a448e03e64
Root cause of NaN at step 22: cuBLAS out-of-bounds reads in the GPU experience collector and training forward pass, caused by buffer dimension mismatches that produced garbage states → garbage Q-values → NaN loss. Bugs fixed: 1. GpuDqnTrainConfig::default() had bottleneck_dim=2, market_dim=42 — collector computed s1_input_dim=40 instead of state_dim=80, cuBLAS read 2x past W1 weight buffer (10KB OOB per SGEMM) 2. batch_states allocated with state_dim=80 but cuBLAS ldb=128 (CUTLASS K-tile alignment) — 48 bf16/f32 values read past end per row 3. Validation state tensor had 59 elements/row (42+3+8+6) instead of 128 (state_dim_padded) — missing portfolio/MTF features + padding 4. CUTLASS K-tile overread on all hidden activation buffers (K=64 but tile=128) — added 128-element padding to 14 bf16 buffers 5. init_from_fxcache never set self.ofi_features — collector OFI buffer was 1-element placeholder, state_gather kernel read OOB 6. collect_gpu_experiences_slices missing *2 counterfactual multiplier — half of collected experiences never inserted into PER Dead code removed (~1228 lines): - train_with_data_full_loop (old Vec<(FeatureVector, Vec<f64>)> loop) - init_gpu_data, init_gpu_raw_buffers, collect_gpu_experiences, run_training_steps (old helpers only called by above) - train_with_preloaded_data, train_with_shared_data (old hyperopt APIs) - train() and train_walk_forward() now convert to fixed-size arrays and route through init_from_fxcache + train_fold_from_slices Other fixes: - precompute_features defaults output-dir to sibling of data-dir - workspace_root() + feature_cache_dir() helpers for reliable path resolution (works from any cwd, with/without CARGO_MANIFEST_DIR) - Production smoketest uses fxcache (no slow DBN parsing) - compute-sanitizer: 0 errors (was 2539) Co-Authored-By: Claude Opus 4.6 (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.