example_gemm.py 1.36 KB
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import tilelang
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import tilelang.language as T
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def matmul(M, N, K, block_M, block_N, block_K, dtype="float16", accum_dtype="float"):
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    @T.prim_func
    def main(
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            A: T.Tensor((M, K), dtype),
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            B: T.Tensor((K, N), dtype),
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            C: T.Tensor((M, N), dtype),
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    ):
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        with T.Kernel(T.ceildiv(N, block_N), T.ceildiv(M, block_M), threads=128) as (bx, by):
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            A_shared = T.alloc_shared((block_M, block_K), dtype)
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            B_shared = T.alloc_shared((block_K, block_N), dtype)
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            C_local = T.alloc_fragment((block_M, block_N), accum_dtype)
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            T.clear(C_local)
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            for k in T.Pipelined(T.ceildiv(K, block_K), num_stages=3):
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                T.copy(A[by * block_M, k * block_K], A_shared)
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                T.copy(B[k * block_K, bx * block_N], B_shared)
                T.gemm(A_shared, B_shared, C_local)

            T.copy(C_local, C[by * block_M, bx * block_N])
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    return main

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func = matmul(1024, 1024, 1024, 128, 128, 32)

print(func)

kernel = tilelang.compile(func, out_idx=-1)

import torch

a = torch.randn(1024, 1024).cuda().half()
b = torch.randn(1024, 1024).cuda().half()

c = kernel(a, b)

ref_c = a @ b

print("c:")
print(c)
print("ref_c:")
print(ref_c)

torch.testing.assert_close(c, ref_c, rtol=1e-2, atol=1e-2)
print("All check passed.")

# Get CUDA Source
print("CUDA Source:")
print(kernel.get_kernel_source())