jgrusewski 2e84fd35d4 feat(sp5): Task A8 — Pearl 1-ext per-branch num_atoms — Layer A complete
Final SP5 Layer A producer. Per-branch C51 num_atoms derived from
per-branch ATOM_V_HALF (Pearl 1, Task A1). Threshold cascade:
  v_half < 0.1  → 64 atoms (narrow Q, high resolution)
  v_half < 1.0  → 32 atoms (moderate)
  v_half ≥ 1.0  → 16 atoms (wide Q, modest resolution)

4 ISV slots [ATOM_NUM_ATOMS_BASE=274..278). Pearls A+D smooths the
discrete output during transitions; Layer B's atoms_update consumer
rounds to nearest valid count.

producer_step_scratch_buf grew 203 → 207. wiener_state_buf already
at 543 (sized at A1 for entire SP5 block).

StateResetRegistry: 1 new FoldReset entry (sp5_atom_num_atoms).

atoms_update consumer migration deferred to Layer B.

LAYER A COMPLETE. 8 producers + 3 auxiliary kernels (q_branch_stats,
grad_cosine_sim, q_skew_kurtosis) populating 110 ISV slots [174..286)
with 4 cross-fold-persistent slots carved out (Kelly).

Refs: SP5 spec 6e6e0fa11 line 1020

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-02 00:19:36 +02:00

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
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Readme 849 MiB
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Python 1.3%
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