66f7e64d13
The original D1 kernel (commit 5ee795f14) was authored against a brief
that assumed per-trade event arrays exist in production. They don't.
Production has per-bar step_returns + done_flags with episode-boundary
resets, plus already-aggregated summary scalars (sum_returns,
sum_sq_returns) on TradeStats. The previous D4 agent found this
mismatch as a structural blocker and stopped before any code changes.
This rewrite fixes the kernel internals to match compute_epoch_financials
in financials.rs bit-for-bit. The slot allocation (ISV[286..290) for
PNL_TOTAL/MEAN/VAR/MAX_DD), Pearls A+D chain, and reset registry are
unchanged — only the kernel interface and max_dd internals shift.
What changed:
- pnl_aggregation_kernel.cu: full rewrite. New signature consumes
step_returns[N], done_flags[N], num_bars, n_trades, sum_returns,
sum_sq_returns, initial_capital. pnl_total uses log-space
compounded growth (financials.rs:80-97). pnl_mean/pnl_var are
per-trade (financials.rs:122-124). pnl_max_dd implements per-bar
equity walk over last 10K bars with reset at done_flags > 0.5
AFTER processing the bar's return (matches financials.rs:163-194
line-by-line, including 1.0 cap).
- launch_sp5_pnl_aggregation: signature updated to match. 2
MappedF32Buffers + 5 i32/f32 scalars instead of 3 mapped-pinned
buffers + 1 count. Same Pearls A+D chain on the same stream.
- sp5_isv_slots.rs: PNL slot docstring updated to reflect the actual
output semantics (slot constants unchanged).
- SCRATCH_PNL_AGG_BASE docstring + cubin static docstring + field
docstring updated.
- sp5_producer_unit_tests::pnl_aggregation_kernel_correctness:
rewritten with new oracle. Inputs cover an episode boundary at
bar 2 so the reset semantics are observable; expected values
derived analytically from the host formula (no CPU oracle in the
test process, per feedback_no_cpu_test_fallbacks).
- Audit doc: D1-rewrite entry supersedes original D1 entry, with a
line-by-line formula provenance table for D4 reviewers.
Unchanged: ISV slot allocation (sp5_isv_slots.rs constants),
SP5_SLOT_END/SP5_PRODUCER_COUNT/ISV_TOTAL_DIM, wiener offsets,
state_reset_registry arm + dispatch, build.rs cubin registration.
The kernel filename stays the same; only the file contents change.
Formula fidelity provenance (financials.rs as the oracle):
- pnl_total: lines 80-97 (log-space sum, 1e-10 floor, exp − 1)
- pnl_mean: line 122 (per-trade sum_returns / n_trades)
- pnl_var: lines 123-124 (per-trade E[X²] − E[X]², .max(0))
- pnl_max_dd: lines 163-194 (10K window, post-update reset, 1.0 cap)
Tests: cargo check + cargo build --features cuda clean; ISV slot +
state_reset_registry tests pass (8/8 unchanged); rewritten GPU
correctness test fires on next L40S smoke.
This unblocks D4 atomic wiring (D1+D2+D3 into the production hot
path with host-EMA removal). D4 dispatch resumes once this lands.
Refs: SP5 plan §D Task D1 + the structural blocker investigation by
the prior D4 agent (no commit; investigation reported up).
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.