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Mojo struct

BlackwellBlockScaledMatmulKernel

struct BlackwellBlockScaledMatmulKernel[a_type: DType, b_type: DType, c_type: DType, sfa_dtype: DType, sfb_dtype: DType, a_layout: Layout, b_layout: Layout, c_layout: Layout, sfa_layout: Layout, sfb_layout: Layout, a_desc_layout: Layout, b_desc_layout: Layout, c_desc_layout: Layout, sfa_desc_layout: Layout, sfb_desc_layout: Layout, transpose_b: Bool, config: BlockScaledMatmulConfig[a_type, b_type, c_type, sfa_dtype, sfb_dtype, transpose_b], cluster_shape: StaticTuple[Int32, 3] = StaticTuple[Int32, 3](1), elementwise_compute_lambda_fn: OptionalReg[fn[dtype: DType, width: Int, *, alignment: Int = 1](IndexList[2], SIMD[dtype, width]) capturing -> SIMD[dtype, width]] = None, register_based_epilogue: Bool = True, pdl_level: PDLLevel = PDLLevel(), max_profiled_tiles_per_SM: UInt32 = 0]

Block-scaled matmul kernel V3 - ported from working legacy kernel.

This struct provides the structured interface while internally using the proven legacy kernel logic.

Implemented traits​

AnyType, ImplicitlyDestructible

comptime members​

__del__is_trivial​

comptime __del__is_trivial = True

a_expected_bytes​

comptime a_expected_bytes = (BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].a_smem_layout.size() * size_of[a_type]())

a_smem_layout​

comptime a_smem_layout = tile_layout_k_major[a_type, BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].BM, BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].BK, config.a_swizzle]()

a_tma_load_size​

comptime a_tma_load_size = a_desc_layout.size()

a_tma_rows​

comptime a_tma_rows = a_desc_layout.shape[1].value()

accum_pipeline_consumer_arv_count​

comptime accum_pipeline_consumer_arv_count = (BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].cta_group * BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].EPILOGUE_THREADS)

accum_pipeline_producer_arv_count​

comptime accum_pipeline_producer_arv_count = 1

accum_type​

comptime accum_type = DType.float32

b_expected_bytes​

comptime b_expected_bytes = (BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].b_smem_layout.size() * size_of[b_type]())

b_smem_layout​

comptime b_smem_layout = tile_layout_k_major[b_type, BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].BN, BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].BK, config.b_swizzle]() if transpose_b else tile_layout_mn_major[b_type, BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].BN, BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].BK, config.b_swizzle]()

b_tma_load_size​

comptime b_tma_load_size = b_desc_layout.size()

b_tma_rows​

comptime b_tma_rows = b_desc_layout.shape[1].value()

BK​

comptime BK = config.block_tile_shape.__getitem__[3, DType.int64, Int](2)

BM​

comptime BM = config.block_tile_shape.__getitem__[3, DType.int64, Int](0)

BN​

comptime BN = config.block_tile_shape.__getitem__[3, DType.int64, Int](1)

c_smem_layout​

comptime c_smem_layout = Layout.row_major(BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].OutputM, BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].OutputN)

clc_consumer_arv_count​

comptime clc_consumer_arv_count = (BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].SCHEDULER_THREADS + (BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].CLUSTER_SIZE * ((BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].TMA_LOAD_THREADS + BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].MMA_THREADS) + BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].EPILOGUE_THREADS)))

clc_producer_arv_count​

comptime clc_producer_arv_count = 1

clc_throttle_consumer_arv_count​

comptime clc_throttle_consumer_arv_count = BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].SCHEDULER_THREADS

clc_throttle_producer_arv_count​

comptime clc_throttle_producer_arv_count = BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].TMA_LOAD_THREADS

CLUSTER_M​

comptime CLUSTER_M = Int.__init__[Int](config.cluster_shape.__getitem__[3, DType.int64, Int](0))

CLUSTER_N​

comptime CLUSTER_N = Int.__init__[Int](config.cluster_shape.__getitem__[3, DType.int64, Int](1))

CLUSTER_SIZE​

comptime CLUSTER_SIZE = (BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].CLUSTER_M * BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].CLUSTER_N)

