biondizzle/nvfp4-megamoe-kernel
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revert grid change to debug regression

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biondizzle
2026-05-25 17:03:19 +00:00
parent aa66f44ff9
commit 0b9f9da2f7
1 changed files with 1 additions and 7 deletions
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8
dsv4/kernels/attention/fmha.py
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@@ -131,13 +131,7 @@ class FmhaKernel:
# CuTeDSL doesn't support None parameters in @cute.kernel.
if const_expr(lse is None):
lse = cute.make_tensor(c.iterator, cute.make_layout((1,), stride=(0,)))
# Grid: (M_tiles, 1, batch) where M = n_h * T packed into M dimension
# At decode T=1, n_h=128: M=128, grid=(1,1,batch) — 1 CTA per batch
# At T=64, n_h=128: M=8192, grid=(64,1,batch) — 64 CTAs per batch
# For single-head (n_h=1): grid=(1,1,1) — backward compatible
M_total = self.num_query_heads # T is implicitly 1 for decode, M = n_h * T
num_M_tiles = math.ceil(M_total / 128) if M_total > 128 else 1
self._kernel(qk_mma,pv_mma,tma_q,mQ,tma_k,mK,tma_v,mV,tma_c,mC,self.cluster_layout_vmnk,self.q_smem_s,self.k_smem_s,self.v_smem_s,self.p_tmem_s,self.p_smem_s,self.c_smem_s,self.epi_tile,lse).launch(grid=(num_M_tiles,1,self.batch_size),block=[self.threads_per_cta,1,1],stream=stream)
self._kernel(qk_mma,pv_mma,tma_q,mQ,tma_k,mK,tma_v,mV,tma_c,mC,self.cluster_layout_vmnk,self.q_smem_s,self.k_smem_s,self.v_smem_s,self.p_tmem_s,self.p_smem_s,self.c_smem_s,self.epi_tile,lse).launch(grid=(1,1,1),block=[self.threads_per_cta,1,1],stream=stream)
@cute.kernel
def _kernel(self, qk_mma, pv_mma, tma_q, mQ, tma_k, mK, tma_v, mV, tma_c, mC, cl_vmnk, q_smem_s, k_smem_s, v_smem_s, p_tmem_s, p_smem_s, c_smem_s, epi_tile, mLSE):