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

..

2026-03-10-zero-cpu-hotpath.md

docs: add zero-CPU DQN training hot path implementation plan

2026-03-10 15:49:40 +01:00

2026-03-11-dqn-factored-actions.md

feat(dqn): enable Branching DQN with 45 factored actions (5×3×3)

2026-03-11 22:00:13 +01:00

2026-03-13-gpu-test-workflow.md

fix(plan): reviewer round 3 — tggn/tgnn module mapping, exit code, canonical imports

2026-03-13 11:51:58 +01:00

2026-03-14-kanidm-netbird-sso.md

docs: add Kanidm SSO + NetBird mesh design spec and implementation plan

2026-03-14 19:41:40 +01:00

2026-03-15-fused-cuda-training.md

refactor(ml): delete mixed_precision module — BF16 unconditional on CUDA

2026-03-16 16:11:48 +01:00

2026-03-16-gpu-iql-her-porting.md

refactor(cuda): eliminate all CPU fallbacks — CUDA mandatory across ML stack

2026-03-16 21:01:28 +01:00

2026-03-17-candle-hard-refactor.md

refactor(cuda): eliminate candle from ml-core, ml-ppo, and 4 thin crates

2026-03-17 22:27:56 +01:00

2026-03-17-cuda-candle-elimination.md

feat(cuda): complete Candle elimination + cudarc 0.19.3 upgrade

2026-03-17 15:13:04 +01:00

2026-03-18-full-gpu-forward-passes.md

audit: annotate all remaining to_vec/memcpy_dtoh — categorized 158 sites

2026-03-18 19:36:41 +01:00

2026-03-18-gpu-dedup-consolidation.md

fix(ml-supervised): resolve all 104 compile errors — clean build

2026-03-18 07:26:56 +01:00

2026-03-18-gpu-resident-pipeline.md

feat: WORKSPACE COMPILES — zero candle, zero errors, GPU-native

2026-03-18 13:31:35 +01:00

2026-03-21-h100-epoch-optimization-phase1.md

docs: Phase 1 implementation plan — eliminate PER CPU roundtrips

2026-03-21 10:26:11 +01:00

2026-03-21-h100-epoch-optimization-phase2.md

docs: Phase 2 plan — cuBLAS batched GEMM + kernel fusion (10.7ms → <1ms/step)

2026-03-21 11:23:09 +01:00

2026-03-21-h100-epoch-optimization-phase3.md

perf: cuBLAS SGEMM pipeline + dead code elimination — 37s → 86ms/epoch (430x)

2026-03-21 15:33:00 +01:00

2026-03-21-h100-epoch-optimization-phase4.md

perf: keep GPU training data resident across epochs — init 73ms → 0ms

2026-03-21 16:29:32 +01:00

2026-03-21-training-profiles.md

docs: training profile configuration system — spec + plan

2026-03-21 23:22:58 +01:00

2026-03-22-gpu-composite-reward.md

plan: GPU composite reward implementation — 7 tasks

2026-03-22 20:35:57 +01:00

2026-03-22-gpu-segment-tree.md

docs: GPU segment tree spec + plan for O(log n) PER sampling

2026-03-22 00:39:34 +01:00

2026-03-23-9-exposure-dual-distributional.md

plan: 9-exposure action space + dual C51/IQN distributional architecture

2026-03-23 09:03:19 +01:00

2026-03-23-stable-distributional-loss.md

plan: three-layer stable distributional loss architecture

2026-03-23 20:42:08 +01:00

2026-03-24-c51-loss-convergence.md

feat: comprehensive DQN training pipeline overhaul — 16 bug fixes, MSE warmup, financial metrics

2026-03-24 21:48:38 +01:00

2026-03-24-financial-metrics-pipeline.md

fix: segment-based trade lifecycle + reversal P&L computation

2026-03-24 23:57:04 +01:00

2026-03-24-master-trading-agent.md

docs: master plan — maximize all 25 DQN features for profitable ES trading

2026-03-24 22:00:45 +01:00

2026-03-24-remaining-gpu-features.md

fix: segment-based trade lifecycle + reversal P&L computation

2026-03-24 23:57:04 +01:00

2026-03-25-boundary-trade-counting.md

fix: backtest evaluator — correct annualization, window sizing, objective calibration

