7b3309edcc35ef111a870c84b77419408fb047f3
Replaces atomicAdd accumulators in `ppo_clipped_surrogate_fwd` and
`dqn_distributional_q_bwd` with per-batch [B] outputs + a dedicated
single-block tree-reduce kernel. Per feedback_no_atomicadd.
Root cause: `ss_pi_loss_dev_ptr` was zero-init at trainer construction
but never reset between steps; the PPO atomicAdd accumulated across
every step since startup. Result: `loss.pi` = step_count × mean_per_step,
bit-exact step-count fingerprints:
- local 1k × ~9 ≈ 9080 ✓
- cluster 20k × ~1200 ≈ 24M ✓
The DQN distributional Q kernel had the same atomicAdd pattern. Its
trainer caller happened to memset between launches in dqn_replay_step
so the symptom was masked, but the anti-pattern was identical. Fixed
in the same commit per the user's "atomicAdd should not be used at all"
reminder.
Local smoke (RTX 3050, b=16, 1k steps, seed=16962):
step | l_pi (pre → post) | l_q (pre → post)
100 | 27.5 → 0.56 | 18.1 → 0.19
500 | 743.1 → 4.59 | 93.3 → 0.19
999 | 9080.5 → 65.1 | 186.1 → 0.19
l_q now bit-flat at per-step mean (~0.19) — no step-count fingerprint.
l_pi grows organically with policy excursion (PPO surrogate magnitude
when ratio→clamp_max under Q-distillation-driven policy updates),
which is the legitimate diagnostic the prior staleness was burying.
Changes:
- ppo_clipped_surrogate_fwd: scalar [1] outputs → per-batch [B]
- dqn_distributional_q_bwd: remove atomicAdd; per_batch[B] only
- ppo_loss_reduce_b.cu (NEW): two block tree-reduce kernels
• ppo_loss_reduce_b (dual: PPO loss + entropy loss)
• mean_reduce_b_f32 (single, reused by DQN head)
- PolicyHead + DqnHead: load reducer cubin, add reduce_loss_to_scalar
- Trainer: allocate ss_pi_loss_per_b_d + ss_pi_loss_entropy_per_b_d,
invoke reducer after each backward (PPO + DQN replay paths)
Co-Authored-By: Claude Opus 4.7 <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.
Description
Languages
Rust
88.2%
Cuda
7.7%
Python
1.3%
Shell
1.1%
PLpgSQL
0.8%
Other
0.8%