aada419de3
Replaces the kernel's hardcoded `ema_alpha` with the shared `pearls_ad_update`
host-side helper (Task A3). Buffer growth in same commit so subsequent A13.x
retrofits land on a stable scratch/Wiener layout.
- Kernel `h_s2_rms_ema_update` signature: `(h_s2, B, SH2, scratch_buf,
scratch_idx)`. Reduces RMS = sqrt(sum_sq/(B*SH2)) via the existing
256-thread shmem tree (no atomicAdd) and writes step_obs to
`producer_step_scratch_buf[40]` with `__threadfence_system()`.
- Launcher `launch_h_s2_rms_ema(_ema_alpha_unused: f32)` syncs the stream,
then applies Pearls A+D host-side via zero-copy mapped-pinned reads/
writes of `isv_signals_pinned[H_S2_RMS_EMA_INDEX=96]` and
`wiener_state_buf[120..123)` (= scratch slot 40 × 3). Degenerate-zero
short-circuit before mutating ISV/Wiener state.
- Buffer growth: `SP4_PRODUCER_COUNT 47 → 69` (40 SP4 + 29 Task A13
retrofit producers); `wiener_state_buf 141 → 207` floats;
`producer_step_scratch_buf` grows to 69 entries.
- Stable-layout doc-comments updated: `producer_step_scratch_buf` field
comment, `launch_sp4_target_q_p99` slot-table comment, 5 launcher
`wiener_offset + 2 < 141` safety comments (now `< 207`),
`reset_sp4_wiener_state` doc + body comment, and
`state_reset_registry.rs::sp4_wiener_state` description.
- Test cubin reference `SP4_PRODUCER_COUNT: usize = 47` in
`tests/sp4_producer_unit_tests.rs` updated to 69 across all 6
occurrences.
Behavior: stationary signals converge to the same RMS at adaptive rate
(Pearl D's α* derived from per-slot signal-vs-noise variance);
non-stationary signals respond Wiener-optimally faster. Cold-path producer
with no consumer-facing change beyond the EMA mechanism — slot 96 is read
by `mag_concat_qdir`'s adaptive-scale path and stays semantically identical
(RMS of `save_h_s2`).
Tests: new `sp4_h_s2_rms_ema_writes_step_rms_via_pearl_a_then_converges_pearl_d`
unit test (`#[ignore]`-gated for GPU) drives the production kernel kernel-
direct on a constant-5.0 stationary signal of B=4 SH2=64, asserts
step_rms ≈ analytical RMS=5.0 ± 1e-4, asserts non-target scratch slots
remain 0, then exercises Pearl A bootstrap (returns step_rms directly +
seeds x_lag) and Pearl D convergence (1000 stationary observations →
x_mean within 1% of 5.0).
Per `feedback_no_atomicadd.md`, `feedback_no_htod_htoh_only_mapped_pinned.md`,
`feedback_no_partial_refactor.md`. Build: `cargo check -p ml --lib --tests
--offline` clean (11 pre-existing warnings, no new warnings); `cargo test
-p ml --lib sp4_wiener_ema --offline` 6/6 passing.
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.