field; V1 files load as SharedQuery, new
V2 training writes the discriminant.
Three validation rings:
1. Per-(b,h) numgrad parity at K=16
2. One-epoch smoke (no NaN, loss decreases)
3. 30-epoch × 3-fold A/B (#204) — decision gate per §0 falsifiable claim
Implementation explicitly deferred. The decision to invest depends on
(a) GPU time budget (~3-6 hrs on L40S × 5 GPUs for the A/B), (b)
whether per-horizon cost-frontier sweeps (#202 follow-ups) surface
viable horizons beyond h6000 that would benefit from per-horizon
specialisation, and (c) the 3-fold variance noise floor making the
expected effect size visible.
Next step when ready: invoke superpowers:writing-plans against this
spec for the ~6-8 commit implementation plan.
Closes the "good to have" question from the recent brainstorm with a
concrete decision framework rather than ad-hoc implementation.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Revises all 12 issues from the self-review pass:
1. (HIGH) Soften bit-equivalence claim — single-sample helper and
batched kernel at B=1 are different CUDA kernels; FP order may
differ. Acceptance is relative_eq ≤ 1e-6, not bit-exact.
2. (HIGH) Explicit asymmetry: only cfc_step has a single-sample GPU
oracle. GRN/VSN/attn bwd rely on smoke + chain-rule preservation.
feedback_no_cpu_test_fallbacks.md forbids a CPU reference oracle.
3. (HIGH) Realistic targets — 3× floor, 5× stretch. Drops 15× claim
which was Amdahl-bounded under any reasonable assumption.
4. (MED) AdamW-after-reducer invariant stated explicitly: final grad
buffer is OVERWRITE by reducer, meaningful only after reducer ran.
5. (MED) New B=32 smoke test (stacked_trainer_loss_shrinks_at_batch_32)
actually exercises the cross-batch reduction path; existing
perception_overfit suite is all B=1.
6. (MED) Rollout commit 1 bundles reduce_axis0 + first consumer
(cfc_step refactor) to avoid feedback_wire_everything_up.md
orphan-kernel anti-pattern.
7. (LOW) Drop "merge to ml-alpha-phase-a" — user already chose direct
commits to that branch; clarify in Rollout.
8. (LOW) Add explicit scratch-sizing formula:
scratch_bytes ≈ B × Σ(param tensor sizes per kernel).
9. (LOW) Remove resolved open question (memset_zeros ordering).
10. (STRUCT) Post-refactor bottleneck analysis section — names the
next L40S floor (Mamba2 scan, launch latency, cuBLAS).
11. (STRUCT) cudaFuncSetAttribute note — refactored cfc_bwd's per-
block shared mem drops to 1 KiB; no attribute change needed.
12. (STRUCT) Explicit Rollback section — atomic-commit-per-kernel +
revert strategy; rollback baseline is the spec commit
(54aa69c10) on ml-alpha-phase-a.
Plus locks the target pool to L40S — speedup must be attributable to
the refactor, not to a hardware bump. H100 / BF16 / larger batch
become candidates for a follow-up spec once the L40S floor is known.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Documents the design for fixing the single-SM bottleneck in five
backward/K-loop kernels: cfc_step (fwd+bwd), GRN bwd, VSN bwd, and
attention_pool bwd. All currently use grid=(1,1,1) with an internal
n_batch loop — on L40S (142 SMs) with B=32 this puts <1% of the GPU
to work in the K-loop critical path.
Architecture: block-per-batch (grid=(B,1,1)) for the kernel body, plus
per-batch grad scratch buffers reduced via a single parameterised
reduce_axis0 kernel (block tree-reduce, no atomicAdd per
feedback_no_atomicadd.md). Same pattern as the existing LayerNorm bwd
reducer — CUDA-Graph-safe, debuggable, and consistent with foxhunt's
no-cooperative-groups discipline.
Target: ≥3× epoch wall speedup (stretch 8-15×). Makes 3-fold CV
tractable (10.5h → 2-3h) and unblocks decision-stride / state-dim
sweeps that compound the gain.
Acceptance gates: (a) all 8 perception_overfit smokes still converge,
(b) new B=1 bit-equivalence test asserts the refactored batched bwd
kernel at B=1 matches the existing single-sample helper byte-for-byte,
(c) cluster A/B vs t6z89 baseline shows AUC trajectory within ±0.005
and epoch wall ≥3× faster.
Atomic refactor per kernel — one commit per kernel covering the
kernel rewrite, scratch buffer alloc, reducer launch wiring, and
smoke. No "_legacy" parallel kernels per feedback_no_legacy_aliases.md
+ feedback_no_partial_refactor.md.
