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3 Commits

Author SHA1 Message Date
jgrusewski
98a81981ac fix(build-infra): cargo:rerun-if-env-changed=CUDA_COMPUTE_CAP across 6 crates 
Per pearl_build_rs_rerun_if_env_changed, every std::env::var() must be
paired with cargo:rerun-if-env-changed. Task #321 fixed crates/ml/build.rs
(commit e3d082968) but missed 6 sibling build.rs files. Each reads
CUDA_COMPUTE_CAP without registering the rerun directive, so cargo
sees no env-change between e.g. SM 89 (L40S) → SM 90 (H100) workflow
re-submissions and cache-hits the wrong-arch cubin from the previous
run. At runtime, the H100 fails to load the SM 89 cubin with
CUDA_ERROR_NO_BINARY_FOR_GPU on rmsnorm — exactly what killed
train-multi-seed-vlv8c (commit 0371d6a76, post-Class-B chain).

Files (all add `println!("cargo:rerun-if-env-changed=CUDA_COMPUTE_CAP")`
just before the env::var() read):
- crates/ml-dqn/build.rs (rmsnorm — root cause of vlv8c failure)
- crates/ml-ensemble/build.rs
- crates/ml-explainability/build.rs
- crates/ml-ppo/build.rs
- crates/ml-supervised/build.rs
- crates/ml-core/build.rs

Atomic single commit per feedback_no_partial_refactor.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-05-08 13:09:21 +02:00
jgrusewski
68804a1a51 fix(cuda): remove --use_fast_math, eliminate cross-stream NaN race, f32 rewards/dones 
Three root causes of sporadic NaN during training:

1. --use_fast_math (nvcc) breaks IEEE 754 NaN semantics: fmaxf(NaN,x)
   returns NaN instead of x, isnan()/isinf() compile to false.
   Replaced with --ftz=true --fmad=true --prec-div=true --prec-sqrt=true
   across all 4 build.rs (ml, ml-dqn, ml-ppo, ml-core).

2. Cross-stream race: replay buffer wrote batch data on the device's
   original stream while the trainer read it on a forked stream.
   Fixed by passing the forked stream to the DQN agent via agent_device,
   so all GPU components share a single CUDA stream (zero sync overhead).

3. Rewards/dones stored as bf16 in replay buffer caused done=0xFFFF NaN.
   Converted entire rewards/dones pipeline to f32: experience collector,
   replay buffer storage, nstep kernel, loss/grad kernels.

Also:
- Removed fast_isnan/fast_isinf/fast_isfinite wrappers — standard
  isnan/isinf/isfinite work correctly without --use_fast_math
- Updated dqn-smoketest.toml: lr=1e-4, epsilon=1e-8 (f32 Adam values)
- Removed debug printfs from gather kernels
- Added curiosity_weight to training profile system
- Cleaned up smoke_params() inline overrides

11/11 smoke tests pass, 5/5 stress runs of 50-epoch test pass,
359/359 ml-dqn + 895/895 ml unit tests pass.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
 2026-03-29 16:18:37 +02:00
jgrusewski
07d0e60fe4 feat(bf16): remove nvrtc from entire workspace + wire ml-core precompiled cubins 
- Fork cudarc locally (vendor/cudarc): add CudaContext::load_cubin()
  that calls cuModuleLoadData directly — zero nvrtc dependency
- Remove "nvrtc" feature from ml-core, ml-dqn, ml-ppo Cargo.toml
- Replace all 89 Ptx::from_binary + load_module calls with load_cubin
- ml-core cuda_autograd: wire 9 stub constructors to precompiled cubins
  (activation, elementwise, linear, loss, reduction, dropout, layer_norm, optimizer)
- ml-core build.rs: compile 8 BF16-native CUDA kernels via nvcc
- cubin_loader.rs: thin wrapper around CudaContext::load_cubin()
- Fix size_of::<f32> in gpu_tensor.rs, stream_ops.rs, layer_norm.rs
- Fix test data: Vec<f32> → Vec<half::bf16> for memcpy_htod
- Stub ml-ppo/ml-dqn runtime compile_ptx calls (dead code)
- backtest_metrics_kernel.cu: full native BF16 rewrite (no float)
- backtest_env_kernel.cu: shared memory → __nv_bfloat16

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
 2026-03-28 10:11:46 +01:00