e15adecef1
The `val_picked_dir_dist` reader added in 89ece2e36 read `chunked_actions_buf`
which is overwritten each chunk, so the diagnostic only saw the last ~64 bars
of the 214 654-bar val window. The cluster's run-after-run identical
distribution (`s=0.0001 h=0.20 l=0.0000 f=0.80` post-physics; `s=0.18 h=0.18
l=0.41 f=0.22` last-chunk picks) was therefore inconclusive: the post-physics
flatness covers the full window, but the pick-side diversity may only hold for
the last 64 bars while the first 99.97% of bars produce a different
distribution.
Add `picked_action_history_buf` — a window-major `[n_windows, max_len]` i32
buffer parallel to `actions_history_buf`. Filled by an additional
`scatter_intent_chunk` launch immediately after the existing intent-mag
scatter (same kernel handle, different src/dst — `chunked_actions_buf` →
`picked_action_history_buf`). One extra kernel launch per chunk; the launch
config and grid sizing are identical to the existing intent scatter.
The reader `read_chunked_actions_direction_distribution` now reads this
buffer instead of the chunk-local one. The HEALTH_DIAG line stays at
`val_picked_dir_dist [short=... hold=... long=... flat=...]` but now
reflects the full val window.
Decision matrix once the cluster reports the new diagnostic:
both `val_dir_dist` and `val_picked_dir_dist` show ~80% Flat
→ kernel itself produces collapsed picks across the window;
Q-values must be near-uniform for most bars; the eval-collapse is
a learning problem (network can't differentiate states).
`val_picked_dir_dist` diverse but `val_dir_dist` ~80% Flat
→ kernel is diverse, env_step drains active picks; the eval-collapse
is a physics problem (Kelly cap or another gate I haven't found).
Build clean at 11-warning baseline. No new kernel source, no determinism
contract change.
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.