Audited the v1 plan against the full project memory catalog. Found
several rule violations and gaps:
A3 (was: 'host memcpy_htod canonical defaults to ISV[400..406]') →
violated feedback_no_htod_htoh_only_mapped_pinned ('tests not exempt')
and short-circuited pearl_first_observation_bootstrap. Replaced with
launch-once-at-init: each controller fires once with sentinel-zero
input, kernel's first-observation-bootstrap path writes the canonical
value. No host write to ISV. Canonical pattern across the codebase.
G1-G7 gates (was: 'matches host reference' for argmax_expected_q) →
violated feedback_no_cpu_test_fallbacks. Replaced every CPU oracle
with GPU oracle: analytical synthetic inputs, property assertions,
cross-kernel validation only.
Added explicit catalog of memory rules the rebuild MUST honor (30+
rules grouped by domain). Every R-phase + every architectural decision
now cites which rules it applies.
Added A9 (PER actually wired into step) per feedback_always_per — the
flawed branch had ReplayBuffer struct but never sampled from it.
Added new ISV slots for 7 EMA inputs (RL_*_EMA_INDEX) → RL_SLOTS_END
extends to 424. The controllers' inputs live on device, not host.
Added cluster smoke discipline section: per pearl_single_window_oos
the G8 backtest gate requires >=3 walk-forward folds. Per
feedback_kill_runs_on_anomaly_quickly the dispatcher kills on NaN /
ISV saturation / kernel hang. Per pearl_q_spread misaligned, the
dispatcher MUST NOT kill on Q_SPREAD. Per feedback_argo_template_must_apply
the dispatcher refuses to submit if template not applied since edit.
Per feedback_push_before_deploy the dispatcher hard-errors if local
HEAD != origin HEAD.
Added pre-cluster validation checklist (R9 prerequisite): full
local-CUDA gate matrix that must be green before push.
Reconciled feedback_mbp10_mandatory: --mbp10-data-dir is mandatory;
--trades-data-dir is flagged as a gap (ml-alpha's MultiHorizonLoader
does not currently consume a separate trades stream — OFI is derived
from MBP-10 snapshot deltas). Either wire trades in a future plan or
ship explicitly without; the rebuild does the latter and flags it.
Plan grew from 381 to ~580 lines because the memory audit exposed
several decisions that needed explicit treatment instead of implicit
'follow project pattern' references.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Replaces the flawed Phase F + G arc preserved on branch
`ml-alpha-phase-f-g-flawed` (commits 99a125cdb..b3808a5ac). The prior
attempt shipped a trainer with multiple production-blocking defects:
1. ISV[400..406] uninitialised → kernels read γ=0, ε=0, entropy=0
2. rl_reward_scale_controller drifted to 1e3 on no-trade steps
3. 6 controllers exist as .cu but never launched
4. Target net never soft-updated (τ has no consumer)
5. step_with_lobsim violated feedback_cpu_is_read_only with host
Thompson sampling + EMA tracking + advantage/return loops
6. "toy" framing leaked into production (alpha_rl_train.rs shipped
with next_snapshots=snapshots — the F.4 next-state code path was
a no-op until that one issue got caught mid-review)
7. No NaN abort in production CLI
The convergence-gate fixtures (dqn_toy/ppo_toy → renamed
dqn_reward_signal/ppo_reward_signal on the flawed branch) hid every
defect because MockLobEnv is state-invariant with horizon=1.
The rebuild is GPU-pure: kernel-driven action sampling, kernel-driven
EMA tracking, kernel-driven advantage/return, ISV bootstrap at trainer
construction, all 7 controllers wired with device-resident EMA inputs,
target-net soft update consumer, NaN abort, no LobEnv trait (drives
LobSimCuda via the existing decision-policy kernel pattern).
Sequenced as R1..R9 with falsifiability gates G1..G7 that exercise
the specific failure modes the convergence-gate fixtures couldn't
catch. Calendar ~8.5 dev days.
