6c3a91c878
The SP7 controller's CQL reference signal was reading cql_sx (post-SAXPY, budget-scaled) which created a self-perpetuating deadlock at small budget values: cql_sx_norm = budget × raw_grad → small budget → small cql_sx → controller can't update → budget stays small. The earlier offset 6 → 3 attempt failed because grad_decomp_launch_cql was never effectively populating slot 3 — the snapshot pattern measures ‖grad_buf − snapshot‖, but apply_cql_gradient writes to cql_grad_scratch (separate buffer), not grad_buf, so the snapshot delta is always 0. This commit adds a real producer kernel cql_raw_norm_compute that reads cql_grad_scratch directly and computes ‖raw_cql‖ over mag/dir/trunk slices. Wired to fire AFTER apply_cql_gradient and BEFORE apply_cql_saxpy, populating grad_decomp_result_pinned[3..6] with the raw norm independent of cql_budget. SP7 launcher updated to read from offset 3 (now: real raw CQL norm, not the never-populated cql snapshot delta). HEALTH_DIAG label renamed cql_sx → cql_raw to reflect the new contract; component index in the cached grad_component_norms_* arrays switched 2 → 1. The historical grad_decomp_launch_cql() call is removed — keeping it would overwrite the slot with 0 after cql_raw_norm_compute fires. The paired grad_decomp_snapshot_cql snapshot is left in place to scope the diff to Path A; buffer cleanup (grad_snapshot_cql allocation + grad_decomp_launch_cql definition) belongs in a follow-up commit per feedback_no_partial_refactor. Files: cql_raw_norm_kernel.cu (new, 97 LOC), build.rs, gpu_dqn_trainer.rs (struct field + cubin static + load + launcher + SP7 read offset 6→3), loss_balance_controller_kernel.cu (docstring + arg comment), fused_training.rs (4 launch_cql_raw_norm call sites, 1 dead grad_decomp_launch_cql call removed), training_loop.rs (HEALTH_DIAG label + index), audit doc Fix 31 SP7 Path A entry. 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.