foxhunt

Files

jgrusewski d63190b9b9 feat(ml): GPU full saturation — remove artificial caps and enable VRAM-aware scaling

Phase 1: Remove artificial caps
- TFT benchmark: VRAM-scaled batch sizes (4/16/32/64) replacing hardcoded max_batch=4
- Liquid CUDA: VRAM-aware config defaults (batch 256-2048, pool 10% VRAM)
- DQN trainer: remove double-clamp between AutoBatchSizer and HardwareBudget

Phase 2: Mixed precision in training
- DQN agent: add BF16/FP16 dtype casting in forward_with_gradients and
  forward_without_gradients (training was bypassing forward_mixed)

Phase 3: Reduce CPU round-trips
- DQN trainer: flat buffer select_actions_batch (eliminate Vec<Vec<f32>>)
- DQN trainer: early-skip experience extraction (avoid .to_vec() on invalid)
- EpochPrefetcher: AtomicBool is_ready() so callers can detect completion

Phase 4: Adaptive scaling
- HardwareBudget: tiered safety factor (0.70-0.85 by GPU size)
- AutoBatchSizer: VRAM-proportional batch_overhead_mb (1.5% instead of fixed 250MB)

2451 tests pass, 0 clippy warnings.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

2026-03-02 11:42:38 +01:00

backtesting

docs: create/update README.md for all 17 crates

2026-03-01 22:47:39 +01:00

common

refactor(common): make init_observability sync with optional OTLP endpoint

2026-03-01 23:03:13 +01:00

config

docs: create/update README.md for all 17 crates

2026-03-01 22:47:39 +01:00

ctrader-openapi

docs: create/update README.md for all 17 crates