Also adds memory pearl
feedback_extending_existing_code_audits_for_existing_violations
capturing the lesson: extending pre-existing CPU/orphan-controller
violations is how this happened.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Single integrated trainer where 5 loss heads (BCE direction, C51
distributional Q, categorical π, scalar V, aux prof+size) sit on a
shared Mamba2+CfC encoder. Joint training with adaptive loss-balance
λ weights via the existing pearl_loss_balance_controller infrastructure.
Discrete 9-action grid shared between Q and π heads; reward = per-trade
realized PnL from LobSimCuda.
Designed in response to lob-backtest-sweep-jpdhg result (PF=0.24,
sharpe=-9.72, mono-anti-cal in conviction→PnL): the encoder learns
directional AUC but never sees PnL-aware gradient because
stop_grad_aux_to_encoder blocks the aux head's gradient. RL training
fixes this by making the encoder optimize per-trade realized PnL via
Q-head Bellman + π-head clipped surrogate.
Every hyperparameter (γ, τ, PPO clip ε, entropy coef, rollout steps,
PER α, reward scale, loss-balance λs) is ISV-driven per
pearl_controller_anchors_isv_driven and feedback_isv_for_adaptive_bounds.
12 new ISV slots (400-411) + 12 reused existing slots + 8 new controller
kernels following the Wiener-α + first-observation-bootstrap pattern.
10 phases (A-H, ~3 weeks), falsifiable gate G8 = profit_factor > 1.0
on 2M-event backtest sweep.
Per feedback_no_htod_htoh_only_mapped_pinned: mapped-pinned only for
CPU↔GPU; tests not exempt. Previous commit ab64c0412 was a shallow
deprecated-API swap (memcpy_stod -> clone_htod) — both still HTOD
copies. This commit replaces all 5 uploads and the 1 readback in
test_eval_action_select_thompson_picks_proportionally with the
production mapped-pinned + memcpy_dtod_async pattern (mirrors lines
433-448 of the same file).
Closure 'upload_pinned' DRYs the 5 upload sites; readback uses
MappedI32Buffer + DtoD into staging.host_slice_mut().to_vec().
Zero HTOD/HTOH copies remain in this file. Documented in
dqn-wire-up-audit.md.
cudarc 0.19 deprecated memcpy_stod (use clone_htod) and memcpy_dtov
(use clone_dtoh). Six call sites in cuda_pipeline/mod.rs migrated.
Pre-existing warnings surfaced now because the recent file-level
allow(unsafe_code) on this file no longer per-line-suppresses the
deprecated lint.
Per feedback_no_legacy_aliases: rename call sites directly, no
deprecated wrappers. Documented in dqn-wire-up-audit.md.
CUDA kernel launches via cudarc::launch_builder and MappedF32::new
(cuMemHostAlloc DEVICEMAP FFI) inherently require unsafe blocks. The
workspace-wide '-W unsafe-code' lint produced ~80 warnings across these
files, all structurally identical. Match the established pattern from
ml-backtesting/src/harness.rs and ml-backtesting/src/sim/mod.rs: single
file-level allow with a comment explaining the rationale.
Files: alpha_dqn_h600_smoke, alpha_baseline, cublaslt_debug,
gpu_walk_forward, cuda_pipeline/mod, hyperopt adapters (mamba2, ppo),
DQN smoke_tests (helpers, td_propagation), trainers/ppo, and two
ml/tests files. Documented in dqn-wire-up-audit.md.
Replaces Option<u32> instrument_id_filter with InstrumentFilter enum {All,
Id(u32), FrontMonth}. FrontMonth runs a two-pass detect over the DBN
stream: pass 1 counts instrument_ids and collects SymbolMapping records,
picks the dominant id, validates it resolves to an ES contract via regex
ES[FGHJKMNQUVXZ]\d{1,2}; pass 2 streams the filtered records.
Motivated by alpha-perception-k54wd: a single-id filter on parent-symbol
ES.FUT data caught Q1 2024 (kept=73M) but kept=0 for Q2-Q9 because ES
front-month rolls quarterly (ESH4 -> ESM4 -> ESU4 -> ESZ4 ...). FrontMonth
self-tunes across the rolls without needing a per-file id table.