Open implementation-plan decisions: exact memset_zeros ordering inside
the captured graph, batch-vs-per-tensor reducer launches, optimal
block_dim for reduce_axis0 itself.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Per user direction "no gating, this is the new default": the stacked
Mamba2 -> CfC -> heads design is THE production architecture. There's
no competing-baseline comparison to run. Validation reduces to normal
training metrics (per-horizon val AUC, train loss curve, sanity floor
of >0.5 AUC).
Deletions:
- crates/ml-alpha/src/gate/cfc_vs_mamba2.rs (gate verdict logic)
- crates/ml-alpha/src/gate/mod.rs
- crates/ml-alpha/examples/alpha_gate.rs (gate runner binary)
Renames:
- crates/ml-alpha/src/gate/auc.rs -> crates/ml-alpha/src/eval/auc.rs
- lib.rs: pub mod gate -> pub mod eval (gate implied comparison;
eval doesn't)
Spec amendments:
- Drop the "Gate baseline strategy" amendment (committed earlier
this session)
- Reframe the stacked-architecture amendment as a "decision" not a
"gate"; production path is unambiguous
- Reframe Section 4 "Validation gate: CfC must meet Mamba2" -> just
"Validation: per-horizon val AUC" with the >0.5 sanity floor
Doc cleanups: stale "Mamba2 gate baseline" mentions in build.rs and
pinned_mem.rs replaced with neutral wording. The Argo template
comment about "downstream gate consumption" becomes "for monitoring".
Test status: all 26+ ml-alpha tests pass. AUC tests (6/6) still pass
under the eval:: namespace.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Defines the Mamba2-only baseline for the stacked-vs-baseline gate
verdict as an ablation of the SAME PerceptionTrainer (a --bypass-cfc
flag), not a separate model. Apples-to-apples; same data window,
same hyperparameters, same code path. The only difference is whether
the CfC step is in the loop.
Three ablation options evaluated:
1. --bypass-cfc flag (recommended): Mamba2 -> heads directly
2. --mamba2-state-dim 2 (crippled Mamba2, CfC stays)
3. Frozen CfC initialized to identity (no code branch needed)
Option 1 wins on clarity: it answers "is CfC additive on top of
Mamba2" unambiguously, with the same Mamba2 capacity and same
training regime in both arms.
Concrete next-session work documented (1-2 hours):
- PerceptionTrainerConfig.bypass_cfc: bool + step() branch
- alpha_train --bypass-cfc CLI flag
- alpha-perception-template.yaml workflow parameter + bash branch
- submit both runs, fetch summaries, alpha_gate, commit verdict
gate_verdict logic unchanged — the cfc/mamba2 naming in the report
becomes stacked/bypass at the binding layer; the verdict math is
generic.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Mid-execution architecture revision: Mamba2 stays as a sequence
encoder; CfC becomes the layer on top (replacing the Phase 1d.3 MLP
stacker). Gate becomes 'stacked AUC >= Mamba2-only stacker AUC at
every horizon' — proves the CfC layer is additive, rather than CfC
alone beating Mamba2 alone.
Plan 1 kernels (cfc_step, heads, projection, BCE, AdamW, Graph A)
are unchanged. Only CfcTrunk's forward path gains a Mamba2 prefix
that consumes the snapshot stream and emits a 128-dim h_mamba which
CfC reads. The Mamba2 kernel (mamba2_alpha_kernel.cubin) is already
in the build.
Option B (parallel + fused dual-stream) is documented as the Plan 2
fallback if the stacked gate fails.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Two documentation deliverables produced while T14 backtest runs:
1. Plan update (specs/2026-05-15-phase-e-4-a-temporal-foundation.md):
adds 'Execution Status' section reflecting actual T1-T14
progression. T5 deferred (real MBP-10 peek), T9 skipped (GRN
moved to E.4.B per integration notes), T10 partial (new C51
grad-input kernel landed but Mamba2 backward wiring deferred),
T14 in flight. Documents the 4 execution learnings:
research-first saved a week of duplicate kernel work; cheap
falsification experiments (Path 2, Path 3) avoided expensive
investments; C51 borrow was the largest single Sharpe-lift in
the session; GpuTensor/CudaSlice interop friction is the real
integration cost.
2. T10 patch sketch (specs/2026-05-15-t10-mamba2-backward-from-h-enriched.md):
ready-to-apply patch for ml-alpha::Mamba2Block adding a new
public method backward_from_h_enriched(cache, d_h_enriched).
