d2331f2f62
The K=3 head's input is now [h_s2_aux (256) || plan_params (6)] = 262- dim, matching the spec's intended architecture. Implements the input concat in both the trainer's replay-batch path and the collector's rollout-step path, with appropriate handling of the backward-side stride mismatch. NEW kernel strided_row_saxpy_kernel.cu: row-truncating SAXPY that accumulates first n_cols_copy columns per row of src [B, src_cols] into dst [B, dst_cols] scaled by alpha. Handles stride mismatch (src_cols != dst_cols). Needed because backward emits dh_s2_aux_to_buf [B, 262] but dh_s2_aux_accum [B, 256] only consumes first 256 cols. PLAN_PARAM_DIM = 6 constant in gpu_aux_heads.rs. Ops struct updates: - AuxTradeOutcomeForwardOps gains concat_kernel + launch_concat() - AuxTradeOutcomeBackwardOps gains strided_saxpy_kernel + launch_strided_row_saxpy() - Both load new cubins in new() Weight tensor resize: - sizes[163] = H × (SH2 + PLAN_PARAM_DIM) = 128 × 262 = 33,536 floats - fan_dims[163] = (H, SH2 + PLAN_PARAM_DIM) Trainer changes: - New aux_to_input_buf [B × 262] field - aux_dh_s2_to_buf resized to [B × 262] - aux_partial_to_w1 resized to [B × H × 262] - max_aux_tensor_len bumped for param_grad_final scratch Trainer forward (aux_heads_forward): - Concat h_s2_aux + plan_params_buf → aux_to_input_buf - forward() with SH2_TOTAL=262 Trainer backward (aux_heads_backward): - backward() with SH2_TOTAL=262; reads aux_to_input_buf - saxpy_f32_kernel SAXPY for dh_s2_aux REPLACED by launch_strided_row_saxpy: copies only first SH2=256 cols per row; trailing 6 cols (plan_params gradient) are dropped — STOP-GRAD on trade plan head from aux loss. Collector forward (rollout): - New exp_aux_to_input_buf [N × 262] field - Concat with plan_params_ptr = 0 (NULL) → zero-fill trailing 6 cols - forward() with SH2_TOTAL=262 Train/inference asymmetry (documented): - Trainer: real plan_params from trade plan head output - Collector: zeros (no trade plan launch in collector) - The head is trained on real plan-conditional outcomes but queried at rollout time with plan_params=0. Phase B5b-2 follow-up would add a trade plan launch to the collector to resolve. Deferred — current state is functional, head still receives plan signal during training. Stop-grad on plan_params: backward writes full [B, 262] gradient, but strided SAXPY only copies first 256 cols. Trade plan head weights NOT trained by K=3 aux loss in this commit. Verification: - cargo check -p ml clean. - cargo test -p ml --lib → 1016/0 green. Phase D next: 12-weight W atom-shift (4 actions × 3 outcomes). Audit: docs/dqn-wire-up-audit.md Phase B5b section. 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.