Context​

comptime Context = KernelContext[BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].num_clc_pipeline_stages, BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].cta_group, BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].CLUSTER_M, BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].CLUSTER_N]

cta_group​

comptime cta_group = config.cta_group

EPILOGUE_THREADS​

comptime EPILOGUE_THREADS = (4 * WARP_SIZE)

EpilogueCtx​

comptime EpilogueCtx = EpilogueWarpContext[Int(config), BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].stage_stride_cols, BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].cta_group, BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].MMA_THREADS, BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].EPILOGUE_THREADS]

input_expected_bytes​

comptime input_expected_bytes = ((BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].cta_group * (((BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].a_expected_bytes + BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].b_expected_bytes) + BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].sfa_expected_bytes) + BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].sfb_expected_bytes)) * Int(config))

InputTilePipeline​

comptime InputTilePipeline = InputTilePipeline[BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].TilePayload, BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].SmemType.num_group_pipeline_stages, Int(config)]

max_tmem_cols​

comptime max_tmem_cols = 512

MMA_K​

comptime MMA_K = config.mma_shape.__getitem__[3, DType.int64, Int](2)

MMA_M​

comptime MMA_M = config.mma_shape.__getitem__[3, DType.int64, Int](0)

MMA_N​

comptime MMA_N = config.mma_shape.__getitem__[3, DType.int64, Int](1)

MMA_THREADS​

comptime MMA_THREADS = WARP_SIZE

MmaCtx​

comptime MmaCtx = MmaWarpContext[Int(config), BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].stage_stride_cols, BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].cta_group, BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].MMA_THREADS, BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].EPILOGUE_THREADS]

MmaEpilogueSync​

comptime MmaEpilogueSync = WarpGroupBarrier[(BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].MMA_THREADS + BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].EPILOGUE_THREADS), 1]

MmaOp​

comptime MmaOp = MmaOpSM100_BlockScaled_SS[c_type, a_type, b_type, sfa_dtype, sfb_dtype, config.scaling_kind, config.block_tile_shape, config.mma_shape, cta_group=BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].cta_group, cluster_shape=config.cluster_shape, a_swizzle=config.a_swizzle, b_swizzle=config.b_swizzle, transpose_b=transpose_b]

num_accum_pipeline_stages​

comptime num_accum_pipeline_stages = Int(config)

num_clc_pipeline_stages​

comptime num_clc_pipeline_stages = Int(config)

num_group_pipeline_stages​

comptime num_group_pipeline_stages = (BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].num_pipeline_stages // Int(config))

num_output_stages​

comptime num_output_stages = Int(config)

num_output_warps​

comptime num_output_warps = 4

num_pipeline_stages​

comptime num_pipeline_stages = Int(config)

NUM_THREADS​

comptime NUM_THREADS = (((BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].SCHEDULER_THREADS + BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].TMA_LOAD_THREADS) + BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].MMA_THREADS) + BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].EPILOGUE_THREADS)

NUM_TMEM_COLS​

comptime NUM_TMEM_COLS = 512

OutputM​

comptime OutputM = config.output_tile_shape.__getitem__[2, DType.int64, Int](0)

OutputN​

comptime OutputN = config.output_tile_shape.__getitem__[2, DType.int64, Int](1)

OutputPipeline​

comptime OutputPipeline = OutputTilePipeline[Int(config), BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].stage_stride_cols, BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].cta_group]

Scheduler​

comptime Scheduler = TileScheduler[BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].num_clc_pipeline_stages, Index[dtype=DType.uint32](config.cluster_shape.__getitem__[3, DType.int64, Int](0), config.cluster_shape.__getitem__[3, DType.int64, Int](1), config.cluster_shape.__getitem__[3, DType.int64, Int](2)), config.raster_order, config.block_swizzle_size]

SCHEDULER_THREADS​

comptime SCHEDULER_THREADS = WARP_SIZE

SF_K_GROUP_SIZE​

comptime SF_K_GROUP_SIZE = (4 * config)

sfa_expected_bytes​

comptime sfa_expected_bytes = (BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].sfa_smem_layout.size() * size_of[sfa_dtype]())