Bypasses the W_out projection backward, accepts the
[B, hidden_dim] gradient from C51's grad-input kernel directly,
zero-initialises dw_out/db_out (AdamW step on zero grad is a
no-op with correct moment decay — effectively freezes W_out
params which is correct semantics since Phase E never uses
them). Includes the smoke binary wiring snippet that consumes
the new method via launch_alpha_c51_grad_input → Mamba2
backward → AdamW step. Application gated on T14 backtest
validation — if frozen Mamba2 already lifts Sharpe, T10
becomes optimisation rather than prerequisite.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Design doc (specs/): TFT-style architecture for Phase E execution
policy — sliding window → Mamba2 SSM → GRN trunk → MoE regime gate
→ C51 head → Thompson selector. Two core pillars added per user:
A) Full L1-L10 LOB depth input via hybrid MBP-10 peek
B) ISV-continual-learning: controllers fire at training AND
inference; Q-net weights frozen at inference but effective
policy adapts via ISV modulation
Plan doc (plans/): 14-task implementation plan for E.4.A foundation
(window buffer + L1-L10 depth + Mamba2 forward+backward + ISV-eval
controllers). Falsification gates: smoke R_mean improvement ≥ 50%,
backtest cost=0 Sharpe ≥ +8 (no regression vs C51-flat +10.41),
half-tick Sharpe ≥ -8 (closes 5pt+ of 10pt gap to Phase 1d.4
baseline -4.0).
TGGN (foxhunt Temporal Graph Gated Network) explicitly deferred to
Phase E.5+: existing CPU graph implementation + GPU adapter at
ml-supervised/src/tgnn/ — marginal benefit for single-instrument ES
futures vs the TFT-Mamba2 stack; revisit for multi-instrument
extension or production HFT inference layer.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Findings:
- Production Mamba2 (gpu_dqn_trainer) is coupled to SH2=256 trunk +
ofi_embed + ISV[8] temporal routing — not portable to Phase E.
- ml-alpha::mamba2_block::Mamba2Block is from-scratch, fully
configurable (in_dim/hidden_dim/state_dim/seq_len), GPU-pure with
forward_train/backward/AdamW. Used in Phase 1d.2 to lift AUC 0.50
to 0.66. ml-alpha is already a workspace dep of ml.
- GRN skipped for E.4.A — Mamba2 output goes straight to C51 head.
Reintroduce GRN in E.4.B if Sharpe gates don't pass.
- Controller-at-inference: kernel has no training-mode branches;
Wiener state preserved across episodes/cost cells for natural
live-deployment simulation.
Revises Tasks 8-10 of the plan: use Mamba2Block API instead of
writing custom kernels. Only new CUDA needed: alpha_c51_grad_input
(C51 gradient w.r.t. input features, for Mamba2 backward chain).
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Atomic Phase 1.4 commit per `feedback_no_partial_refactor`. Wires the
SP20 fused-producer chain (Stats → Aggregate → EMAs → Controllers) into
GpuExperienceCollector's per-rollout-step path with one new aggregation
kernel + Phase 1.2 EMA kernel-signature refactor + production wire-up
+ tests + audit/spec/plan amendments, all in one commit.
## Path C decision rationale
The Phase 1.2 EMA kernel originally took 9 scalar value-args. The Phase
1.4 wire-up site (per-rollout-step in GpuExperienceCollector) needs to
feed per-env GPU-resident trade signals (trade_close_per_sample,
step_ret_per_sample, hold_at_exit_per_sample, packed factored
actions_out) into the kernel — forbidden via host sync
(`feedback_cpu_is_read_only`) and via memcpy_dtoh/htod
(`feedback_no_htod_htoh_only_mapped_pinned`). Path C refactors the EMA
kernel to take a device struct pointer (`SP20EmaInputs* ema_inputs`) +
adds an aggregation kernel that writes the struct on the GPU. Phase 1.2
had zero production consumers yet, so the sig change + Phase 1.4 wire-up
land atomically.
## What this commit contains
1. **EMA kernel signature refactor** (Phase 1.2 → Path C):
`sp20_emas_compute_kernel.cu` swaps 9 scalar args for a single
`const SP20EmaInputs* __restrict__ ema_inputs` device pointer.
Math semantics bit-identical. Rust `EmaInputs` mirrored as
`#[repr(C)]` byte-for-byte; new `pack_inputs_into_f32_view` helper
for tests + collectors that fill the struct via a mapped-pinned
f32-aliased buffer.
2. **New aggregation kernel** (`sp20_aggregate_inputs_kernel.cu`):
Per-env arrays (sliced to current rollout step) + sp20_stats outputs
(p50/std) + aux_dir_acc_reduce_kernel output [0] → SP20EmaInputs
struct. Block tree-reduce (4 stripes × bdim × 4 bytes shmem); no
atomicAdd. Aggregation rules per spec §4.5:
- is_close = OR over envs
- is_win = (≥ 0.5 of closed envs were wins)
- trade_duration = round(mean(hold_at_exit) over closed envs)
- action_is_hold = strict majority (count*2 > n_envs) HOLD
- alpha = 0.0 (Phase 2 forward ref — reward kernel)
- per_bar_hold_reward = 0.0 (Phase 3.2 forward ref — Hold-cost dual)
- aux_logits_p50/std/dir_acc forwarded from upstream
3. **Production wire-up in GpuExperienceCollector**:
4 kernel handles + 4 mapped-pinned buffers (struct fields, alloc,
init); per-rollout-step launch sequence after env_step (step 5c):
`Stats → Aggregate → EMAs → Controllers`. All on the same stream;
stream-implicit producer→consumer ordering. Gated on
`isv_signals_dev_ptr != 0 && trainer_params_ptr != 0` (matches the
existing SP14-β EGF chain pattern).
