mirror of
https://github.com/tile-ai/tilelang.git
synced 2026-10-21 06:40:23 +08:00
Zhiwen Mo
f58bcd43f1
* update sm100 related utcmma, tmem, ld/st256 in src * update sm100 related utcmma, tmem, ld/st256 in tilelang * Remove deprecated GEMM examples and related README documentation for SM100 architecture support * Update GEMM implementation to replace UTCMMA with TCGEN5MMA across relevant files * Remove gemm_umma.py example and update README to reflect TCGEN5MMA terminology changes * Update README.md for gemm_sm100 example by removing outdated API sections and streamlining documentation * Update README and source files to reflect TCGEN5.MMA terminology changes * Refactor CUDA GEMM header for improved readability
61 lines
1.8 KiB
Python
61 lines
1.8 KiB
Python
import tilelang
|
|
from tilelang import tvm as tvm
|
|
import tilelang.testing
|
|
import tilelang.language as T
|
|
|
|
|
|
def matmul(M, N, K, block_M, block_N, block_K, dtype="float16", accum_dtype="float"):
|
|
|
|
@T.prim_func
|
|
def main(
|
|
A: T.Tensor((M, K), dtype),
|
|
B: T.Tensor((K, N), dtype),
|
|
C: T.Tensor((M, N), dtype),
|
|
):
|
|
# Initialize Kernel Context
|
|
with T.Kernel(T.ceildiv(N, block_N), T.ceildiv(M, block_M), threads=128) as (bx, by):
|
|
A_shared = T.alloc_shared((block_M, block_K), dtype)
|
|
B_shared = T.alloc_shared((block_K, block_N), dtype)
|
|
C_local = T.alloc_fragment((block_M, block_N), accum_dtype)
|
|
|
|
T.clear(C_local)
|
|
|
|
for ko in T.Pipelined(T.ceildiv(K, block_K), num_stages=0):
|
|
T.copy(A[by * block_M, ko * block_K], A_shared, coalesced_width=2)
|
|
T.copy(B[ko * block_K, bx * block_N], B_shared, coalesced_width=2)
|
|
|
|
for i, j, k in T.grid(block_M, block_N, block_K):
|
|
C_local[i, j] += A_shared[i, k] * B_shared[k, j]
|
|
|
|
T.copy(C_local, C[by * block_M, bx * block_N], coalesced_width=2)
|
|
|
|
return main
|
|
|
|
|
|
def assert_gemm_codegen(
|
|
M,
|
|
N,
|
|
K,
|
|
block_M,
|
|
block_N,
|
|
block_K,
|
|
dtype="float16",
|
|
accum_dtype="float",
|
|
):
|
|
func = matmul(M, N, K, block_M, block_N, block_K, dtype=dtype, accum_dtype=accum_dtype)
|
|
# Because the current pass context have been polluted by previous testing.
|
|
with tvm.transform.PassContext(), tvm.target.Target("webgpu"):
|
|
artifact = tilelang.lower(func, target="webgpu")
|
|
|
|
src_code = artifact.kernel_source
|
|
|
|
assert src_code is not None
|
|
|
|
|
|
def test_gemm_codegen():
|
|
assert_gemm_codegen(1024, 1024, 1024, 16, 16, 16)
|
|
|
|
|
|
if __name__ == "__main__":
|
|
tilelang.testing.main()
|