SFA_NUM_COLS​

comptime SFA_NUM_COLS = (config * (BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].BM // 32))

sfa_smem_layout​

comptime sfa_smem_layout = tile_sf_layout_k_major[BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].BM, (BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].SF_K_GROUP_SIZE * config), config.vec_sf_size]()

sfb_expected_bytes​

comptime sfb_expected_bytes = (BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].sfb_smem_layout.size() * size_of[sfb_dtype]())

SFB_NUM_COLS​

comptime SFB_NUM_COLS = (config * (BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].MMA_N // 32))

sfb_smem_layout​

comptime sfb_smem_layout = tile_sf_layout_k_major[BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].MMA_N, (BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].SF_K_GROUP_SIZE * config), config.vec_sf_size]()

SmemType​

comptime SmemType = BlockScaledSmem[a_type, b_type, c_type, sfa_dtype, sfb_dtype, transpose_b, config=config]

stage_stride_cols​

comptime stage_stride_cols = BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].MMA_N

TilePayload​

comptime TilePayload = BlockScaledTilePayload[a_type, b_type, sfa_dtype, sfb_dtype, BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].SmemType.a_smem_layout, BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].SmemType.b_smem_layout, BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].SmemType.sfa_smem_layout, BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].SmemType.sfb_smem_layout, BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].SmemType.num_pipeline_stages]

TileWriterType​

comptime TileWriterType = BlockScaledTileWriter[a_type, DType.float32, config.block_tile_shape, config.mma_shape, BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].cta_group, Int(config), config.c_swizzle, config.AB_swapped, BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].SmemType.c_smem_layout, Int(config), BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].stage_stride_cols, 4]

TMA_LOAD_THREADS​

comptime TMA_LOAD_THREADS = WARP_SIZE

Tmem​

comptime Tmem = TmemAllocation[BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].cta_group]

TmemDealloc​

comptime TmemDealloc = TmemDeallocBarrier[BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].cta_group]

Methods​

load_input_tiles​

static load_input_tiles[tiles_origin: MutOrigin, //](a_tma_op: TMATensorTile[a_type, a_layout, a_desc_layout], b_tma_op: TMATensorTile[b_type, b_layout, b_desc_layout], sfa_tma_op: TMATensorTile[sfa_dtype, sfa_layout, sfa_desc_layout], sfb_tma_op: TMATensorTile[sfb_dtype, sfb_layout, sfb_desc_layout], tiles: InputProducerStage[tiles_origin, BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].TilePayload, BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].SmemType.num_group_pipeline_stages, Int(config)], peer_cta_coord: Tuple[UInt, UInt, UInt], work_tile_coord: Tuple[UInt, UInt, UInt], a_multicast_mask: UInt16, b_multicast_mask: UInt16, iter_idx: UInt32, elect_one_cta: Bool)

Load A, B, SFA, SFB tiles using TMA with InputProducerStage.

This method uses the structured ProducerStage pattern from matmul_kernels.mojo, with tiles and barrier encapsulated in the stage.

Args:

  • ​a_tma_op (TMATensorTile): TMA descriptor for A matrix.
  • ​b_tma_op (TMATensorTile): TMA descriptor for B matrix.
  • ​sfa_tma_op (TMATensorTile): TMA descriptor for A scaling factors.
  • ​sfb_tma_op (TMATensorTile): TMA descriptor for B scaling factors.
  • ​tiles (InputProducerStage): ProducerStage context with encapsulated tile access.
  • ​peer_cta_coord (Tuple): (rank_n, rank_m, peer_m_rank) for peer CTA slicing.
  • ​work_tile_coord (Tuple): (m, n, k_start) coordinates of the work tile.
  • ​a_multicast_mask (UInt16): Multicast mask for A tiles.
  • ​b_multicast_mask (UInt16): Multicast mask for B tiles.
  • ​iter_idx (UInt32): K iteration index (base index for k_group).
  • ​elect_one_cta (Bool): True if this CTA should call expect_bytes.

