108a426c38
First Rust-side commit of Phase B for the SP22 H6 vNext trade-outcome aux head. Pure orchestrator scaffolding mirroring AuxHeadsForwardOps / AuxHeadsBackwardOps. Zero production callers — additive per the gpu_grn / aux_trunk commit-by-commit ordering convention (scaffold → trainer fields → collector wireup). Adds: - gpu_dqn_trainer.rs: 4 cubin embeds (TRADE_OUTCOME_LABEL_CUBIN, AUX_TRADE_OUTCOME_FORWARD_CUBIN, AUX_TRADE_OUTCOME_LOSS_REDUCE_CUBIN, AUX_TRADE_OUTCOME_BACKWARD_CUBIN). All #[allow(dead_code)] until B1+. - gpu_aux_heads.rs: AUX_OUTCOME_K = 3 constant (parallel to AUX_NEXT_BAR_K). - gpu_aux_heads.rs: AuxTradeOutcomeForwardOps struct holding 3 kernel handles (forward + loss_reduce + label producer). Launch methods: forward(), loss_reduce(), compute_label(). Per-env label kernel uses grid ceil(n_envs/256) — pure per-env map, no reduction. - gpu_aux_heads.rs: AuxTradeOutcomeBackwardOps struct holding 1 kernel handle (backward). Launch method: backward(). Reuses existing K-generic aux_param_grad_reduce from AuxHeadsBackwardOps — no separate reducer needed. Contract shapes mirror AuxHeadsForwardOps/AuxHeadsBackwardOps so subsequent wireup commits plug in with minimal contract drift. Phase B proper (input concat 256→262 with plan_params) becomes a small change touching only the buffer fill + W1 shape once B1-B4 land the wireup. Phase B1 next: trainer struct fields for W1/b1/W2/b2 + Adam state + Xavier init + reset registry entries. Audit: docs/dqn-wire-up-audit.md Phase B0 section. Cargo check clean (21 warnings, none new). 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.