ViperEkura e9b03f4fca perf: apply cp.async, XOR swizzle, pre-scaled Q to decode MMA kernel ... Decode MMA kernel previously used scalar global→shared loads with LD=HEAD_DIM+8 padding and per-tile scale multiply. This commit brings it in line with the prefill MMA kernel (which already had these optimizations): - cp.async K/V loads (bypasses registers, halves load instructions) - XOR swizzle: LD=HEAD_DIM instead of HEAD_DIM+8 (zero waste smem) - Pre-scale Q during load (removes per-tile scale multiply in softmax) - Clean up prefill MMA kernel comments (no code change) ~2x speedup on decode (0.47ms→0.24ms at seq_len=512)		2026-07-08 16:15:14 +08:00
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gqa_common.cuh	fix: correct prefill mask index, unify GQA kernel interface	2026-07-06 17:21:23 +08:00
gqa_decode_attn.cu	perf: apply cp.async, XOR swizzle, pre-scaled Q to decode MMA kernel	2026-07-08 16:15:14 +08:00
gqa_decode_attn.cuh	fix: correct prefill mask index, unify GQA kernel interface	2026-07-06 17:21:23 +08:00
gqa_decode_attn_mma.cuh	perf: apply cp.async, XOR swizzle, pre-scaled Q to decode MMA kernel	2026-07-08 16:15:14 +08:00
gqa_mma_utils.cuh	feat: support HEAD_DIM=32 and split extension into loader/ops	2026-07-08 14:14:11 +08:00
gqa_prefill_attn.cu	perf: apply cp.async, XOR swizzle, pre-scaled Q to decode MMA kernel	2026-07-08 16:15:14 +08:00
gqa_prefill_attn.cuh	feat: tensor-core mma prefill with build-time dispatch	2026-07-06 20:33:24 +08:00
gqa_prefill_attn_mma.cuh	perf: apply cp.async, XOR swizzle, pre-scaled Q to decode MMA kernel	2026-07-08 16:15:14 +08:00