494a2e4827
Per docs/superpowers/specs/2026-05-17-kloop-parallelization-design.md. cfc_step_batched (fwd + bwd) refactored from grid=(1,1,1) with internal n_batch loop to grid=(B,1,1) — each block handles one batch. Removes the single-SM bottleneck on the K-loop's most-called kernel (64×/step). Param-grad accumulation moves to per-batch scratch: cfc_grad_w_in_scratch_d [B, n_hid, n_in] cfc_grad_w_rec_scratch_d [B, n_hid, n_hid] cfc_grad_b_scratch_d [B, n_hid] cfc_grad_tau_scratch_d [B, n_hid] Zeroed once per training step, K-loop's 64 bwd calls += into them, then 4 reduce_axis0 launches collapse B → final grad buffers (OVERWRITE) before AdamW. New AdamW-after-reducer invariant: final grads are meaningful only after the reducer has run in the current step. New reduce_axis0 kernel: single parameterised reducer [B, N] → [N] via block tree-reduce (no atomicAdd per feedback_no_atomicadd.md). Same pattern as layer_norm_reduce_param_grads — CUDA-Graph-safe. cfc_step_backward_batched shared-mem dropped from (B+1)*n_hid*4 to 2*n_hid*4 bytes per block (only one row of sd_pre needed per block bi). Tests: - New stacked_trainer_loss_shrinks_at_batch_32: FIRST test that actually exercises the cross-batch reduction code path; existing perception_overfit suite was all B=1. Initial 0.24 → final 0.00. - Scratch-clears test removed (explanatory comment kept): structurally hard to assert directly due to begin_capture/end_capture not executing kernels; the B=32 convergence smoke implicitly validates scratch zeroing since divergence would otherwise be immediate. All 9 perception_overfit smokes + 4 backward_finite_diff tests pass. build.rs: - KERNELS list adds "reduce_axis0" - Cache-bust → v11 Co-Authored-By: Claude Opus 4.7 <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.