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[OPTIMIZER] Pipeline async buffer (#110)

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This commit is contained in:
Philippe Tillet
2022-09-09 11:01:14 -07:00
committed by GitHub
parent 2a852044d9
commit 9bd5a3dcd2
2 changed files with 90 additions and 57 deletions
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27
test/TritonGPU/loop-pipeline.mlir
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@@ -16,18 +16,16 @@
// CHECK: %[[A1BUFFER:.*]] = triton_gpu.insert_slice_async
// CHECK: %[[B1BUFFER:.*]] = triton_gpu.insert_slice_async
// CHECK: triton_gpu.async_wait {num = 2 : i32}
// CHECK: %[[A0:.*]] = triton_gpu.extract_slice %[[A0BUFFER]]
// CHECK: %[[B0:.*]] = triton_gpu.extract_slice %[[B0BUFFER]]
// CHECK: %[[A1:.*]] = triton_gpu.extract_slice %[[A1BUFFER]]
// CHECK: %[[B1:.*]] = triton_gpu.extract_slice %[[B1BUFFER]]
// CHECK: scf.for {{.*}} iter_args({{.*}}, {{.*}}, {{.*}}, %[[arg_a0:.*]] = %[[A0]], %[[arg_a1:.*]] = %[[A1]], %[[arg_b0:.*]] = %[[B0]], %[[arg_b1:.*]] = %[[B1]], {{.*}})
// CHECK: %[[A0:.*]] = triton_gpu.extract_slice %[[A1BUFFER]]
// CHECK: %[[B0:.*]] = triton_gpu.extract_slice %[[B1BUFFER]]
// CHECK: scf.for {{.*}} iter_args({{.*}}, {{.*}}, {{.*}}, {{.*}}, {{.*}}, %[[arg_a0:.*]] = %[[A0]], %[[arg_b0:.*]] = %[[B0]], {{.*}})
// CHECK: tt.dot %[[arg_a0]], %[[arg_b0]], {{.*}}
// CHECK: %[[NEXT_A_BUFFER:.*]] = triton_gpu.insert_slice_async
// CHECK: %[[NEXT_B_BUFFER:.*]] = triton_gpu.insert_slice_async
// CHECK: triton_gpu.async_wait {num = 2 : i32}
// CHECK: %[[NEXT_A:.*]] = triton_gpu.extract_slice %[[NEXT_A_BUFFER]]
// CHECK: %[[NEXT_B:.*]] = triton_gpu.extract_slice %[[NEXT_B_BUFFER]]
// CHECK: scf.yield {{.*}}, {{.*}}, {{.*}}, %[[arg_a1]], %[[NEXT_A]], %[[arg_b1]], %[[NEXT_B]]
// CHECK: scf.yield {{.*}}, {{.*}}, {{.*}}, %[[NEXT_A_BUFFER]], %[[NEXT_B_BUFFER]], %[[NEXT_A]], %[[NEXT_B]]
func @matmul_loop(%lb : index, %ub : index, %step : index, %A : !tt.ptr<f16>, %B : !tt.ptr<f16>) {
%a_ptr_init = tt.broadcast %A : (!tt.ptr<f16>) -> tensor<128x32x!tt.ptr<f16>, #AL>
%b_ptr_init = tt.broadcast %B : (!tt.ptr<f16>) -> tensor<32x128x!tt.ptr<f16>, #BL>
@@ -66,18 +64,16 @@ func @matmul_loop(%lb : index, %ub : index, %step : index, %A : !tt.ptr<f16>, %B
// CHECK: %[[A1BUFFER:.*]] = triton_gpu.insert_slice_async
// CHECK: %[[B1BUFFER:.*]] = triton_gpu.insert_slice_async
// CHECK: triton_gpu.async_wait {num = 2 : i32}
// CHECK: %[[A0:.*]] = triton_gpu.extract_slice %[[A0BUFFER]]
// CHECK: %[[B0:.*]] = triton_gpu.extract_slice %[[B0BUFFER]]
// CHECK: %[[A1:.*]] = triton_gpu.extract_slice %[[A1BUFFER]]
