KernelBench hard · RTX PRO 6000

KDA CUTLASS GPT-5.6 Sol

manually audited: clean

Genuine from-scratch five-kernel Triton chunk pipeline for KDA forward on SM90. Pair-matrix kernel builds in-chunk cumsum(g), anchored-exponential Aqk/Akk (exp centered on the chunk midpoint to keep both factors well-scaled); a dedicated solve kernel inverts the 64x64 unit-lower- triangular system as a 4x4 grid of 16x16 blocks (forward substitution on diagonal blocks, tf32 tl.dot block back-substitution off-diagonal); project kernel forms w/u/kg; state kernel walks the inter-chunk recurrence keeping the 128xBV fp32 state in registers and materializes per-chunk states; output kernel then computes o = qg@S + tril(Aqk)@v_new fully parallel over chunks. Fresh torch.empty workspace every forward, no memoization, no data_ptr identity gate, no CUDA graphs. No fla imports or forbidden ops (agent self-checked with rg for chunk_kda/fused_recurrent/ naive_* before finishing). peak_fraction 0.0154 is an honest low number consistent with other clean KDA cells (~0.018 fable). template_mutated=false.

20260721_142442_codex_gpt-5.6-sol_02_kda_cutlass