5309d4bee53f07afbaed50f2ccb9a2acf146b46e
LAYOUT FINGERPRINT BREAK: pre-SP15 checkpoints WILL NOT LOAD after this commit. Greenfield OK per spec Q1. Per spec §6.5: dd_pct (slot 406, written by Task 1.3 dd_state_kernel) gets concatenated to the trunk forward input as the last dim. Eval-time policy SEES drawdown context on every forward pass; Phase 3 teachings can condition on dd_pct directly via state, not just reward modulation. New kernel `dd_pct_concat_kernel.cu` produces a [B, state_dim_padded + 1] buffer whose leading state_dim_padded columns equal the input states_buf and whose +1 last column equals isv[DD_PCT_INDEX=406] broadcast across batch. Pure scatter-copy (no atomicAdd per feedback_no_atomicadd). layout_fingerprint_seed extended with 'TRUNK_INPUT_DD_PCT=sp15_phase_1_5' marker — FNV1a hash changes; old checkpoints fail to load with the existing layout-mismatch error path (same fail-fast that fired on the SP4 / SP14 layout breaks). Phase 1.5 lands kernel + launcher + layout fingerprint marker + GPU oracle test only. Trunk consumer migration (re-pointing forward_online to consume the concat buffer + bumping s1_input_dim from 48 → 49 + propagating through GRN encoder, VSN gate input, bottleneck path, and backward dx scratch) is deferred to a follow-up atomic commit per feedback_no_partial_refactor — matches the established Phase 1.1-1.4 precedent (kernels + launchers verify in isolation first; consumer migration is a load-bearing change touching the GRN encoder, VSN partition boundaries, fxcache schema, and backward gradient flow). GPU oracle test `dd_pct_concat_kernel_writes_last_column` validates B=4, raw state_dim=48, state_dim_padded=128: leading 128 columns of each output row match the input states (including pad zeros), and the 129th column equals isv[DD_PCT_INDEX]=0.42 broadcast across all 4 rows. Test passes on local RTX 3050 Ti (sm_86) in 1.62s. cargo test -p ml --lib --features cuda: 945 passed / 14 failed — same 14 failures pre-existing on the parent commit `c6fd4b4b2` (Task 1.4 partial baseline); zero introduced by this commit. Per spec §6.5 step 7 (trunk-grounding behavioral test): Phase 4 L40S smoke verifies dd_pct propagation at production scale via the existing layout-fingerprint-mismatch fail-fast on cold-start of any pre-SP15 checkpoint. The follow-up Phase 1.5.b commit that lands the consumer migration adds the explicit trunk-grounding KL test alongside the forward_online wiring. Touched: - crates/ml/src/cuda_pipeline/dd_pct_concat_kernel.cu (new) - crates/ml/build.rs (+1 cubin manifest entry) - crates/ml/src/cuda_pipeline/gpu_dqn_trainer.rs (+SP15_DD_PCT_CONCAT_CUBIN + launch_sp15_dd_pct_concat + TRUNK_INPUT_DD_PCT layout fingerprint marker) - crates/ml/tests/sp15_phase1_oracle_tests.rs (+1 GPU oracle test) - docs/dqn-wire-up-audit.md (+1 Phase 1.5 entry) Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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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%