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fix: replace TMEM round-trip normalize with CUTLASS correction_epilog pattern

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biondizzle
2026-05-23 01:18:56 +00:00
parent 690fd77e6c
commit 3c134f7e90
1 changed files with 72 additions and 34 deletions
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106
tests/unit/test_fmha_v3_stage_c.py
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@@ -399,48 +399,86 @@ class FmhaV3StageCMulti:
# Wait for MMA's PV[N-1] to commit before reading O.
final_o_bar.arrive_and_wait()
# === Final O normalization: O *= 1/row_sum ===
# DIAG: use 1.0 instead of 1/row_sum to test raw PV output
inv_row_sum = Float32(1.0)
# === Final O normalization + epilogue: CUTLASS correction_epilog pattern ===
# ONE-WAY trip: TMEM → reg (normalize + FP32→BF16) → SMEM → TMA → GMEM
# NO TMEM round-trip. Hand-constructed atoms corrupt data on round-trip.
inv_row_sum = Float32(1.0) / row_sum
tTMrO = cute.make_rmem_tensor(
(tTMEM_LOADcO.shape, 128 // corr_tile_size), self.acc_dtype
# Build paired atoms for TMEM load → SMEM store
epi_corr_tile_size = 32 * 8 // self.o_dtype.width # 16 for BF16
epi_subtile = (self.epi_tile[0], epi_corr_tile_size)
tOsO = pv_thr.partition_C(sC)
cO_epi = cute.make_identity_tensor((self.pv_mma_tiler[0], self.pv_mma_tiler[1]))
tOcO_epi = pv_thr.partition_C(cO_epi)
tOtO_epi = cute.logical_divide(tOtO0, cute.make_layout((128, epi_corr_tile_size)))
tOsO_epi = cute.logical_divide(tOsO, cute.make_layout((128, epi_corr_tile_size)))
tOcO_epi = cute.logical_divide(tOcO_epi, cute.make_layout((128, epi_corr_tile_size)))
tmem_load_epi_atom = utils.sm100.get_tmem_load_op(
self.pv_mma_tiler,
self.c_layout,
self.o_dtype,
self.acc_dtype,
epi_subtile,
use_2cta_instrs=False,
)
tiled_tmem_load_epi = tcgen05.make_tmem_copy(
tmem_load_epi_atom, tOtO_epi[(None, None), 0]
)
thr_tmem_load_epi = tiled_tmem_load_epi.get_slice(sfw_idx)
smem_store_epi_atom = utils.sm100.get_smem_store_op(
self.c_layout,
self.o_dtype,
self.acc_dtype,
tiled_tmem_load_epi,
)
tiled_smem_store_epi = cute.make_tiled_copy_D(
smem_store_epi_atom, tiled_tmem_load_epi
)
for i in range(n_corr_tiles):
tTMrO_i_ = tTMrO[None, i]
tTMrO_i_layout = cute.composition(
tTMrO_i_.layout, cute.make_layout(tTMrO.shape[0])
)
tTMrO_i = cute.make_tensor(tTMrO_i_.iterator, tTMrO_i_layout)
tTMEM_LOADtO_i = cute.make_tensor(
tTMEM_LOADtO.iterator + i * corr_tile_size, tTMEM_LOADtO.layout
)
tTMEM_STOREtO_i = cute.make_tensor(
tTMEM_STOREtO.iterator + i * corr_tile_size, tTMEM_STOREtO.layout
)
tTMEM_LOADtO_epi = thr_tmem_load_epi.partition_S(tOtO_epi[(None, None), None])
tTMEM_LOADsO_epi = thr_tmem_load_epi.partition_D(tOsO_epi[(None, None), None])
tTMEM_LOADcO_epi = thr_tmem_load_epi.partition_D(tOcO_epi[(None, None), None])
cute.copy(tiled_tmem_load_o, tTMEM_LOADtO_i, tTMrO_i)
for j in cutlass.range(cute.size(tTMrO_i), vectorize=True):
tTMrO_i[j] = tTMrO_i[j] * inv_row_sum
cute.copy(tiled_tmem_store_o, tTMrO_i, tTMEM_STOREtO_i)
n_epi_corr_tiles = self.pv_mma_tiler[1] // epi_corr_tile_size
for i in range(n_epi_corr_tiles):
tTMEM_LOADtO_epi_i = tTMEM_LOADtO_epi[None, 0, 0, i]
tTMEM_LOADsO_epi_i = tTMEM_LOADsO_epi[None, 0, 0, i]
tTMrO = cute.make_rmem_tensor(
tTMEM_LOADcO_epi[None, 0, 0, i].shape, self.acc_dtype
)
cute.copy(tiled_tmem_load_epi, tTMEM_LOADtO_epi_i, tTMrO)
for j in range(cute.size(tTMrO)):
tTMrO[j] = tTMrO[j] * inv_row_sum
tSMrO = cute.make_rmem_tensor(tTMrO.shape, self.o_dtype)
o_vec = tTMrO.load()
tSMrO.store(o_vec.to(self.o_dtype))
cute.copy(tiled_smem_store_epi, tSMrO, tTMEM_LOADsO_epi_i)
cute.arch.fence_view_async_tmem_store()
cute.arch.fence_proxy("async.shared", space="cta")
# Standard epilogue: TMEM → SMEM → GMEM via TMA store.
# O in TMEM is now scaled by 1/row_sum.
tCtO_base = cute.make_tensor(tmem_ptr + self.tmem_o0_offset, tCtO_fake.layout)
acc_cons_st = pipeline.make_pipeline_state(
pipeline.PipelineUserType.Consumer, self.num_acc_stage
# TMA store: SMEM → GMEM
epi_s_tile = cute.select(self.c_smem_s, mode=[0, 1])
tma_c_epi, mC_epi = cpasync.make_tiled_tma_atom(
cpasync.CopyBulkTensorTileS2GOp(), c, epi_s_tile, self.epi_tile
)
c_grp = pipeline.CooperativeGroup(pipeline.Agent.Thread, 32 * len(self.epilogue_warp_id))
c_pipe = pipeline.PipelineTmaStore.create(num_stages=self.num_c_stage, producer_group=c_grp)
acc_cons_st = utils.gemm.sm100.epilogue_tma_store(
self, tidx, warp_idx, tma_c, tCtO_base, sC, tCgC, epi_tile,
0, const_expr(lambda x: x), (0, 0, 0),
acc_cons_st, acc_pipe, c_pipe,
tCgC_epi = cute.local_tile(mC_epi, cute.slice_(self.pv_mma_tiler, (None, None, 0)), (None, None, None))
tCsC_epi = cute.local_tile(sC, cute.slice_(self.epi_tile, (None, None)), (None, None))
# Sync before TMA store — all softmax warps must finish SMEM writes
softmax_all_bar = pipeline.NamedBarrier(
barrier_id=5, num_threads=32 * len(self.epilogue_warp_id)
)
c_pipe.producer_tail()
softmax_all_bar.arrive_and_wait()
# Warp 0 does the TMA store
if sfw_idx < 32:
cute.copy(tma_c_epi, tCsC_epi, tCgC_epi)
cute.arch.cp_async_bulk_commit_group()
cute.arch.cp_async_bulk_wait_group(0, read=True)
tmem.relinquish_alloc_permit()
tmem.free(tmem_ptr)