37964ae2a4
Path (B) Commit A — additive infrastructure for the SP19 producer-side
multi-horizon reward augmentation. Three ISV slots reserve indices for
a future Path (A) refactor that would let a controller drive per-batch
horizon weights; producer (Commit B) hardcodes equal-thirds 1/3 each at
fxcache-write time so the slot reservations are dormant in this branch.
Pure additive — changes NO runtime behaviour. The dispatch arms write
the equal-thirds sentinel at every fold boundary, but no kernel
consumes the slots. This is forward-compatible reservation per
feedback_isv_for_adaptive_bounds, NOT a half-fix; the producer wiring
is complete (next commit), the slot reservations are documented
forward-compatibility for the TARGET_DIM-bumping refactor.
Slot allocation:
- 507 REWARD_HORIZON_WEIGHT_1BAR_INDEX sentinel = 1/3
- 508 REWARD_HORIZON_WEIGHT_5BAR_INDEX sentinel = 1/3
- 509 REWARD_HORIZON_WEIGHT_30BAR_INDEX sentinel = 1/3
Touches:
- crates/ml/src/cuda_pipeline/sp14_isv_slots.rs: 3 slot constants +
sentinel + range markers + sp19_reward_horizon_slot_layout_locked +
all_sp19_slots_fit_within_isv_total_dim lock tests.
- crates/ml/src/cuda_pipeline/gpu_dqn_trainer.rs: ISV_TOTAL_DIM 507 →
510 + layout_fingerprint_seed extension (3 SLOT_* lines + a
SP19_PRODUCER_HARDCODED_HORIZON_BLEND token registering producer-time
consumption).
- crates/ml/src/cuda_pipeline/state_layout.cuh: 3 #define mirrors of
the Rust slot indices + SENTINEL_REWARD_HORIZON_WEIGHT_DEFAULT macro.
- crates/ml/src/trainers/dqn/state_reset_registry.rs: 3 RegistryEntry {
FoldReset } with the "SP19 Path (B) reservation" marker + lock-test
expansion 24 → 27 entries.
- crates/ml/src/trainers/dqn/trainer/training_loop.rs: 3 dispatch arms
in reset_named_state writing SENTINEL_REWARD_HORIZON_WEIGHT_DEFAULT.
- docs/dqn-wire-up-audit.md: SP19 Commit A entry documenting the
reservation rationale + verification steps.
Verification:
SQLX_OFFLINE=true CUDA_COMPUTE_CAP=86 cargo check --workspace clean
cargo test -p ml --lib sp19_reward_horizon_slot_layout_locked passes
cargo test -p ml --lib all_sp19_slots_fit_within_isv_total_dim passes
cargo test -p ml --lib sp18_fold_reset_entries_present passes (27)
cargo test -p ml --lib every_fold_and_soft_reset_entry_has_dispatch_arm passes
bash scripts/audit_sp18_consumers.sh --check exit 0
Atomic-refactor invariant (HARD — feedback_no_partial_refactor): NO
L40S DISPATCH between Commit A and Commit B. The producer-side blend
+ fxcache version bump + behavioural test land in the next commit on
this branch.
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.