fbf48df9de
Replaces A2's CudaSlice<u64>/<i32> field types with MappedU64Buffer/ MappedI32Buffer per feedback_no_htod_htoh_only_mapped_pinned. Mapped- pinned eliminates the HtoD copy entirely — the kernel reads via the device-mapped pointer (cuMemHostGetDevicePointer_v2) while the trainer writes through the same mapped pages on the host side. Adds populate_nan_check_meta on GpuDqnTrainer (one-shot construction- time write of 12 (ptr, len) tuples for slots 24-35). Slot 31 deferred (null entry); slots 27/28 nullable on Option<u64> (None when IQN inactive); slots 33-35 null (inline checks fire separately at backward orchestration phases — kept individual for entry-point localization). Adds launch_nan_check_fused_f32 (per-step kernel launch wrapper with grid_dim=12, block_dim=256, base_flag_idx=24). Registers dqn_nan_check_fused_f32_kernel in compile_training_kernels (tuple 43→44, info log 38→39 utility kernels) — same module as the per-buffer dqn_nan_check_f32 to share the captured replay group. Constructor-time wire-up lands in FusedTrainingCtx::new after gpu_iqn construction (gpu_iqn is owned by FusedTrainingCtx, not GpuDqnTrainer — mirrors the same Option<u64> arg pattern used by apply_iqn_trunk_gradient and run_nan_checks_post_backward). Wrapper unused yet — call-site replacement (8 individual check_nan_f32 calls in run_nan_checks_post_backward → single fused launch) lands in A4. Audit doc updated (Invariant 7). 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.