tilelang.tileop.gemm.gemm_wgmma¶

Classes¶

GemmWGMMA

Module Contents¶

class tilelang.tileop.gemm.gemm_wgmma.GemmWGMMA¶

Bases: tilelang.tileop.gemm.gemm_base.GemmBase

infer_shared_layout(continuity)¶

Infer the swizzle layout for shared memory based on continuity.

WGMMA can directly use shared memory as input, so the swizzle layout must match the tensor core’s access pattern. The swizzle granularity is determined by the continuous dimension size:

  • 128B swizzle (Full): continuity % (vectorized_size * 8) == 0

  • 64B swizzle (Half): continuity % (vectorized_size * 4) == 0

  • 32B swizzle (Quarter): continuity % (vectorized_size * 2) == 0

  • Linear (no swizzle): otherwise

See: https://docs.nvidia.com/cuda/cuda-driver-api/group__CUDA__TENSOR__MEMORY.html

Parameters:

continuity (int)

Return type:

Callable[[tvm.tir.Buffer], tilelang.layout.Layout]

infer_layout(target, thread_nums)¶
Parameters:

  • target (tvm.target.Target)

  • thread_nums (int)

lower(layout_map, target, thread_bounds, thread_var)¶
Parameters:

  • layout_map (dict)

  • target (tvm.target.Target)

  • thread_bounds (tvm.ir.Range)

  • thread_var (tvm.tir.Var)

is_gemm_ss()¶
Return type:

bool

is_gemm_sr()¶
Return type:

bool

is_gemm_rs()¶
Return type:

bool

is_gemm_rr()¶
Return type:

bool