Mojo module
utils
comptime values
elementwise_compute_lambda_type
comptime elementwise_compute_lambda_type = def[dtype: DType, width: Int, *, alignment: Int = 1](IndexList[2], SIMD[dtype, width]) capturing -> SIMD[dtype, width]
elementwise_epilogue_type
comptime elementwise_epilogue_type = def[dtype: DType, width: Int, *, alignment: Int = 1](IndexList[2], SIMD[dtype, width]) capturing -> None
Structs
-
GemmShape: Helper class to unpack gemm dimension and layout. -
InnerKernelID: -
KernelConfig: Static configuration of the matmul inner kernel. -
MicroKernelShape: Record describing the inner kernel shape. -
SubMatmulConfig: Static configuration of sub-matrices in parallel matmul.
Functions
-
apply_epilogue: -
calculate_tile_n_k: Helper heuristic function to decide on tile size to partition the matmul given the cache size and desired data layout. -
dispatch_get_kernel_type: -
get_kernel_config: Utility function to extract matmul configuration parameters for exported Functions. TODO: Add target dependent configuration parameters. -
get_kernel_type: -
get_matmul_arch_factor: -
get_matmul_kernel_shape: -
get_matmul_kernel_shape_ARM: -
get_matmul_kernel_shape_x86: -
get_matmul_num_tasks: Compute the number of tasks for parallel matmul. The max number of tasks is typically the number of threads/cores. -
get_matmul_prefetch_b_distance_k: -
get_min_task_size: -
get_pack_data_size: Utility to compute the number of elements to pack in each tile. Returns: The number of elements to pack. -
get_packB_unroll_factor: -
get_partitioned_matmul: -
get_partitioned_matmul_mojo: -
get_partitioned_matmul_mojo_shape: -
packA_i8mm: -
partial_simd_load: Loads a vector with dynamic bound. -
partial_simd_store: Stores a vector with dynamic bound. -
partition_work: -
select_inner_kernel: -
use_i8mm_fn: -
use_vnni_fn:
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