Sidecar keys distinguish modes: mbp10 / mbp10_instr<id> / mbp10_front_month.
CLI flag renamed --instrument-id -> --instrument-mode {all,id=N,front-month}
with matching parameter rename in argo-alpha-perception.sh + template.
Per spec §4.1 + Q-3-seed-baseline. Both baseline Argo workflows
succeeded:
- alpha-perception-baseline-seed16963 (39min)
- alpha-perception-baseline-seed16964 (26min)
Precise AUC values deferred: train pod stdout is in MinIO archive
(xl.meta format, needs mc auth). The on-disk alpha_train_summary.json
on /feature-cache/alpha-perception-runs/f22f3f948/ corresponds to
seed 16963 (last to finish). Task 15 implementer retrieves via debug
pod mount of feature-cache PVC.
Known data point: seed 16962 = 0.7454 best_auc_h6000.
The Smoke 1 invariant gate threshold is signal-derived per
pearl_tests_must_prove_not_lock_observations — formulas captured in
the JSON for Task 15 to apply once values are retrieved.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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>
Per spec §7 (v3 architecture reset, promoted from v2 Phase B into CRT.1).
Single-cache-line layout. Every reader and writer of open_trade_state
migrates in this commit per feedback_no_partial_refactor.
New 64-byte layout (existing 24-byte fields preserved at original offsets):
Offset Size Field
0 8 entry_ts_ns (u64)
8 4 entry_px_x100 (i32)
12 4 entry_size (i32)
16 4 realized_at_open (f32)
20 4 conviction_at_entry (f32) ← NEW
24 4 conviction_ema (f32) ← NEW
28 16 conviction_per_horizon_ema [4 × f32] ← NEW
44 4 pnl_adjusted_conviction_ema (f32) ← NEW
48 4 peak_unrealized_pnl (f32) ← NEW
52 4 degradation_consecutive_events (u32) ← NEW
56 4 disagreement_consecutive_events (u32) ← NEW
60 1 horizon_idx_dominant_at_entry (u8) ← NEW
61 3 pad
The 24-byte prefix is unchanged so downstream readers (stop_check_isv in
decision_policy.cu, max_hold event-rate check in resting_orders.cu) need
only update the stride constant. The new fields at offsets 20..63 are
populated by subsequent CRT.1 tasks (C1.2 multi-horizon conviction, C1.4
composite exit signal).
Open branch in pnl_track.cu zeros the new fields implicitly because
alloc_zeros on the device slot zero-initialises everything; subsequent
writes only touch the 0-23 byte range (existing fields). Close branch
reset-loop iterates OPEN_TRADE_STATE_BYTES which now zeros all 64.
Files changed:
crates/ml-backtesting/src/lob/mod.rs — pub const OPEN_TRADE_STATE_BYTES: usize = 64
crates/ml-backtesting/cuda/pnl_track.cu — #define OPEN_TRADE_STATE_BYTES 64
crates/ml-backtesting/cuda/resting_orders.cu — comment + stride literal 24→64
crates/ml-backtesting/tests/stop_controller.rs — open_trade_state_64_byte_layout test
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>
forward_only requires the full K=seq_len window on every call and resets
Mamba2 h_s2 to zero each invocation — no cross-call state carry. Additionally,
the call is inside the stride=200 gate in harness.rs (spec §3.2 claim "already
every event" is incorrect as of HEAD). Moving to stride=1 without a forward_step
implementation would be a ~200x GPU cost increase. A0.5 must implement
forward_step with persistent h_s2, a dedicated K=1 CUDA graph, and session-reset
hook. Memo documents exact file paths, line numbers, required struct/method
changes, and open questions for the A0.5 implementer.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Per user direction: no fallbacks, greenfields, kernel updates acceptable.
