3 Commits

Author	SHA1	Message	Date
biondizzle	c2e3d15633	NVFP4-1.1 integration: GPU-only quantize kernel + MoE pipeline wiring ... - Add quantize_nvfp4.cu: BF16→FP4 GPU kernel (no CPU sync, warp shuffle amax) - Add quantize_nvfp4_gpu() bridge in ops/quantize.py - Fix deinterleave_quantize kernel path (dsv4/ops/kernels → dsv4/kernels/cuda) - Wire GPU quantize into Nvfp4MoE._run_impl(): - L1 input: quantize_nvfp4_gpu (replaces quantize_activation_nvfp4) - Fused SwiGLU L2: deinterleave_quantize_nvfp4_cuda (single kernel) - Non-fused L2: quantize_nvfp4_gpu - Add test_nvfp4_gpu_quantize.py for both kernels	2026-05-25 16:19:07 +00:00
biondizzle	401e24768a	fix: import ceil_div in quantize.py (was NameError at runtime)	2026-05-23 08:40:24 +00:00
biondizzle	3fb3c925af	Restructure: cutedsl/ -> dsv4/ with proper layering ... - Split bridge.py -> ops/quantize.py, ops/layouts.py, ops/gemm_runner.py - Renamed classes: CuTeDSLNvfp4Linear -> Nvfp4Linear, etc. - Moved kernel code to dsv4/kernels/ (gemm, attention, compressor, decode, cuda) - Moved PyTorch bridges to dsv4/ops/ - Moved nn.Module layers to dsv4layers/ - Moved reference implementations to dsv4/reference/ - Moved vendored CUTLASS code to vendored/ - Archived ~190 debug tests to tests/archive/ - Kept ~15 canonical tests in tests/unit/ - Updated all import paths - Added stubs for future components (model/, cache/, loader/) - Updated pyproject.toml: dsv4-inference package name	2026-05-21 17:30:44 +00:00