a6087a0b23
Wires E6 (compute_winner_indices) + E7 (compute_hindsight_labels) outputs into the PER priority update kernel via signal-driven ISV slots. Phases 5 and 6 combined into one atomic commit per feedback_no_deferrals_for_complementary_fixes — both attack the same consumer kernel (per_update_pa) with non-overlapping refactor scopes (E6 contributes one ISV-mediated scalar, E7 contributes another, kernel composes both into alpha_boost). Plan revision (briefed and accepted 2026-05-11): - E6's literal Vec<usize> of val bar indices CANNOT directly bump training-PER priorities — val and training have separate coord systems (no bar-index → buffer-slot mapping). - E7's true synthetic injection requires val state retention infrastructure (n_windows × max_len × state_dim scratch buffer) — significant scope expansion deferred to Phase 6.5. - The MEANINGFUL signal in both phases is scalar aggregations of the per-trade tape: E6 winner concentration (top-decile-mean P&L / all-mean P&L) and E7 hindsight magnitude (mean |counterfactual_pnl|). Both compose multiplicatively into per_update_pa's alpha_eff. ISV slot allocation: - WINNER_CONCENTRATION_INDEX = 525 - HINDSIGHT_MAGNITUDE_INDEX = 526 - ISV_TOTAL_DIM 525 → 527 (bus extension) - Layout fingerprint adds 2 SLOT entries - Compile-time test asserts SP21_SLOT_END (527) ≤ ISV_TOTAL_DIM Signal semantics: - winner_concentration: top_decile_mean_pnl / max(all_mean_pnl, EPS). > 1.0 = top decile dominates; ≈ 1.0 = uniform; ≤ 0 → 0.0 sentinel (losing strategy, signal ill-defined). - hindsight_magnitude: mean(|counterfactual_pnl|). Higher = larger missed opportunities. - Cold start: both at 0.0 sentinel; kernel short-circuits to alpha_eff = alpha (no-op). ABI surgery (minimal): - per_update_pa: ONE new arg `const float* __restrict__ isv_signals` at end. NULL-tolerant. Reads slots 525/526 device-side, composes boost_delta (bounded [0, 0.4]), applies alpha_eff = alpha + delta. - update_priorities_gpu launcher: passes existing self.isv_signals_dev_ptr (already on struct, settable via set_isv_signals_ptr — same infra per_insert_pa uses for recovery_oversample). Zero new public API. Producer wireup: - enrichment.rs: 2 new helpers (compute_winner_concentration, compute_hindsight_magnitude); EnrichmentResult gains 2 fields (winner_concentration, hindsight_magnitude); run_enrichments populates both; log line extended. - training_loop.rs: post-enrichment block writes both ISV slots via fused.trainer().write_isv_signal_at. Files changed: - crates/ml/src/cuda_pipeline/sp21_isv_slots.rs: +2 slot consts - crates/ml/src/cuda_pipeline/gpu_dqn_trainer.rs: ISV_TOTAL_DIM bump + fingerprint - crates/ml-dqn/src/per_kernels.cu: per_update_pa ABI + boost logic - crates/ml-dqn/src/gpu_replay_buffer.rs: launcher passes ISV ptr - crates/ml/src/trainers/dqn/trainer/enrichment.rs: 2 helpers + 2 fields + populate - crates/ml/src/trainers/dqn/trainer/training_loop.rs: write 2 slots - docs/dqn-wire-up-audit.md: 2026-05-11 audit entry Verification (passing): - cargo check -p ml --tests --features cuda: 0 errors - cargo test -p ml --lib sp21_isv_slots: 3/3 - sp20_aggregate_inputs_test: 12/12 - sp20_phase1_4_wireup_test: 2/2 - sp20_emas_compute_test: 4/4 - sp20_controllers_compute_test: 7/7 - sp21_per_trade_predicted_q_test: 3/3 Total: 34 tests, 0 failures. Behavioral gate (alpha_eff lift on post-warmup val passes) is the upcoming smoke training run. Deferred follow-up (Phase 6.5): true E7 hindsight synthetic experience injection via val state retention + per_insert_pa extension. Significant infrastructure (n_windows × max_len × state_dim scratch + insert API extension). Documented in audit. After this commit (T2.2 Phases 7-8 + 6.5 deferred): - Phase 7: E8 curriculum weights → segment sampling - Phase 8: signal-drive remaining controller GAINS - Phase 6.5: synthetic hindsight injection (deferred — needs val state buffer infrastructure) Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Foxhunt
Production HFT trading system in Rust.
Architecture
The workspace contains 32 crates organized as follows:
Core Libraries (16)
| Crate | Purpose |
|---|---|
trading_engine |
Order processing, FIX 4.4, IB TWS, SIMD, RDTSC timing |
risk |
VaR, Kelly, circuit breakers, kill switches, compliance |
risk-data |
Risk data types and shared structures |
trading-data |
Trading data types |
ml |
DQN Rainbow, PPO, TFT, Mamba2, ensemble inference |
ml-data |
ML data types and feature definitions |
data |
Market data ingestion and storage |
backtesting |
Replay engine, strategy tester |
adaptive-strategy |
Ensemble execution, microstructure analysis |
common |
Shared types, resilience, error handling |
storage |
S3 and local model storage |
model_loader |
Model serialization and loading |
market-data |
Market data feed handlers |
database |
PostgreSQL access layer (SQLx) |
config |
Configuration management |
tli |
CLI commands and tooling |
Services (8)
| Service | Purpose |
|---|---|
backtesting_service |
gRPC backtesting service |
broker_gateway_service |
FIX routing, broker connectivity |
trading_service |
Core trading operations |
ml_training_service |
Model training orchestration |
data_acquisition_service |
Market data acquisition |
trading_agent_service |
Autonomous trading agents |
api_gateway |
gRPC API gateway with auth |
web-gateway |
Axum REST + WebSocket gateway |
Frontend
web-dashboard/ -- React 19 + TypeScript + Vite + TradingView charts.
Building
# Check compilation (no PostgreSQL required)
SQLX_OFFLINE=true cargo check --workspace
# Run tests for a specific crate
SQLX_OFFLINE=true cargo test -p <crate> --lib
# Clippy
SQLX_OFFLINE=true cargo clippy --workspace
ML Models
Four production model architectures on Candle v0.9.1 with CUDA:
- DQN Rainbow -- Deep Q-Network with prioritized replay, dueling heads, noisy nets
- PPO -- Proximal Policy Optimization with GAE and LSTM policies
- TFT -- Temporal Fusion Transformer for multi-horizon forecasting
- Mamba2 -- State space model for sequence prediction
Each model has a standalone trainer and a UnifiedTrainable adapter for the hyperopt pipeline.
Infrastructure
- Git: Gitea at
git.fxhnt.ai(Tailscale-only), Scaleway DEV1-S - Observability: OpenTelemetry OTLP (env
OTEL_EXPORTER_OTLP_ENDPOINT) - Database: PostgreSQL with SQLx offline mode for CI
License
Proprietary. All rights reserved.