5ded1cb4b9
Component 5 / Kernel 2 of the SP20 fused-producer chain — the
deterministic derivation step. Reads the EMAs Phase 1.2's
sp20_emas_compute wrote (4 ISV + 4 internal scratch slots) and
derives 6 controller outputs into ISV slots:
- LOSS_CAP (510) = -1 - clamp((wr-0.50)/0.05, 0, 1)
- HOLD_COST_SCALE (513) two-sided ramp around TARGET_HOLD_PCT ±0.05
- TARGET_HOLD_PCT (514) = clamp(0.8 - aux_p50_ema*1.5, 0.1, 0.8)
- N_STEP (517) = clamp(round(trade_dur_ema), 1, 30) (f32)
- AUX_CONF_THRESHOLD (518) = clamp(aux_dir_acc_ema-0.50, 0.01, 0.20)
- AUX_GATE_TEMP (519) = max(aux_conf_std_ema, 0.01)
TARGET_HOLD_PCT computed before HOLD_COST_SCALE because the
HOLD_COST_SCALE controller reads tgt; implemented as a local f32
written to ISV then re-used for the controller (no redundant ISV
read-back). HOLD_COST_SCALE is the only output that READS its own
previous ISV value (in-place update); deadband path writes the
unchanged previous value verbatim per feedback_no_stubs.
Single-block, single-thread kernel — captureable in the per-step
CUDA Graph per pearl_no_host_branches_in_captured_graph. ISV +
internal pointers are mapped-pinned device pointers (existing
buffers from Phase 1.2); kernel emits __threadfence_system() for
PCIe-visible coherence.
Pearls + invariants honoured:
- pearl_controller_anchors_isv_driven: every output's anchor /
target / cap derives from EMAs; only spec-frozen ramp / clamp
parameters are compile-time constants.
- feedback_isv_for_adaptive_bounds: these 6 outputs ARE the
adaptive bounds.
- feedback_no_atomicadd, feedback_no_cpu_compute_strict,
feedback_no_htod_htoh_only_mapped_pinned, feedback_no_stubs.
- feedback_no_partial_refactor: kernel + launcher + tests + build
entry land atomically; production wire-up lands in Phase 1.4.
- pearl_tests_must_prove_not_lock_observations: 7 GPU oracle
tests assert clamp boundaries, formula correctness, and
bidirectional ramp behavior — NOT specific observed values.
Tests (all #[ignore = "requires GPU"], pass on RTX 3050 Ti sm_86):
1. loss_cap_ramp_boundaries — 4 wr_ema sweeps incl. clamps.
2. n_step_bounds — round + clamp [1, 30].
3. aux_conf_threshold_bounds — clamp [0.01, 0.20].
4. aux_gate_temp_floor — max(std, 0.01).
5. target_hold_pct_inverse_relation — 0.8 − p50*1.5 with clamps.
6. hold_cost_scale_two_sided_ramp — up/down/deadband + clamps.
7. all_six_outputs_written_in_one_launch — guards missed writes.
Plus 3 launcher unit tests (slot range, slot uniqueness, ISV input
slot range).
Verification:
SQLX_OFFLINE=true CUDA_COMPUTE_CAP=86 cargo check -p ml --features cuda
SQLX_OFFLINE=true CUDA_COMPUTE_CAP=86 cargo test -p ml \
--test sp20_controllers_compute_test --features cuda \
-- --ignored --nocapture
→ 7/7 GPU oracle tests pass; 3/3 launcher unit tests pass.
Phase 1.4 will land the production caller atomically alongside
Kernel 1 + Kernel 3 launches on the same stream in order
Stats → EMAs → Controllers per the SP20 design.
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.