jgrusewski eb5e19d670 plan(sp15): rewrite v2 — fix all 16 reviewer-flagged issues
Rewrite of 2026-05-06-sp15-trader-discipline-and-recovery.md from v1
(commit 0178a53ab) which had 16 reviewer-flagged issues including
5 critical compile-breakers and 8 important plan-failure violations.

CRITICAL fixes:
- Real GATE1_OPEN_STATE_INDEX (slot 391) — was wrong GATE1_STATE_INDEX
- Real PS_PEAK_EQUITY/PS_PREV_EQUITY (state_layout.cuh slots 7+9) —
   no invented CUMULATIVE_EQUITY_INDEX
- Real sp4_histogram_p99<BLOCK_SIZE> block-tree-reduce pattern, no
   atomicAdd_block (was feedback_no_atomicadd violation)
- Real evaluate_dqn_graphed pattern (gpu_backtest_evaluator.rs:1143) —
   no nonexistent evaluate_on_val_slice
- Real services/ml_training_service/src/main.rs path — was wrong

IMPORTANT fixes:
- Fork from current main 0178a53ab, not stale 5417e2756
- Phase 0.B has explicit case-(a)/case-(b) branches driven by 0.A
   diagnostic conclusion
- Phase 2B uses TEMPLATE + 17-row differential table — every test fully
   specified, no compressed bullets
- Phase 3 each teaching gets full TDD: write test → run-fail → kernel
   (full code) → launcher → consumer → run-pass → commit (5+ steps)
- Phase 3.5 each mechanism same TDD pattern with full kernel code
- Plasticity 3.5.4 specifies TWO-STEP recovery (Flat first, then
   cooldown) + Kaiming-He init (not Xavier — architecturally appropriate)
- Phase 4.3 includes FULL eval-final-template.yaml (not 4 bullets)
- 4 EGF constants replaced (not 3 — verified all four in
   alpha_grad_compute_kernel.cu lines 142,143,144,147)
- Behavioral_suite test target ordering fixed (Cargo.toml entry lands
   before tests run against it)

Stats: 4947 lines, ~270 [- [ ]] step checkboxes, 0 todo!() in test
bodies, every kernel shown in compilable form.

Self-review section maps every spec section to implementing task,
verifies all cross-references against verified codebase facts.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-06 09:58:30 +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
No description provided
Readme 849 MiB
Languages
Rust 88.2%
Cuda 7.7%
Python 1.3%
Shell 1.1%
PLpgSQL 0.8%
Other 0.8%