87ea9fa416
Per `feedback_no_htod_htoh_only_mapped_pinned.md`, mapped pinned
(cuMemHostAlloc DEVICEMAP) is the only allowed CPU↔GPU path.
Adds module-level `upload_via_mapped_{f32,i32,u32,u64}` helpers and an
in-place `update_via_mapped_f32`. Each stages CPU data through a
transient mapped pinned buffer and DtoD-copies into the destination
`CudaSlice<T>`, then stream-syncs so the staging buffer is safe to
drop. Destination buffer types remain `CudaSlice<T>` so every existing
consumer (raw_ptr / kernel arg) is untouched, satisfying
`feedback_no_partial_refactor.md` for these one-shot init paths.
Migrated COLD sites in `GpuDqnTrainer::new`:
- weight_decay_mask (TOTAL_PARAMS f32)
- branch_slice_starts_dev, branch_slice_lens_dev ([i32; 4])
- branch_grad_scales_dev ([f32; 4])
- per_branch_gamma_base/max_dev ([f32; 4] each)
- q_quantile_branch_offsets/sizes_dev ([i32; 4] each)
- spectral_norm_descriptors_dev ([u64; 78])
- stochastic_depth_scale_buf ([f32; 3])
- stochastic_depth_rng_state ([u32; 1])
- vsn_group_begins_buf, vsn_group_ends_buf ([i32; num_groups] each)
- mamba2_params Xavier init (mamba2_param_count f32)
11 COLD HtoD sites eliminated. cargo check clean (15 warnings; +2 over
baseline 13 are the new MappedU32/U64 struct visibility warnings,
matching the existing MappedF32/I32 pattern).
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.