tilelang.intrinsics.tcgen05_macro_generator¶
Attributes¶
Classes¶
Enum where members are also (and must be) ints |
|
To eliminate Python syntax within TIR Macro. |
Module Contents¶
- tilelang.intrinsics.tcgen05_macro_generator.lift¶
- class tilelang.intrinsics.tcgen05_macro_generator.SwizzleMode¶
Bases:
enum.IntEnumEnum where members are also (and must be) ints
- NONE = 0¶
- SWIZZLE_128B = 2¶
- SWIZZLE_64B = 4¶
- SWIZZLE_32B = 6¶
- swizzle_byte_size()¶
- Return type:
int
- swizzle_atom_size()¶
- Return type:
int
- class tilelang.intrinsics.tcgen05_macro_generator.TensorCoreIntrinEmitter(a_dtype='float16', b_dtype='float16', accum_dtype='float16', a_transposed=False, b_transposed=False, block_row_warps=2, block_col_warps=2, warp_row_tiles=8, warp_col_tiles=8, chunk=16, reduce_k=1, num_elems_per_byte=1, is_m_first=False, thread_var=None)¶
Bases:
tilelang.intrinsics.mma_macro_generator.TensorCoreIntrinEmitterTo eliminate Python syntax within TIR Macro.
- Parameters:
- tcgen05_prefix: str¶
- tcgen05mma(A_buf, B_buf, C_local_buf, mbar, clear_accum=False)¶
- Parameters:
A_buf (tvm.tir.Buffer)
B_buf (tvm.tir.Buffer)
C_local_buf (tvm.tir.Buffer)
clear_accum (tvm.tir.PrimExpr)
- abstract make_mma_load_layout(local_buf, matrix='A')¶
Create a layout function for storing MMA results into a fragment buffer. This layout is used in conjunction with inverse_mma_store_layout to map fragment indices to threads and local indices.
- Parameters:
local_buf (tir.Buffer) – The local buffer representing a fragment of a matrix.
matrix (str)
- Returns:
A fragment object that describes how threads and indices in local_buf are laid out.
- Return type:
T.Fragment
- Raises:
AssertionError – If local_buf is not detected to be a fragment buffer.
- make_mma_store_layout(tmem_buf)¶
Create the TCGEN5 tensor-memory layout used to store MMA accumulators.
- Parameters:
tmem_buf (tir.Buffer) – The local buffer representing tensormemory of a mma’s output
- Returns:
Layout object describing how logical (i, j) coordinates map to the swizzled tensor-memory offsets required by TCGEN5MMA.
- Return type:
- Raises:
AssertionError – If tmem_buf is not detected to be a tensor-memory buffer.
- get_tcgen5_mma_meta(m, n, k)¶
- Parameters:
m (int)
n (int)
k (int)