// CHECK: %[[B1:.*]] = triton_gpu.extract_slice %[[B1BUFFER]]
// CHECK: scf.for {{.*}} iter_args({{.*}}, {{.*}}, {{.*}}, %[[arg_a0:.*]] = %[[A0]], %[[arg_a1:.*]] = %[[A1]], %[[arg_b0:.*]] = %[[B0]], %[[arg_b1:.*]] = %[[B1]], {{.*}})
// CHECK: %[[A0:.*]] = triton_gpu.extract_slice %[[A1BUFFER]]
// CHECK: %[[B0:.*]] = triton_gpu.extract_slice %[[B1BUFFER]]
// CHECK: scf.for {{.*}} iter_args({{.*}}, {{.*}}, {{.*}}, {{.*}}, {{.*}}, %[[arg_a0:.*]] = %[[A0]], %[[arg_b0:.*]] = %[[B0]], {{.*}})
// CHECK: tt.dot %[[arg_a0]], %[[arg_b0]], {{.*}}
// CHECK: %[[NEXT_A_BUFFER:.*]] = triton_gpu.insert_slice_async
// CHECK: %[[NEXT_B_BUFFER:.*]] = triton_gpu.insert_slice_async
// CHECK: triton_gpu.async_wait {num = 2 : i32}
// CHECK: %[[NEXT_A:.*]] = triton_gpu.extract_slice %[[NEXT_A_BUFFER]]
// CHECK: %[[NEXT_B:.*]] = triton_gpu.extract_slice %[[NEXT_B_BUFFER]]
// CHECK: scf.yield {{.*}}, {{.*}}, {{.*}}, %[[arg_a1]], %[[NEXT_A]], %[[arg_b1]], %[[NEXT_B]]
// CHECK: scf.yield {{.*}}, {{.*}}, {{.*}}, %[[NEXT_A_BUFFER]], %[[NEXT_B_BUFFER]], %[[NEXT_A]], %[[NEXT_B]]
func @matmul_loop_nested(%lb : index, %ub : index, %step : index, %A : !tt.ptr<f16>, %B : !tt.ptr<f16>) {
scf.for %iv0 = %lb to %ub step %step {
%a_ptr_init = tt.broadcast %A : (!tt.ptr<f16>) -> tensor<128x32x!tt.ptr<f16>, #AL>
@@ -114,14 +110,13 @@ func @matmul_loop_nested(%lb : index, %ub : index, %step : index, %A : !tt.ptr<f
// CHECK: %[[B0BUFFER:.*]] = triton_gpu.insert_slice_async
// CHECK: %[[B1BUFFER:.*]] = triton_gpu.insert_slice_async
// CHECK: triton_gpu.async_wait {num = 1 : i32}
// CHECK: %[[B0:.*]] = triton_gpu.extract_slice %[[B0BUFFER]]
// CHECK: %[[B1:.*]] = triton_gpu.extract_slice %[[B1BUFFER]]
// CHECK: scf.for {{.*}} iter_args({{.*}}, {{.*}}, %[[arg_b0:.*]] = %[[B0]], %[[arg_b1:.*]] = %[[B1]], {{.*}})
// CHECK: %[[B0:.*]] = triton_gpu.extract_slice %[[B1BUFFER]]
// CHECK: scf.for {{.*}} iter_args({{.*}}, {{.*}}, {{.*}}, %[[arg_b0:.*]] = %[[B0]], {{.*}})
// CHECK: tt.dot {{.*}}, %[[arg_b0]], {{.*}}
// CHECK: %[[NEXT_B_BUFFER:.*]] = triton_gpu.insert_slice_async
// CHECK: triton_gpu.async_wait {num = 1 : i32}
// CHECK: %[[NEXT_B:.*]] = triton_gpu.extract_slice %[[NEXT_B_BUFFER]]
// CHECK: scf.yield {{.*}}, {{.*}}, %[[arg_b1]], %[[NEXT_B]]
// CHECK: scf.yield {{.*}}, {{.*}}, %[[NEXT_B_BUFFER]], %[[NEXT_B]]
func @matmul_loop_single_pipeline(%lb : index, %ub : index, %step : index, %A : !tt.ptr<f16>, %B : !tt.ptr<f16>) {
%a_ptr_init = tt.broadcast %A : (!tt.ptr<f16>) -> tensor<128x32x!tt.ptr<f16>, #AL>
%b_ptr_init = tt.broadcast %B : (!tt.ptr<f16>) -> tensor<32x128x!tt.ptr<f16>, #BL>