4. **Fold-boundary reset**:
3 new RegistryEntry records (sp20_ema_inputs_buf,
sp20_emas_internal_buf, sp20_emas_obs_count_buf) + 13 new dispatch
arms in training_loop.rs (10 SP20 ISV slot resets + 3 buffer resets).
Closes the pre-existing `every_fold_and_soft_reset_entry_has_dispatch_arm`
regression (was failing on fresh check after the SP20 ISV slot
registrations landed in commit 4249ebc96).
5. **HEALTH_DIAG emit**:
Per-epoch `HEALTH_DIAG[N]: sp20_isv [loss_cap=… alpha_ema=…
wr_ema=… hold_cost_scale=… target_hold_pct=… hold_pct_ema=…
hold_reward_ema=… n_step=… aux_conf_threshold=… aux_gate_temp=…]`
right after the existing q_disagreement_diag emit.
6. **Tests** (5 test files, all green on RTX 3050 Ti sm_86):
- sp20_emas_compute_test.rs (4 GPU oracle): updated to use the
post-Path-C buffer-arg API (mapped-pinned f32-aliased struct).
- sp20_aggregate_inputs_test.rs (NEW, 6 GPU oracle): aggregation
rule coverage including the Phase 2 / Phase 3.2 placeholder
contract.
- sp20_phase1_4_wireup_test.rs (NEW, 2 GPU oracle): end-to-end
4-kernel chain integration test.
- sp20_stats_compute_test.rs (4 GPU oracle): unchanged, regression.
- sp20_controllers_compute_test.rs (7 GPU oracle): unchanged,
regression.
- 18 lib unit tests across the SP20 launchers.
7. **Phase 2 / Phase 3.2 forward references**:
The `alpha` (Phase 2) and `per_bar_hold_reward` (Phase 3.2) fields
are emitted as 0.0 placeholders and documented at:
- `sp20_aggregate_inputs_kernel.cu:46-52` (in-kernel docstring)
- `sp20_aggregate_inputs.rs:46-49` (launcher docstring)
- `dqn-wire-up-audit.md` "Phase 2 / Phase 3.2 forward references"
These are NOT stubs — Phase 2 / 3.2 will replace the kernel's 0.0
writes with real signals atomically with their respective producers.
The original Task 2.3 (host-side aggregation) is **subsumed** by
the GPU-side aggregation kernel.
## Hard rules
- `feedback_no_partial_refactor` — kernel sig change + aggregation
kernel + production wire-up + tests + audit/spec/plan amendments
in one atomic commit
- `feedback_no_atomicadd` — aggregation kernel uses block tree-reduce
- `feedback_no_cpu_compute_strict` — every aggregation lives on GPU
- `feedback_no_htod_htoh_only_mapped_pinned` — every Phase 1.4 buffer
is mapped-pinned with `cuMemHostAlloc(DEVICEMAP)` reachable via
`dev_ptr`; no memcpy_dtoh/htod
- `pearl_first_observation_bootstrap` — counter-based bootstrap
preserved; placeholder writes (0.0) keep the ALPHA / HOLD_REWARD
EMAs at 0.0 sentinel until Phase 2 / 3.2 wire real producers
- `pearl_no_host_branches_in_captured_graph` — every kernel is single-
block; no host branches; safe to capture in the per-step CUDA Graph
- `pearl_tests_must_prove_not_lock_observations` — integration test
asserts invariants (slots populate, bounds respected) rather than
locked observed values
## Verification
- `cargo check -p ml --features cuda` clean
- 18 lib unit tests for SP20 launchers pass
- 23 GPU oracle tests across 5 test files pass on RTX 3050 Ti (sm_86)
- `every_fold_and_soft_reset_entry_has_dispatch_arm` regression test
now passes (was failing pre-change)
- 14 baseline lib test failures unchanged (none introduced by this
commit)
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
The Phase 1.1 sp20_stats_compute kernel (de922c6a4) assumed the SP14-C aux
head emits 3-class logits {short, hold, long} with baseline 1/3. This was
an error in the SP19+20 spec — production aux head emits K=2 logits
{down, up} per gpu_aux_heads.rs:61 (AUX_NEXT_BAR_K = 2, established by
SP13 B1.1a). Wiring K=2 production aux into the K=3 kernel = OOB reads +
corrupt stats.