mma​

static mma[tiles_origin: MutOrigin, //](tiles: InputConsumerStage[tiles_origin, BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].TilePayload, BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].SmemType.num_group_pipeline_stages, Int(config)], mma_op: MmaOpSM100_BlockScaled_SS[c_type, a_type, b_type, sfa_dtype, sfb_dtype, config.scaling_kind, config.block_tile_shape, config.mma_shape, cta_group=BlackwellBlockScaledMatmulKernel[a_type, b_type, c_type, sfa_dtype, sfb_dtype, a_layout, b_layout, c_layout, sfa_layout, sfb_layout, a_desc_layout, b_desc_layout, c_desc_layout, sfa_desc_layout, sfb_desc_layout, transpose_b, config, cluster_shape, elementwise_compute_lambda_fn, register_based_epilogue, pdl_level, max_profiled_tiles_per_SM].cta_group, cluster_shape=config.cluster_shape, a_swizzle=config.a_swizzle, b_swizzle=config.b_swizzle, transpose_b=transpose_b], tmem_addr: UInt32, sfa_tmem: UInt32, sfb_tmem: UInt32, iter_idx: UInt32, k_start: UInt32)

Execute MMA operations using InputConsumerStage.

This method uses the structured ConsumerStage pattern from matmul_kernels.mojo, with tiles and barrier encapsulated in the stage.

Args:

  • ​tiles (InputConsumerStage): ConsumerStage context with encapsulated tile access.
  • ​mma_op (MmaOpSM100_BlockScaled_SS): Block-scaled MMA operation instance.
  • ​tmem_addr (UInt32): TMEM address for accumulators.
  • ​sfa_tmem (UInt32): TMEM base address for A scaling factors.
  • ​sfb_tmem (UInt32): TMEM base address for B scaling factors.
  • ​iter_idx (UInt32): K iteration index.
  • ​k_start (UInt32): Starting K iteration (for init_c determination).

epilogue​

static epilogue(c_tiles: SMemTileArrayType[c_type, BlockScaledSmem[a_type, b_type, c_type, sfa_dtype, sfb_dtype, transpose_b, config=config].c_smem_layout, BlockScaledSmem[a_type, b_type, c_type, sfa_dtype, sfb_dtype, transpose_b, config=config].num_output_stages, 128], c_tma_op: TMATensorTile[c_type, c_layout, c_desc_layout], mma_output_pipeline: ProducerConsumerPipeline[Int(config)], tmem_addr: UInt32, work_tile_coord: Tuple[UInt32, UInt32, UInt32], elect_one_warp: Bool, M: UInt32, N: UInt32)

Execute epilogue to store accumulated results to global memory.

Uses BlockScaledTileWriter which encapsulates:

  • TmemArrayType.load_fragments() for TMEM load
  • AccumBarrier.arrive() for barrier signaling
  • TMEMToSMemWriter.write_fragments() for SMEM write
  • 3D TMA store (M, N, Batch coordinates)
  • tma_wait_pipelined() for TMA wait

Args:

  • ​c_tiles (SMemTileArrayType): SMEM tile array for C output.
  • ​c_tma_op (TMATensorTile): TMA descriptor for C matrix.
  • ​mma_output_pipeline (ProducerConsumerPipeline): Pipeline for MMA→epilogue sync.
  • ​tmem_addr (UInt32): Base TMEM address for accumulators.
  • ​work_tile_coord (Tuple): (m, n, k_start) coordinates.
  • ​elect_one_warp (Bool): Whether this warp should execute (unused).
  • ​M (UInt32): Problem M dimension.
  • ​N (UInt32): Problem N dimension.

validate_config​

static validate_config()

Validate configuration constraints at compile time.

run​

static run(a_tma_op: TMATensorTile[a_type, a_layout, a_desc_layout], b_tma_op: TMATensorTile[b_type, b_layout, b_desc_layout], c_tma_op: TMATensorTile[c_type, c_layout, c_desc_layout], sfa_tma_op: TMATensorTile[sfa_dtype, sfa_layout, sfa_desc_layout], sfb_tma_op: TMATensorTile[sfb_dtype, sfb_layout, sfb_desc_layout], cluster_dim: StaticTuple[Int32, 3], mnk: StaticTuple[UInt32, 3], workspace: Span[UInt64, MutAnyOrigin])

Kernel entry point - ported from legacy kernel.

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