The single_shot is a reference for vLLM/SGLang integration. The layer-pipeline
sharding (gpu = li % NUM_GPUS) is the right pattern for this reference.
EP/TP sharding belongs in the actual vLLM integration, not here.
- fused_amax_quantize.cu: Single kernel launch computes amax → gsa → NVFP4 quantize
Zero CPU-GPU syncs. gsa written to GPU buffer for downstream GEMM global_scale_a.
- dsv4/kernels/cuda/__init__.py: Module loader that compiles .cu once and caches.
Eliminates JIT recompilation overhead (was ~100ms per call, ~500x per token).
- P1 audit corrected: layer-pipe at batch=1 is wrong, but single-GPU doesn't fit
(800GB weights vs 192GB HBM). Correct fix is EP=8 for MoE + TP/replicate for dense.