Retargets the kernel + launcher + tests to K=2 atomically per
feedback_no_partial_refactor:
- Kernel: SP20_K_CLASSES 3→2; SP20_UNIFORM_K3 0.333…→SP20_UNIFORM_K2 0.5f;
Pass A reads 2 logits (was 3); aux_conf range [0, 1/2] (was [0, 2/3]).
- Launcher: AUX_K_CLASSES 3→2; renamed unit test
aux_k_classes_is_three → aux_k_classes_matches_production_aux_head.
- Tests: rewrote CPU oracle for K=2 input shape and 0.5 baseline; updated
expected p50/std ranges; redesigned heterogeneous-distribution test to
use ramped (not lockstep) clusters — K=2's saturated softmax in the hot
half collapses every row to bin 255, triggering the
pearl_sp4_histogram_warp_tile_undercount trap; ramped clusters distribute
bin indices across each warp's 32 lanes so the histogram path matches
the CPU oracle within bin_width tolerance.
Phase 1.2 (sp20_emas_compute) and Phase 1.3 (sp20_controllers_compute)
consume the scalar [p50, std] outputs and do NOT carry the K dimension.
Both regression suites verified passing unmodified:
- sp20_emas_compute_test: 4 GPU + 1 unit, all pass.
- sp20_controllers_compute_test: 7 GPU, all pass.
Verification (RTX 3050 Ti, sm_86):
- sp20_stats_compute_test: 4 GPU oracle + 4 launcher unit, all pass.
- cargo check -p ml --features cuda: clean (pre-existing warnings only).
Spec + plan amended at top with "AMENDED 2026-05-09" notes; audit doc
Phase 1.1 entry has a "K=2 fixup" subsection documenting the change.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Q1 design decision (b): add explicit hold_reward_ema to center the per-bar
Hold reward, so Q(Hold) and Q(trade) targets are scale-comparable. The
marginal Q(trade) > Q(Hold) preference now comes from data variance in
each state (high-aux states pull Q(Hold) more negative), not from
structural scale asymmetry that depends on cost_scale magnitude.
Q2 decision: keep 4-quadrant fixed (no ramping partials). Already in spec.
Changes:
- §4.2 Hold opp-cost: dual emission documented — R_per_bar_centered
(= R_per_bar - hold_reward_ema) for Q-target/replay tuple,
R_per_bar uncentered for hold_baseline_buffer (Component 1 baseline)
- §4.5 Kernel 1: hold_reward_ema added (per-step on Hold-state bars only)
- §5 data flow: per-bar reward path shows the centered/uncentered split
- ISV slots: 9 → 10 (HOLD_REWARD_EMA_INDEX added)
- §8 footprint: Component 2 LoC 70 → 90 (+20 for dual emission)
- Total LoC estimate: 1620
Mirrors the SP17 PP.1 plan-copy pattern. Plan and spec source-of-truth
live on the sister `feat/sp17-dueling-q-network` worktree; this commit
copies them onto the SP18 branch so subsequent commits reference local
paths.
Spec: docs/superpowers/specs/2026-05-08-sp18-reward-shape-hold-attractor-design.md
Plan: docs/superpowers/plans/2026-05-08-sp18-reward-shape-hold-attractor.md
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Second critical review pass found 10 more issues, 3 critical.
All addressed:
CRITICAL:
- §8.2 (3.1): ALPHA_SPLIT cold-start was unspecified — formula
produces 0/0=0, not the claimed 0.5 sentinel. Now: ISV slot
initialized DIRECTLY to 0.5 in trainer constructor; formula
takes over only after both grad-norm EMAs accumulate N_warm
non-zero observations
- §9.2 (3.5.4): plasticity now performs TWO-STEP recovery:
(1) Flat all positions at fire bar (close current losing trade),
(2) engage warmup cooldown forcing Hold for M_warm bars.
Without step 1, forced Hold preserved the losing position
that drove drawdown for the entire 200-bar warmup
- §12.2: stale "5-10%" baseline cost estimate updated to "15-25%"
matching §6.4 (was contradicting earlier amendment)
IMPORTANT:
- §9.2 (3.5.5): DD_TRAJECTORY_DECREASING threshold 0.02 hardcoded
→ ISV-driven via new slot DD_TRAJECTORY_FLOOR (slot 441,
25th percentile of running dd_pct distribution)
- §8.2 (3.5): HOLD_FLOOR_ALPHA tracked from rolling 95th percentile
of |Q_dir| (NOT running max — was outlier-ratchet vulnerable)
- §9.2 (3.5.3): MEDIAN_STREAK_LENGTH formerly undefined in cooldown
K formula → ISV-driven via new slot 442, running median of
observed loss-streak lengths via two-heap algorithm
- §9.2 (3.5.2): asymmetric reward × α split compound interaction
explicitly stated as intentional with POS_CAP as binding ceiling
NIT:
- §7.4: "2C: Group 3 (4 tests)" → "(5 tests)" (was off-by-one
after 2.22 added)
- §9.2 (3.5.4): Xavier → Kaiming-He init for advantage head reset
(architecturally appropriate for ReLU-gated activation chain)
ISV_TOTAL_DIM: 441 → 443 post-SP15 (added DD_TRAJECTORY_FLOOR
and MEDIAN_STREAK_LENGTH at slots [441..443)). 46 SP15 slots
total. File: 799 → 811 lines.
