biondizzle 583ad6cfe6 P0 complete: Kill .item() in grouped_linear, reduce hot-path syncs ...

- grouped_linear.py: Replace .item() gsa + Python quantize with
  quantize_nvfp4_gpu_fused (zero CPU syncs). Flatten all groups
  into (G*T, D), single fused kernel launch, GPU-only gsa copy.
- single_shot_inference.py: Reduce torch.cuda.synchronize() to
  every 20 steps instead of every step. Gate per-layer diagnostics
  to li<3 or li>=58 (avoid 61 .item() calls per decode step).

2026-06-01 22:21:12 +00:00

..

cache

E1: Wire LayerCacheHandle gather methods + CUDA gather kernels

2026-05-30 21:09:21 +00:00

kernels

CRITICAL FIX: fused_amax_quantize cross-CTA race condition

2026-06-01 21:26:51 +00:00

layers

P0 complete: Kill .item() in grouped_linear, reduce hot-path syncs

2026-06-01 22:21:12 +00:00

loader

Restructure: cutedsl/ -> dsv4/ with proper layering

2026-05-21 17:30:44 +00:00

model

P0 COMPLETE: Eliminate ALL .item() CPU-GPU syncs from NVFP4 activation path

2026-06-01 21:05:03 +00:00

ops

Fix gsa_buffer shape mismatch for MoE (M>1 rows)

2026-06-01 21:33:59 +00:00

reference

Restructure: cutedsl/ -> dsv4/ with proper layering

2026-05-21 17:30:44 +00:00

__init__.py

Restructure: cutedsl/ -> dsv4/ with proper layering

2026-05-21 17:30:44 +00:00