Changes:
1. Task A0.5 ADDED — pre-planned task that fires if A0 investigation
finds forward_only is stateless K-window (Case 2) or has periodic
reset (Case 3). Refactors PerceptionTrainer to maintain persistent
SSM state and expose forward_step(snapshot, b) that advances by 1
event. Bit-identical to forward_only of equivalent window per a
new golden test in incremental_forward.rs.
This is NOT a fallback — it's a pre-planned task whose execution
is determined by actual investigation outcome. Case 1 → A0.5 is
a no-op. Case 2 or 3 → A0.5 fires in full. Either way the plan
proceeds without user-approval pause.
2. Task A2 reframed — Wiener-α conviction-EMA is a "load-bearing
component of continuous control," not a "minimal Phase B subset."
Without smoothing, event-rate trading is structurally incoherent.
3. Task A2 test fallback REMOVED — instead of "if helpers don't
exist, omit the unit test," the plan now says "add the helpers
properly to the public API." Step 1 audits the LobSimCuda public
API and adds missing accessors. Greenfields — accessors stay on
the API permanently if testing needs them.
4. Task A5 (conditional hyperactivity mitigation) DELETED. A2 is
designed correctly the first time with Wiener-α floor at 0.4. If
A4 cluster smoke shows hyperactivity, that's an A2 bug to fix
properly, not a tuning knob to nudge.
5. Scope contract updated — Phase A vs Phase B split is by code-path
responsibility (continuous control infrastructure vs multi-horizon
signal-driven policy), NOT by "shipping less to be safe."
6. Notes for the Implementer — explicit "No fallbacks" section
replaces the implicit-fallback language. STOP-and-notify-user for
Case 2 deleted (A0.5 handles it inline).
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Per docs/superpowers/specs/2026-05-20-continuous-reasoning-trader-design.md
(v2, commit 8ba8755b4). One plan per phase per writing-plans guidance —
Phase B/C/D plans written after each prior gate closes.
Phase A scope:
A0 - Investigate forward_only cost model (read-only research,
writes memo to docs/superpowers/memos/). STOP condition if
trunk forward is stateless K-window per call (Case 2) —
requires user approval to expand scope.
A1 - Atomic delete of decision_stride (greenfields, no compat).
Removes from SweepBase, ResolvedSimVariant, BatchedSimConfig,
BacktestHarness, all YAMLs.
A2 - Minimal Wiener-α conviction-EMA smoothing in decision_policy_*
kernels. Three new device slots: conviction_ema_d,
conviction_diff_var_ema_d, conviction_sample_var_ema_d. Floor
at 0.4 per pearl_wiener_alpha_floor_for_nonstationary.
First-observation bootstrap. Direction stays from raw alpha;
magnitude/sizing uses smoothed value.
A3 - Local compile + tests.
A4 - Cluster smoke + Gate 1 validation against spec §3.6 acceptance.
Memory entry on closure (green/red/yellow).
A5 - Conditional hyperactivity mitigation (raise floor 0.4→0.6 OR
add target-delta hysteresis). Fires only if Gate 1 reveals
trade-count balloon.
Out of scope (deferred): full §4.4 multi-horizon conviction formula,
§4.3 conviction-degradation exit, §5 envelope, §6 LoRA adapter, §7
open_trade_state expansion — all Phase B/C/D.
Pearl conformance:
- feedback_no_partial_refactor (atomic delete)
- feedback_no_legacy_aliases (no compat shim)
- feedback_push_before_deploy
- pearl_wiener_optimal_adaptive_alpha
- pearl_wiener_alpha_floor_for_nonstationary
- pearl_first_observation_bootstrap
- feedback_stop_on_anomaly (Gate 1 RED → diagnose, don't advance)
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>
11 tasks, each one commit, TDD-disciplined (test → fail → impl →
pass → commit). Covers all 11 sections of the spec at
docs/superpowers/specs/2026-05-19-isv-driven-stop-controller-design.md:
- Tasks 1-2: state slots + ATR EMA in book_update_apply_snapshot
- Task 3: stop_check_isv shared __device__ helper skeleton
- Tasks 4-6: SL trigger, trail-TP + HWM ratchet, multi-horizon avg
- Task 7: bytecode VM parity (wire helper into decision_policy_program)
- Task 8: seed_inflight_limits_batched target-delta + in-flight summation
- Task 9: pnl_track_step trail_hwm reset on close
- Task 10: atomic deletion of StopRules + use_cold_start_stopgap +
integration-test retarget + CBSW SUPERSEDED markers
- Task 11: cluster smoke validation via argo-lob-sweep.sh
All 10 §9.1 unit tests have explicit failing-test scaffolds before
their implementations, and the retargeted integration test
(cold_start_persistent_bullish_now_closes) flips the assertion to
prove the fix.