Spec is now consistent end-to-end with no contradictions between
sections, no hardcoded values violating feedback_isv_for_adaptive_
bounds, and no underspecified load-bearing parameters.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Two further user-flagged corrections from second-critical review:
1. Direction Q-head emits K=4 actions, NOT K=3.
Authoritative source: state_layout.cuh:123-126
#define DIR_SHORT 0 // open/maintain short
#define DIR_HOLD 1 // keep current position (no-op)
#define DIR_LONG 2 // open/maintain long
#define DIR_FLAT 3 // close all to zero
The "default: 3 — Short/Flat/Long" comment at gpu_dqn_trainer.rs:2438
is stale pre-SP13. Production callsites all set branch_0_size: 4.
SP13 added DIR_HOLD as a separate fourth direction action (Hold-pricing).
The config default comment was never updated when DIR_HOLD landed.
This is exactly the feedback_trust_code_not_docs failure mode — a
single stale comment would have silently corrupted the q_disagreement
signal (Hold/Flat being indices 1/3 instead of just Flat=1).
Updates:
- B.1 action-space context: 4 actions with Hold AND Flat both
non-committal (Hold = keep position, Flat = exit to zero)
- B.2.3 q_disagreement mapping: K=4↔K=2 with both Hold and Flat
masked from disagreement signal (no new directional commitment
to evaluate); only Short and Long picks contribute to disagreement
- Edge case handling for all-Hold/all-Flat batches
2. Adaptive β rate limiter (was structural β=0.9).
Per feedback_isv_for_adaptive_bounds, β should be signal-driven
not hardcoded. v3 derives β from variance of α_grad_raw, mirroring
the k_aux/k_q variance-driven steepness pattern in B.2.5.
Formula:
β = clip(β_base + variance_alpha_raw / variance_ref_alpha,
[β_base, β_max])
β_base = 0.5 (light smoothing baseline; ~2-step half-life)
β_max = 0.95 (heavy smoothing; ~20-step half-life)
Stable α_grad_raw → β = β_base (preserves directional intent)
Volatile α_grad_raw → β → β_max (dampens jitter)
Adds 2 ISV slots:
ALPHA_GRAD_RAW_VARIANCE_EMA_INDEX (Welford variance)
BETA_RATE_LIMITER_ADAPTIVE_INDEX (current β value)
ISV slot count: 11 → 13 (net +2 for variance + adaptive β).
LOC estimate: ~1150 → ~1180 (negligible delta; 3 Welford
variances now in alpha_grad_compute_kernel instead of 2).
HEALTH_DIAG pearl_egf_diag emit updated to expose all three
adaptive scalars (α, β, k_aux/k_q) plus all three driving
variances (var_alpha, var_aux, var_q) for full observability.
Verified against current code at HEAD d243a6f08:
- state_layout.cuh:123-126 (DIR_* enum truth source)
- gpu_dqn_trainer.rs:2438 (stale K=3 comment confirmed)
- branch_0_size: 4 in 5 production callsites
(smoke_tests, gpu_iqn_head, gpu_backtest_evaluator)
- DIR_HOLD usage in experience_kernels.cu:1298 + 14 other sites
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
8 corrections from code-anchored critical review at HEAD eaf4adcb9:
1. Direction Q-head emits K=3 (Short/Flat/Long), not K=4. Aux head
emits K=2 (down/up). Gate 2 q_disagreement now uses K=3↔K=2 mapping
with Flat masking. Verified against gpu_dqn_trainer.rs:2438.
2. Forward launch order constraint added: aux forward must complete
before direction Q-head forward (new serial dep). Cited
pearl_canary_input_freshness_launch_order.
3. Adaptive sigmoid k formula fixed: v1 had unreachable k_max=50
because formula caps k ≤ k_base. v2 uses max(..., k_min) with
k_max = k_base implicit.
4. α_grad rate limiter promoted from nice-to-have to v1. Schmitt
state-flip introduces sigmoid discontinuity. β=0.9 EMA smoothing
added; new ALPHA_GRAD_SMOOTHED_INDEX slot.
