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Mojo function

matmul_dispatch_sm100_bf16

def matmul_dispatch_sm100_bf16[c_type: DType, a_type: DType, b_type: DType, //, transpose_b: Bool = True, elementwise_lambda_fn: Optional[def[dtype: DType, width: SIMDLength, *, alignment: Int = Int(1)](IndexList[Int(2)], SIMD[dtype, width]) capturing thin -> None] = None, elementwise_lambda_wrapper: Optional[def[dtype: DType, width: SIMDLength, *, alignment: Int = Int(1)](IndexList[Int(2)], SIMD[dtype, width]) capturing thin -> None] = None, elementwise_compute_lambda_fn: Optional[def[dtype: DType, width: SIMDLength, *, alignment: Int = Int(1)](IndexList[Int(2)], SIMD[dtype, width]) capturing thin -> SIMD[dtype, width]] = None, pdl_level: PDLLevel = PDLLevel()](c: TileTensor[c_type, Storage=c.Storage, address_space=c.address_space, linear_idx_type=c.linear_idx_type], a: TileTensor[a_type, Storage=a.Storage, address_space=a.address_space, linear_idx_type=a.linear_idx_type], b: TileTensor[b_type, Storage=b.Storage, address_space=b.address_space, linear_idx_type=b.linear_idx_type], ctx: DeviceContext) -> Int

Dispatches a bfloat16-input SM100 matmul to a tuned or heuristic config.

Routes known low-performance shapes to vendor BLAS, tries the small-MN GEMM tuning table for matched (N, K), then falls back to the heuristic outlier dispatch and finally the default SM100 config on a miss.

Parameters:

c_type (DType): Output element type (inferred).
a_type (DType): Element type of the LHS operand a (inferred).
b_type (DType): Element type of the RHS operand b (inferred).
transpose_b (Bool): Whether b is stored transposed (defaults to True).
elementwise_lambda_fn (Optional[def[dtype: DType, width: SIMDLength, *, alignment: Int = Int(1)](IndexList[Int(2)], SIMD[dtype, width]) capturing thin -> None]): Optional epilogue applied to each output element, passed to the SM100 GEMM path (defaults to None).
elementwise_lambda_wrapper (Optional[def[dtype: DType, width: SIMDLength, *, alignment: Int = Int(1)](IndexList[Int(2)], SIMD[dtype, width]) capturing thin -> None]): Optional epilogue lambda for vendor BLAS and small-MN GEMM paths, folding in the compute lambda (defaults to None).
elementwise_compute_lambda_fn (Optional[def[dtype: DType, width: SIMDLength, *, alignment: Int = Int(1)](IndexList[Int(2)], SIMD[dtype, width]) capturing thin -> SIMD[dtype, width]]): Optional compute epilogue lambda, for example a static scale, passed to the SM100 GEMM path (defaults to None).
pdl_level (PDLLevel): Programmatic dependent launch level for the dispatched kernel (defaults to PDLLevel()).

Returns:

Int