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4 Commits

Author SHA1 Message Date
jgrusewski
1cc6168a6b fix: backtest action_select missing isv_signals_ptr + regenerated fxcache 
Backtest evaluator missing isv_signals_ptr arg (passed as NULL).
Regenerated test fxcache with OFI_DIM=20 from MBP-10 + trades data.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
 2026-04-17 01:07:45 +02:00
jgrusewski
770a1b41fa fix: borrow conflict in gpu_residency test 
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
 2026-04-02 19:35:38 +02:00
jgrusewski
d3a6123046 perf: zero-alloc GPU PER sampling — raw pointers, no CudaSlice cloning 
GpuBatch now stores raw u64 device pointers to pre-allocated replay
buffer memory. Eliminates per-step:
- 14 cuMemAlloc calls (7 in sample_proportional + 7 in into_gpu_batch)
- 14 DtoD copies (clone into owned CudaSlice)
- CPU staging Vec and flush() dead code path

Also removed: GpuBatchSlices, into_gpu_batch, dtod_clone_* helpers,
StagedGpuBuffer.staging field, CPU add/add_batch for GpuPrioritized.

update_priorities_cuda now takes u64 raw pointer.
HER relabel_batch_with_strategy takes u64 episode_ids_ptr.
Cold-path Q-value estimation uses compute_q_stats_internal.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
 2026-04-02 19:19:09 +02:00
jgrusewski
12fdd18223 refactor: remove entire CPU training path — 5,307 lines of dead code 
Deleted:
- DQN::compute_loss_internal (280 lines) — old Candle forward+loss
- DQN::train_step (55 lines) — old Candle training step
- DQN::compute_gradients (47 lines) — old gradient accumulation
- ComputeLossResult struct — only used by deleted functions
- RegimeConditionalDQN::train_step (65 lines) — old dispatch
- RegimeConditionalDQN::train_step_gpu_regime (100 lines) — old GPU path
- RegimeConditionalDQN::compute_gradients_gpu (130 lines) — old regime gradients
- RegimeConditionalDQN::compute_gradients (92 lines) — old dispatch
- DQNAgentType::train_step dispatch — dead
- DQNAgentType::compute_gradients dispatch — dead
- GpuDqnTrainer::upload_batch (71 lines) — old CPU→GPU upload
- train_step.rs (500 lines) — entire module including ensure_fused_ctx
- dqn_benchmark.rs — used old train_step
- examples.rs — used old train_step
- validation/adapters.rs (289 lines) — used old train_step
- dqn/trainable_adapter.rs — used old train_step
- gpu_smoketest.rs — tested old train_step
- Gradient accumulation path in training_loop.rs (144 lines)
- IQN d_h_s2().clone() → raw pointer (zero alloc)
- Causal intervention format! string alloc removed
- Dead HER relabel functions (320 lines)

Kept:
- ensure_fused_ctx logic inlined into training_loop.rs
- set_noise_sigma_scale re-added to RegimeConditionalDQN

Fixed:
- GpuReplayBuffer max_batch_size wired from batch_size parameter
  (was hardcoded 1024, blocking batch_size=8192)

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
 2026-04-02 09:06:23 +02:00