5. q_disagreement_baseline drop: v1 had adaptive baseline as long-EMA
(feedback loop risk). v2 uses structural 0.5 (analytic K=3-with-
Flat-masked random alignment). Drop BASELINE_INDEX slot.
6. Backward gradient scaling clarified: α_grad scales dL/dx (input
gradient flowing back to aux), NOT dL/dW (Q-head's weight grad).
Q-head learns to use the wire freely; gate only controls upstream
flow.
7. 4 hard rules added: feedback_no_hiding,
feedback_no_htod_htoh_only_mapped_pinned,
feedback_kill_runs_on_anomaly_quickly,
pearl_canary_input_freshness_launch_order.
8. Smoke A2 explicit kill criteria table added (8 triggers).
Net ISV slot count unchanged (11), composition shifted: dropped
BASELINE, added SMOOTHED. Total impl cost ~1150 LOC (was ~1060).
Verified against current code:
- TARGET_DIR_ACC_INDEX=372, AUX_DIR_ACC_SHORT_EMA_INDEX=373,
AUX_DIR_PREDICTION_INDEX=375 (sp13_isv_slots.rs)
- set_aux_weight clamp(0.05, 0.3) at gpu_dqn_trainer.rs:14722
(confirms Bug 3 from Smoke A diagnostic)
- mag_concat_qdir precedent at experience_kernels.cu:4560
(direction-conditioning pattern; SP14's wire is the analog)
- state_reset_registry pattern at lines 913-922 (canonical
template for new EMA fold-reset entries)
- branch_0_size = 3 in production config (the K=3 finding)
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Designs the SP14 chain on top of SP13 Layer B (HEAD 6657e5626):
1. Sub-project A — stability fixes (3 small bugs found in Smoke A)
- C51 atom-probability floor (ISV-driven from SP4 atom_pos_p99)
- aux_w setter clamp lift [0.05, 0.3] → [0.15, 1.5]
- Stagnation warmup gate at fold boundary
2. Sub-project B — the architectural piece (THIS spec)
- Forward wire: aux_softmax_diff per-bar into direction Q-head input
concat (in_dim+1, fingerprint bump, zero-init new column)
- Earned Gradient Flow pearl — adaptive ISV-driven gradient gating:
* Gate 1 (aux competence) — Schmitt-trigger hysteresis
* Gate 2 (Q-head disagreement) — NEW signal, EMA per-step argmax
mismatch
* ISV-adaptive sigmoid steepness (variance-driven k_aux, k_q)
* Per-epoch warmup ramp
* Anti-gradient-hacking circuit breaker (mesa-opt defense)
- 11 new ISV slots, 3 new GPU kernels, ~1060 LOC total
- HEALTH_DIAG pearl_egf_diag observability line
3. Sub-project C — Adaptive LR (deferred until A+B effects measured)
Motivation from Smoke A diagnostic:
- aux_dir_acc reached 0.61 (signal extraction works)
- val_win_rate stuck 45-48% (no path to action selection)
- WR-flat-while-aux-varies = Q-head directional weights frozen
- 1109 GRAD_CLIP_OUTLIER events (chronic; not noise)
Three parallel diagnostic agents triangulated three interlocking root
causes:
- Slot 375 has zero readers (the wire was scoped but never built)
- C51 raw grad reaches 9.5e6, saturates SP7 budget controller
- aux_w controller muzzled by SP11-era [0.05, 0.3] clamp
The Earned Gradient Flow pearl is a new application of the codebase's
pearl pattern: ISV-driven adaptive controller, but applied to backward-
pass gradient flow instead of forward-pass features. The wire is one-
way (stop-gradient) by default; co-training is earned by both:
(a) aux head demonstrating label competence, AND
(b) Q-head showing it's actually fighting aux signal (informative
disagreement above baseline).
Stability additions hardened against:
- Oscillation around target (Schmitt hysteresis)
- Numerical sigmoid saturation (argument clipping ±30)
- Stale variance EMAs across folds (state-reset-registry)
- Discontinuous warmup transitions (linear ramp)
- Mesa-optimization (gradient-hacking circuit breaker)
- Cold-start sentinel-state spurious gate openings (Pearl-A bootstrap)
Awaiting user review before invoking superpowers:writing-plans for
sub-project B (and a separate small plan for sub-project A).
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
P0a.T3 v2 implementer's audit revealed `DirectionAction` enum doesn't exist; the
codebase uses an 8-variant fused `ExposureLevel` (ShortSmall/Half/Full, Hold,
LongSmall/Half/Full, Flat) with cross-crate consumers across 77 files and 32+
test files pinning the 8-variant invariant. Atomic Hold elimination would
cascade massively.
