e1aef5337308f9e28aa8ed3ff5e5b690dba185cb
Append a "Plan Accuracy Errata" section to the SP19+20 plan
documenting the 6 deviations from the original Phase 2 plan that
emerged during implementation. Each entry captures the gap, the
decision made, and the rationale, so future implementers see what
was actually built vs what was specified.
Gaps documented:
1. Task 2.0 (label-at-open infrastructure) was NEW — split out from
Task 2.2 to land buffer + alloc + reset + write site atomically
before Task 2.2's consumer ships. Sign convention mapping detail
captured (kernel emits {0, 1, -1}, SP20 spec uses {-1, 0, +1}).
2. Per-env alpha plumbing was not in Task 2.2 plan scope — built in
Task 2.2 (NOT deferred to Phase 4) to preserve the
`feedback_no_partial_refactor` contract atomicity. Touches 5
files in one commit.
3. Per-bar SP18 D-leg sites — KEEP for Phase 2 per `feedback_no_stubs`.
Plan's wording "DELETE [these helpers]" was overbroad; only the
trade-close-site call is deleted. The phantom
`compute_sp12_reward_with_cost` doesn't exist as a function (the
SP12 v3 reward is the inlined block).
4. `sp20_compute_event_reward` placement — new dedicated
`sp20_reward.cuh` header (NOT inside `experience_kernels.cu`,
NOT inside `trade_physics.cuh`). Mirrors the
compute_asymmetric_capped_pnl / compute_min_hold_penalty
header-only pattern; needed for GPU oracle test wrapper to share
the function bit-for-bit per `feedback_no_cpu_test_fallbacks`.
5. Task 2.3 was subsumed by Task 2.2 — the existing Path C chain
consumes the new `alpha` field automatically once `alpha_per_env`
is wired; no separate `sp20_emas_compute` producer call needed.
6. `min_hold_*` kernel-arg trio cleanup deferred to Task 2.4 — the 3
kernel args were deleted in Task 2.2 (per `feedback_no_hiding`)
but the upstream producer chain (`min_hold_temperature_update_kernel`,
ISV[460], `read_min_hold_temperature_from_isv`, `config.min_hold_*`)
deferred to Task 2.4 because it touches SP14 ISV slot registry +
StateResetRegistry + ISV layout fingerprint bump.
Implementation-level details remain in `docs/dqn-wire-up-audit.md`
Task 2.0 / 2.1 / 2.2 entries; this errata is the plan-level
"what was actually built vs what was specified".
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%