ViperEkura cbd140340d perf: load prefill Q fragments directly from global (drop sQ staging) ... - read the 8 Q elements each lane needs straight from global into the mma A-operand layout, pre-scaled, instead of staging through shared sQ - removes the sQ smem area (20KB->16KB) and the serialized per-warp prologue with its WARPS __syncthreads barriers - result vs torch SDPA: prefill 0.70-0.82x -> 0.85-1.00x (matches torch at seq=128; 2048 1.251->1.159ms), correctness unchanged across head dims		2026-07-10 12:27:45 +08:00
..
kernels	perf: load prefill Q fragments directly from global (drop sQ staging)	2026-07-10 12:27:45 +08:00
tests	perf: reduce MMA kernel registers, switch to static smem	2026-07-10 00:39:47 +08:00
__init__.py	feat: add optional CUDA kernel system (csrc/) + fused GQA decode attention	2026-07-06 12:09:58 +08:00
build.py	perf: add fast-math and vectorization nvcc/cxx build flags	2026-07-07 22:28:32 +08:00