User insight (2026-05-04): Hold being FREE is the bug, not Hold itself. MFT
trading legitimately needs multi-bar holds; we want the model to use them
deliberately, not as a CQL-bias lazy default. Holding isn't free in the real
world — broker fees, margin interest, opportunity cost.
v3 reframes as Hold-pricing:
- 4-way action space stays; ExposureLevel::Hold stays; no cross-crate cascade
- 3 new ISV slots (380-382): HOLD_COST_INDEX, HOLD_RATE_TARGET_INDEX,
HOLD_RATE_OBSERVED_EMA_INDEX
- Hold-rate observer: small GPU kernel + Pearls A+D smoothing
- Hold-cost controller: 5-line deficit-driven formula
(excess > target → cost rises 1×→5× base; observed ≤ target → relax)
- Per-bar reward subtraction at action == DIR_HOLD site
- 2 GPU oracle tests for the controller
P0a.T3 cuts from ~250 LOC + 32-test cascade → ~120 LOC additive. T1+T2
already-staged work unchanged. T4/T5/Layer B/C/D structure preserved.
Tension with pearl_event_driven_reward_density_alignment acknowledged in
spec — per-bar Hold cost is exposure-NEGATIVE (away from Hold), models real
economic carry, ISV-bounded by controller. Inverse of the pearl's failure
mode. Faithful reward modeling, not artificial shaping.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Three architectural changes in one unified design to push the model from
HFT noise extraction (62% trade rate, sharpe-gaming) toward MFT alpha-hunting:
1. Asymmetric bounded cap (-10/+5) — restores loss aversion erased by
SP11 symmetric cap. 2:1 ratio matches Kahneman/Tversky prospect theory.
Anchor: pearl_audit_unboundedness_for_implicit_asymmetry.
2. Min-hold soft penalty with temperature curriculum — patience requirement
at exit. Soft factor = deficit/(deficit+T), T anneals 50→5 over 50 epochs.
Forces commitment without paralysis in early training.
3. Zero per-bar shaping (gate micro/opp_cost on events) — eliminates
continuous-reward gradient that pulls toward continuous exposure.
Anchor: pearl_event_driven_reward_density_alignment.
Combined: reward fires only on trade events with prospect-theory loss
aversion + commitment requirement. Pure per-trade event-driven Q-learning
properly aligned with per-trade P&L objective.
~50 LOC across 3-4 files. No new ISV slots in Phase 1 (constants only).
Cost ~€1.30 (€0.30 smoke + €1.00 30-epoch validation).
Empirical motivation: train-multi-seed-pmbwn 50-epoch on commit 6a259942e
showed sharpe-gaming pattern (PnL -30% over 8 epochs while sharpe held).
SP11 cap fix unmasked the per-bar shaping bias plus erased loss-aversion
that the unbounded loss path was implicitly providing.
Continues on sp11-reward-as-controlled-subsystem branch — SP12 is
architectural continuation of SP11, not separate work.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
smoke-test-6wd2c on commit 61b2fa962 (B1b + 4 bug fix-ups) revealed a 5th
pathology not covered by the previous fix-ups: the mag-ratio canary's
linear-magnitude-ratio formula amplifies whichever component is
intrinsically largest, regardless of whether that's a useful signal.
Popart (trade P&L on segment_complete) is O(100) per fire while the
other 5 components (cf/trail/micro/opp_cost/bonus) are O(0.1-2). Even
with the slot 360 fix preventing total-reward contamination, popart's
intrinsic magnitude makes popart_mag / Σ ≈ 0.93. The controller blend
'winner_weight = ratio' then amplifies popart further. Smoke trajectory:
w_pop=2.0 → 2.44 → 2.57, curiosity_b=30 → 120 → 199, sharpe_ema=10.7 →
2.4 → 0.75 (cascading collapse).
Resolution: z-score normalization. Each component's magnitude divided
by its own running standard deviation before computing the ratio:
popart_z = popart_mag_ema / max(sqrt(popart_var_ema), EPS_DIV) ≈ O(1)
cf_z = cf_mag_ema / max(sqrt(cf_var_ema), EPS_DIV) ≈ O(1)
...
ratio[c] = component_z / Σ component_z ≈ ~1/6 each when stable
Allocates 6 new ISV slots [361..367) for per-component variance EMAs.
Producers: extend popart_component_ema_kernel + reward_component_ema_kernel
to also emit variance via Welford's online algorithm (single-pass).
SP5_SLOT_END = 367, ISV_TOTAL_DIM = 367.
Carries forward main's slot 360 amendment (commit 52c0b7521 on main)
which the sp11 branch was missing, plus this z-score amendment.
Per-component gradient ratios (the original spec intent) don't fix this
either — in DQN there's no per-component gradient pathway; grad norm
scales with current_weight × magnitude, so it's the same bias. Z-score
normalization is the standard scale-invariant measure of significance
and matches what the SP11 controller is trying to express.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
