0e61de408f
Single-block 256-thread CUDA kernel computing RMS(h_s2_aux [B, SH2]) and EMA-blending the step observation into ISV[H_S2_AUX_RMS_EMA_INDEX=449] directly. Pearl-A first-observation bootstrap embedded in kernel body (sentinel 0.0 → replace); fixed α=0.05 EMA blend thereafter. ISV slot 449 is outside the SP4/SP5 wiener buffer linear span so the scratch+apply_pearls_ad_kernel path is not available — self-contained Pearl-A logic mirrors the avg_win_hold_time_update_kernel precedent (slot 451). No atomicAdd; shmem block-tree-reduce only. Launched after aux_trunk_forward in the collector per-step hot path. - h_s2_aux_rms_ema_kernel.cu — new CUDA kernel (81 lines) - build.rs — cubin manifest entry - gpu_dqn_trainer.rs — H_S2_AUX_RMS_EMA_CUBIN static - gpu_aux_trunk.rs — HS2AuxRmsEmaOps struct + launch() - gpu_experience_collector.rs — field + constructor + hot-path launch - aux_trunk_oracle_tests.rs — h_s2_aux_rms_ema_pearl_a_bootstrap test - dqn-wire-up-audit.md — Phase C.6 audit entry cargo check -p ml --tests: clean (only pre-existing warnings) Oracle test: 1 new test added (requires GPU to run) Co-Authored-By: Claude Sonnet 4.6 <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.