0ec791734d
Bug audit Pattern 2 — 6 SP15 launchers in gpu_dqn_trainer.rs were doing load_cubin + load_function PER CALL inside the launcher body, called from gpu_experience_collector.rs's per-rollout-step body (~thousands of times per epoch x 4096 envs x 1000 timesteps). Same architectural bug class as commits5d63762ab(bn_tanh_concat_dd) and1396b62ec(sp15_baseline + cost_net). load_cubin/load_function are host-side driver API calls — not capturable inside graph capture, and prone to CUDA_ERROR_ILLEGAL_ADDRESS in subprocess child contexts (documented failure mode in1396b62ec). Migration: - launch_sp15_dd_state, launch_sp15_dd_state_reduce, launch_sp15_dd_trajectory_decreasing, launch_sp15_alpha_split_producer, launch_sp15_final_reward, launch_sp15_plasticity_injection — signatures changed to accept &CudaFunction parameter. - Collector struct gains 6 new pre-loaded CudaFunction fields, populated once in collector::new() (mirrors SP14 EGF kernel loading added in commit09202aa99). - All 6 hot-path call sites updated to pass &self.exp_<kernel>_kernel reference (5 in collect_experiences_gpu, 1 in plasticity-injection trigger path). - Oracle tests in sp15_phase1_oracle_tests.rs pass through a small load_sp15_kernel test helper that inlines the per-call load (graph capture isn't a concern in oracle scaffolds; production callers use struct-cached handles via the collector). - docs/dqn-gpu-hot-path-audit.md gains Fix 29 documenting the pattern, the 6 migrated sites, deferred evaluator launchers, and out-of-scope orphan launchers. Per feedback_no_partial_refactor: all 6 launchers + their callers migrate atomically. Per pearl_no_host_branches_in_captured_graph: zero load_cubin in collector per-rollout-step body after this commit. Deferred (separate scope): launch_sp15_sharpe_per_bar and launch_sp15_position_history_derivation are evaluator-path callers (GpuBacktestEvaluator) — fixing them requires adding fields to a different struct, deferred to a separate atomic commit. Orphan launchers (regret_signal, cooldown) have no production callers; left untouched. Cubin static visibility: all 6 affected SP15 cubins were already pub static (collector imports work without visibility promotion). Verification: cargo check clean (only pre-existing warnings); 7/7 sp14_oracle_tests pass; 36/36 sp15_phase1_oracle_tests pass. 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.