adc3506d3e
Atomic refactor wiring the GPU log ring's first producer end-to-end: - cuda/gpu_log_helpers.cuh (new): extract LogHeader/LogRecord/LogRing struct definitions + the log_record() device __forceinline__ helper into a shared header. Single source of truth — other kernels include this rather than redefining the structs. - cuda/gpu_log_ring.cu: refactor to include gpu_log_helpers.cuh; retain only the gpu_log_tick kernel. - cuda/smoothness_lambda_controller.cu: include gpu_log_helpers.cuh, add trailing (LogRing*, const int*) args, capture pre-EMA jitter + post-EMA jitter + target + excess_ratio into shared mem, and emit three records per call (RT_INPUT, RT_STATE, RT_OUTPUT) gated on non-null ring pointer. - trainer/perception.rs: feature-gated (cuda-diag-log) ring allocation + step counter (mapped-pinned host shadow), gpu_log_tick launch FIRST inside the captured graph, two new pointer args on the smoothness controller launch (null when feature off), step-counter DtoD shadow alongside the other telemetry shadows, drain task spawn (skipped when no tokio runtime — sync tests still construct the trainer), and a feature-gated Drop impl that aborts the drain task on shutdown. - tests/smoothness_lambda_controller_invariants.rs: pass null pointers for the two new kernel args; the kernel's nullptr guard preserves pre-existing behaviour. - build.rs: rerun-if-changed on cuda/gpu_log_ids.h and cuda/gpu_log_helpers.cuh so header edits trigger cubin rebuilds. Verified: cargo build / check --all-targets clean both with and without the cuda-diag-log feature; 4/4 smoothness controller invariant tests pass; 9/9 perception_overfit integration tests pass under the feature. 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.