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>
4-task atomic ladder (Q1-Q4) implementing spec 566e8bcb0. Each task
maps to one commit per feedback_no_partial_refactor:
Q1: Cold-start stopgap (bytecode max-confidence policy upload)
Q2: CBSW kernel aggregator + Tier 1 revert (atomic)
Q3: Memory pearl pearl_conviction_bootstrap_for_kelly_aggregation
Q4: Parallelism spec §3.4 cross-reference
Kernel ABI unchanged across all 4 commits — Q2 modifies only
decision_policy_default's body (decision_policy_program left as a
pluggable bytecode-VM experiment surface). Q2 atomically deletes
the Q1 stopgap field/CLI/YAML/harness branch in the same commit
that lands the kernel fix (feedback_no_legacy_aliases compliance:
grep returns zero hits for use_cold_start_stopgap post-Q2).
Validation gates per spec §9:
- Q1: cluster smoke n_trades > 100, total_pnl != 0 (diagnosis
confirmation). If n_trades = 0 still, STOP — downstream bug.
- Q2: pre-existing 11 CUDA tests still pass; 7 new cbsw_*
regression tests pass; cluster smoke n_trades > 100; ev/s
rate ratio Q2/Q1 ≥ 0.95.
Self-review confirms all 11 spec sections covered, no placeholders,
type/signature consistency across tasks.
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>
Concrete TDD-driven commit map for the v2 spec
(2026-05-18-ml-alpha-v2-multi-horizon-design.md). Thirteen commits
ordered by dependency: delete falsified path, build new kernels with
numgrad parity (V2-V8), trainer state bundle (V9), wire into
PerceptionTrainer (V10), local smoke (V11), cluster smoke (V12), 3-fold
A/B (V13). Per-commit verification gates and explicit stop conditions.
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>
User directive 2026-05-17: borrow TFT GRN over the planned 2-layer MLP heads.
GRN structure: 2-layer GELU MLP body (eta_2 → eta_1) + GLU gate + main +
skip-projection from trunk → final sigmoid. Gives per-horizon "linear vs
deeper-transform" gating, matches the regime-conditional alpha pattern
(pearl_snapshot_alpha_is_regime_conditional). 5x parameter count vs the
2-layer MLP but the gated residual is exactly what TFT empirically wins on.
Phase 2C (TGN Δt Fourier features): 8 sin/cos features of Δt at log-spaced
periods [60s, 6s, 600ms, 60ms] appended to snap_features. Critical with
decision-stride>1 where Δt varies across positions. Bumps FEATURE_DIM 32→40.
Phase 2D (TFT VSN): per-feature softmax-normalised gates at the trunk entry,
replacing raw concat of snap_features. Learns to down-weight noisy
features per regime (canonical: trade-flow in low-volume, OFI in
spread-Q4). 2 new param tensors, 1 new cuda kernel (fwd+bwd).
Existing 2-layer MLP kernels from Tasks 1.3/1.4 stay in the cubin as
ablation baseline; wired path becomes GRN.
Phase 1.7 plan now spells out the full GRN forward + backward chain rule
(skip + sigmoid(gate) * main → outer sigmoid), kernel signatures,
parameter Xavier init, AdamW × 10 setup, and an extended numerical-grad
check covering all 10 new param tensors.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
