10e647c141
C.8 (ISV-driven aux trunk Adam β1/β2/ε/LR/grad-clip) was already complete in C.5a
commit c90de9859 — all 5 ISV reads and fold-boundary StateResetRegistry defaults were
wired atomically with the Adam launcher. No new code required; noted in audit doc.
C.9 adds `aux_trunk_learns_synthetic_uptrend` to aux_trunk_oracle_tests.rs:
- B=16, ENC=32, H1=32, H2=16, SH2=32, H_HEAD=32, K=2, 100 steps
- Backward kernel invocations corrected to match actual signatures:
- aux_trunk_bwd_dh_pre(d_logits, w3, w2, h_aux1, h_aux2, dh_pre2, dh_pre1, B, H1, H2, SH2)
shmem = H2 floats (sh_dh2_pre cache), NOT (H1+H2+SH2)
- aux_trunk_bwd_dW_reduce called 3×: dW3/dW2/dW1 each with (A, B_grad, dW_out, B, Krows, Jcols)
- aux_trunk_bwd_db_reduce called 3×: db3/db2/db1 each with (B_grad, db_out, B, Jcols)
- Head params trained via host-side SGD (test orchestration only; reads mapped-pinned partials)
- Trunk params trained via dqn_adam_update_kernel (GPU Adam)
- Pass gate: CE loss < 0.1 AND dir_acc > 0.95 after 100 steps
Near-random baseline (ln(2)≈0.693) = broken gradient chain, L40S dispatch blocked
Memory pearl pearl_separate_aux_trunk_when_shared_starves.md added and indexed.
Co-Authored-By: Claude Sonnet 4.6 <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.