jgrusewski 5f3c44af2b perf(cuda): StreamTensor ops rewritten — 30+ element-wise ops GPU-native
stream_ops.rs: ZERO host-roundtrip in ANY element-wise operation.
Every gpu_* function now delegates to ElementwiseKernels CUDA kernels.

Rewrote: gpu_add, gpu_sub, gpu_mul, gpu_div, gpu_sigmoid, gpu_tanh,
gpu_silu, gpu_relu, gpu_elu, gpu_exp, gpu_log, gpu_abs, gpu_neg,
gpu_sqrt, gpu_sqr, gpu_sin, gpu_cos, gpu_floor, gpu_clamp, gpu_scale,
gpu_affine, gpu_recip, gpu_scalar_sub, gpu_add_scalar, gpu_minimum,
gpu_max_scalar, gpu_transpose, gpu_softmax, gpu_layer_norm, gpu_mean_all

Memory ops: gpu_cat_dim0/dim1, gpu_narrow_2d, gpu_select_dim1,
gpu_stack_2d — all DtoD async copies, zero host involvement.

elementwise.rs: 10 new CUDA kernel ops — sin, cos, sqrt, silu, elu,
recip, sigmoid, tanh, min, max. Broadcast row/col extended with add/sub.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-18 18:57:58 +01:00

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
No description provided
Readme 849 MiB
Languages
Rust 88.2%
Cuda 7.7%
Python 1.3%
Shell 1.1%
PLpgSQL 0.8%
Other 0.8%