f75786fc5a
c51_grad_kernel.cu line 275: lift floor from 1e-6 to 1e-3 in \`inv_a_std = 1.0f / (a_std + 1e-3f)\`, capping the magnitude-branch gradient amplifier at 1000 instead of ~1e6 in the degenerate case. Why: Smoke A produced 1109 GRAD_CLIP_OUTLIER events with C51 grad reaching 9.5e6 — the SP7 budget controller saturated at the EPS_DIV floor instead of rebalancing proportionally. Phase-0 verification against the actual kernel found the amplifier is NOT the spec's claimed −log(p)/p divide (which does not exist; the kernel uses the CE-stable expf(lp) - proj form at line 81). The actual amplifier is inv_a_std = 1/(a_std + 1e-6) at line 275, gated by \`if (d == 1) grad_val *= inv_a_std\` at line 282. When magnitude advantage logits collapse near-uniform (Smoke A: var_q=9e-10), a_std → ~1e-9, so inv_a_std → ~1e6. Per feedback_isv_for_adaptive_bounds, this is a numerical-stability anchor (Invariant 1: prevent division-by-near-zero amplification), not a behavioural bound. ISV-driven bounds govern behavior; the existing 1e-12f floor on a_std at line 274 is also a structural anchor — same class of fix. Validation gate: Smoke A2-A GRAD_CLIP_OUTLIER count <100 in fold 2 (was 1109 pre-fix). The 3-order-of-magnitude reduction in worst- case amplification should bring C51 grad spikes back under SP7 budget controller authority. Audit doc: Fix 40 added (parallel to Fix 39 for A.2 and Fix 41 for A.3); the stale "A.1 deferred" note was removed in the A.3 commit. 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.