29a2615f6a8782da8a39473a3db4877ba0aebf2c
Lands the producer-side infrastructure for SP20 Phase 2's 4-quadrant
reward kernel (Task 2.2):
* New `[alloc_episodes]` `i32` device buffer `label_at_open_per_env`
on `GpuExperienceCollector`, allocated alongside `episode_starts_buf`.
* Two new `experience_env_step` kernel args (`aux_label_per_env` input,
`label_at_open_per_env` output), threaded into the launch site.
* Write site at the `entering_trade` branch maps the upstream aux
next-bar label (`{0,1,-1}` from `aux_sign_label_per_step_kernel`) to
the SP20 spec sign convention (`{-1,+1,0}`) per spec §4.1.
* StateResetRegistry entry `label_at_open_per_env` (FoldReset) +
`reset_named_state` dispatch arm via `stream.memset_zeros`.
* Registry invariant test `sp20_label_at_open_per_env_registered_fold_reset`
pins the FoldReset category + key description anchors.
* Audit-doc entry documents the design rationale (why per-env buffer
vs. derived-at-trade-close read), sign mapping, FoldReset semantics,
kernel-arg threading, and Task 2.1/2.2 forward references.
Producer-only this commit. The consumer (`is_close` branch reading
`label_at_open_per_env[i]` and passing to `sp20_compute_event_reward`)
lands atomically with the SP12 v3 reward block replacement in Task 2.2,
per `feedback_no_partial_refactor`.
NULL-tolerant kernel arg pair lets test scaffolds without aux-head
wiring continue to work; the FoldReset-zeroed buffer reads as sentinel
0 at the consumer (which Task 2.2 maps to "no info" / wrong-reason
quadrant — safer default than over-rewarding a no-signal trade).
Verification:
SQLX_OFFLINE=true cargo check -p ml # clean
SQLX_OFFLINE=true cargo test -p ml --lib sp20 # 18/18 (+1 new)
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.
Description
Languages
Rust
88.2%
Cuda
7.7%
Python
1.3%
Shell
1.1%
PLpgSQL
0.8%
Other
0.8%