cffc95152c73daf6c25a53074566c4ebb3fbbf30
Bite-sized 12-task runbook for the recentering fix specified in `docs/plans/2026-05-12-sp22-h6-phase2-recenter.md`. Tasks 1-5 are the 5 atomic edits (kernel write recentered to `2*p - 1`, sentinels 0.5 → 0.0 across host + 3 NULL-fallback kernels, plus comment updates in state_layout.rs / state_layout.cuh). Tasks 6-8 are the three verification gates (cargo check / gpu_backtest_validation / compute-sanitizer) identical to H6 Phase 1 — all required clean before commit. Task 9 appends the H6 Phase 2 entry to the audit doc (Invariant 7 satisfaction). Task 10 is the single atomic commit per `feedback_no_partial_refactor` covering all 5 source files + audit doc. Task 11 dispatches the 3-epoch baseline smoke on ci-training-l40s. Task 12 monitors for the cycle-1 verdict using the same single-channel grep-anchored bg waiter pattern as Phase 1 (per `feedback_no_redundant_monitor`). Every task has exact file paths, complete code blocks for edits (showing old + new strings for Edit-tool consumption), exact commands with expected output, and explicit kill criteria for verification gate failures. 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%