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This commit is contained in:
Jokeren
2022-11-28 13:00:26 -08:00
parent f605d95b82
commit 2f9aef1132
1 changed files with 2 additions and 1 deletions
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3
python/tutorials/03-matrix-multiplication.py
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@@ -24,6 +24,7 @@ module attributes {"triton_gpu.num-warps" = 8 : i32} {
%c2_i32 = arith.constant 2 : i32 %c2_i32 = arith.constant 2 : i32
%c64 = arith.constant 64 : index %c64 = arith.constant 64 : index
%c128 = arith.constant 128 : index %c128 = arith.constant 128 : index
%c256 = arith.constant 256 : index
%cst = arith.constant dense<64> : tensor<128x64xi32, #blocked0> %cst = arith.constant dense<64> : tensor<128x64xi32, #blocked0>
%cst_0 = arith.constant dense<0.000000e+00> : tensor<128x256xf32, #mma> %cst_0 = arith.constant dense<0.000000e+00> : tensor<128x256xf32, #mma>
%c8_i32 = arith.constant 8 : i32 %c8_i32 = arith.constant 8 : i32
@@ -104,7 +105,7 @@ module attributes {"triton_gpu.num-warps" = 8 : i32} {
%67 = tensor.extract_slice %63[0, 0, 0] [1, 64, 256] [1, 1, 1] : tensor<3x64x256xf16, #shared> to tensor<64x256xf16, #shared> %67 = tensor.extract_slice %63[0, 0, 0] [1, 64, 256] [1, 1, 1] : tensor<3x64x256xf16, #shared> to tensor<64x256xf16, #shared>
%68 = tensor.extract_slice %66[0, 0] [128, 16] [1, 1] : tensor<128x64xf16, #shared> to tensor<128x16xf16, #shared> %68 = tensor.extract_slice %66[0, 0] [128, 16] [1, 1] : tensor<128x64xf16, #shared> to tensor<128x16xf16, #shared>
%70 = tensor.extract_slice %67[0, 0] [16, 256] [1, 1] : tensor<64x256xf16, #shared> to tensor<16x256xf16, #shared> %70 = tensor.extract_slice %67[0, 0] [16, 256] [1, 1] : tensor<64x256xf16, #shared> to tensor<16x256xf16, #shared>
%72:14 = scf.for %arg9 = %c0 to %39 step %c128 iter_args(%arg10 = %cst_0, %arg11 = %45, %arg12 = %49, %arg13 = %61, %arg14 = %63, %arg15 = %66, %arg16 = %67, %arg17 = %64, %arg18 = %65, %arg19 = %c64, %arg20 = %c2_i32, %arg21 = %c1_i32, %arg22 = %68, %arg23 = %70) -> (tensor<128x256xf32, #mma>, tensor<128x64x!tt.ptr<f16>, #blocked0>, tensor<64x256x!tt.ptr<f16>, #blocked1>, tensor<3x128x64xf16, #shared>, tensor<3x64x256xf16, #shared>, tensor<128x64xf16, #shared>, tensor<64x256xf16, #shared>, tensor<128x64x!tt.ptr<f16>, #blocked0>, tensor<64x256x!tt.ptr<f16>, #blocked1>, index, i32, i32, tensor<128x16xf16, #shared>, tensor<16x256xf16, #shared>) { %72:14 = scf.for %arg9 = %c0 to %39 step %c256 iter_args(%arg10 = %cst_0, %arg11 = %45, %arg12 = %49, %arg13 = %61, %arg14 = %63, %arg15 = %66, %arg16 = %67, %arg17 = %64, %arg18 = %65, %arg19 = %c64, %arg20 = %c2_i32, %arg21 = %c1_i32, %arg22 = %68, %arg23 = %70) -> (tensor<128x256xf32, #mma>, tensor<128x64x!tt.ptr<f16>, #blocked0>, tensor<64x256x!tt.ptr<f16>, #blocked1>, tensor<3x128x64xf16, #shared>, tensor<3x64x256xf16, #shared>, tensor<128x64xf16, #shared>, tensor<64x256xf16, #shared>, tensor<128x64x!tt.ptr<f16>, #blocked0>, tensor<64x256x!tt.ptr<f16>, #blocked1>, index, i32, i32, tensor<128x16xf16, #shared>, tensor<16x256xf16, #shared>) {
%69 = triton_gpu.convert_layout %arg22 : (tensor<128x16xf16, #shared>) -> tensor<128x16xf16, #triton_gpu.dot_op<{opIdx = 0, parent = #mma}>> %69 = triton_gpu.convert_layout %arg22 : (tensor<128x16xf16, #shared>) -> tensor<128x16xf16, #triton_gpu.dot_op<{opIdx = 0, parent = #mma}>>
%71 = triton_gpu.convert_layout %arg23 : (tensor<16x256xf16, #shared>) -> tensor<16x256xf16, #triton_gpu.dot_op<{opIdx = 1, parent = #mma}>> %71 = triton_gpu.convert_layout %arg23 : (tensor<16x256xf16, #shared>) -> tensor<16x256xf16, #triton_gpu.dot_op<{opIdx = 1, parent = #mma}>>
%89 = tt.dot %69, %71, %arg10 {allowTF32 = true, transA = false, transB = false} : tensor<128x16xf16, #triton_gpu.dot_op<{opIdx = 0, parent = #mma}>> * tensor<16x256xf16, #triton_gpu.dot_op<{opIdx = 1, parent = #mma}>> -> tensor<128x256xf32, #mma> %89 = tt.dot %69, %71, %arg10 {allowTF32 = true, transA = false, transB = false} : tensor<128x16xf16, #triton_gpu.dot_op<{opIdx = 0, parent = #mma}>> * tensor<16x256xf16, #triton_gpu.dot_op<{opIdx = 1, parent = #mma}>> -> tensor<128x256xf32, #mma>