2026-03-25 19:43:26 +01:00

2026-03-25-config-unification.md

docs: config unification plan — single source of truth, 8 tasks

2026-03-25 09:01:12 +01:00

2026-03-25-eliminate-nvrtc.md

docs: plan to eliminate NVRTC — precompile all 25 CUDA kernels at build time

2026-03-25 23:58:30 +01:00

2026-03-25-reward-v6-fixes.md

docs: reward v6 fixes plan

2026-03-25 01:49:53 +01:00

2026-03-25-trade-lifecycle-fix.md

docs: trade lifecycle fix plan — address review feedback

2026-03-25 23:02:39 +01:00

2026-03-26-eval-cleanup.md

docs: eval cleanup spec + plan — remove dead 5-action path, fix train/eval mismatch

2026-03-26 00:43:58 +01:00

2026-03-26-final-fixes-before-h100.md

docs: final fixes plan — 6 issues blocking H100 deployment

2026-03-26 01:06:28 +01:00

2026-03-27-bf16-native-completion.md

docs: BF16 native completion plan — zero casts, zero nvrtc, zero GpuTensor

2026-03-27 23:39:43 +01:00

2026-03-27-bug-fixes.md

feat: gradient stability + 9-agent audit bug fixes

2026-03-27 19:52:44 +01:00

2026-03-27-full-bf16-rewrite.md

docs: full BF16 rewrite spec + plan — zero F32 on GPU

2026-03-27 20:42:37 +01:00

2026-03-27-gpu-hot-path-performance.md

feat: gradient stability + 9-agent audit bug fixes

2026-03-27 19:52:44 +01:00

2026-03-27-gradient-stability.md

feat: gradient stability + 9-agent audit bug fixes

2026-03-27 19:52:44 +01:00

2026-03-27-hive-findings-fixes.md

fix: hive findings — capital floor, dueling centering, metrics, CVaR objective

2026-03-27 07:56:50 +01:00

2026-03-27-trade-physics-refactor.md

fix: shared trade physics, IQN arg swap, trailing stop, win_rate

2026-03-27 00:47:34 +01:00

2026-03-27-training-kernel-unification.md

refactor: training kernel fully unified with trade_physics.cuh

2026-03-27 08:16:51 +01:00

2026-03-29-drawdown-aware-training.md

feat(training): continuous drawdown penalty — smooth ramp from dd_threshold to floor

2026-03-29 20:23:51 +02:00

2026-03-29-generalization-gap.md

docs: generalization gap action plan (domain randomization + CQL + multi-fold)

2026-03-29 23:24:10 +02:00

2026-03-29-novel-generalization.md

docs: 8 novel generalization techniques plan (domain rand + CQL + adversarial + curiosity Q-penalty + counterfactual + regime-adversarial + feature filtering)

2026-03-29 23:32:12 +02:00

2026-03-30-dqn-gems-implementation.md

feat: wire OFI features through TOML profile + CUDA kernel guard tests

2026-03-31 01:35:04 +02:00

2026-03-30-gems-and-pearls-generalization.md

feat(generalization): complete all 34 tasks — 7 final CUDA kernels

2026-03-30 12:38:33 +02:00

2026-03-31-databento-download-workflow.md

refactor: remove entire CPU training path — 5,307 lines of dead code

2026-04-02 09:06:23 +02:00

2026-03-31-feature-precompute-pipeline.md

docs: feature precompute pipeline implementation plan

2026-03-31 23:35:47 +02:00

2026-03-31-imbalance-bars-and-cleanup.md

cleanup: remove ALL 32 enable_* feature flags — all features unconditional

2026-03-31 10:56:20 +02:00

2026-04-01-h100-gpu-optimization.md

docs: H100 GPU optimization implementation plan — 10 tasks

2026-04-01 21:41:21 +02:00

2026-04-02-mega-graph-sub10s-epochs.md

refactor: remove entire CPU training path — 5,307 lines of dead code

2026-04-02 09:06:23 +02:00