| // RUN: mlir-opt %s -sparsification="vectorization-strategy=0 vl=16" -cse -split-input-file | \ |
| // RUN: FileCheck %s --check-prefix=CHECK-VEC0 |
| // RUN: mlir-opt %s -sparsification="vectorization-strategy=1 vl=16" -cse -split-input-file | \ |
| // RUN: FileCheck %s --check-prefix=CHECK-VEC1 |
| // RUN: mlir-opt %s -sparsification="vectorization-strategy=2 vl=16" -cse -split-input-file | \ |
| // RUN: FileCheck %s --check-prefix=CHECK-VEC2 |
| // RUN: mlir-opt %s -sparsification="vectorization-strategy=2 vl=16 enable-simd-index32=true" -cse -split-input-file | \ |
| // RUN: FileCheck %s --check-prefix=CHECK-VEC3 |
| |
| #DenseVector = #sparse_tensor.encoding<{ dimLevelType = [ "dense" ] }> |
| |
| #trait_scale_d = { |
| indexing_maps = [ |
| affine_map<(i) -> (i)>, // a |
| affine_map<(i) -> (i)> // x (out) |
| ], |
| iterator_types = ["parallel"], |
| doc = "x(i) = a(i) * b" |
| } |
| |
| // |
| // CHECK-VEC0-LABEL: func @scale_d |
| // CHECK-VEC0-DAG: %[[c0:.*]] = arith.constant 0 : index |
| // CHECK-VEC0-DAG: %[[c1:.*]] = arith.constant 1 : index |
| // CHECK-VEC0-DAG: %[[c1024:.*]] = arith.constant 1024 : index |
| // CHECK-VEC0: scf.for %[[i:.*]] = %[[c0]] to %[[c1024]] step %[[c1]] { |
| // CHECK-VEC0: %[[l:.*]] = memref.load %{{.*}}[%[[i]]] : memref<?xf32> |
| // CHECK-VEC0: %[[m:.*]] = arith.mulf %[[l]], %{{.*}} : f32 |
| // CHECK-VEC0: store %[[m]], %{{.*}}[%[[i]]] : memref<1024xf32> |
| // CHECK-VEC0: } |
| // CHECK-VEC0: return |
| // |
| // CHECK-VEC1-LABEL: func @scale_d |
| // CHECK-VEC1-DAG: %[[c0:.*]] = arith.constant 0 : index |
| // CHECK-VEC1-DAG: %[[c16:.*]] = arith.constant 16 : index |
| // CHECK-VEC1-DAG: %[[c1024:.*]] = arith.constant 1024 : index |
| // CHECK-VEC1: scf.for %[[i:.*]] = %[[c0]] to %[[c1024]] step %[[c16]] { |
| // CHECK-VEC1: %[[r:.*]] = vector.load %{{.*}}[%[[i]]] : memref<?xf32>, vector<16xf32> |
| // CHECK-VEC1: %[[b:.*]] = vector.broadcast %{{.*}} : f32 to vector<16xf32> |
| // CHECK-VEC1: %[[m:.*]] = arith.mulf %[[r]], %[[b]] : vector<16xf32> |
| // CHECK-VEC1: vector.store %[[m]], %{{.*}}[%[[i]]] : memref<1024xf32>, vector<16xf32> |
| // CHECK-VEC1: } |
| // CHECK-VEC1: return |
| // |
| // CHECK-VEC2-LABEL: func @scale_d |
| // CHECK-VEC2-DAG: %[[c0:.*]] = arith.constant 0 : index |
| // CHECK-VEC2-DAG: %[[c16:.*]] = arith.constant 16 : index |
| // CHECK-VEC2-DAG: %[[c1024:.*]] = arith.constant 1024 : index |
| // CHECK-VEC2: scf.for %[[i:.*]] = %[[c0]] to %[[c1024]] step %[[c16]] { |
| // CHECK-VEC2: %[[r:.*]] = vector.load %{{.*}}[%[[i]]] : memref<?xf32>, vector<16xf32> |
| // CHECK-VEC2: %[[b:.*]] = vector.broadcast %{{.*}} : f32 to vector<16xf32> |
| // CHECK-VEC2: %[[m:.*]] = arith.mulf %[[r]], %[[b]] : vector<16xf32> |
| // CHECK-VEC2: vector.store %[[m]], %{{.*}}[%[[i]]] : memref<1024xf32>, vector<16xf32> |
| // CHECK-VEC2: } |
| // CHECK-VEC2: return |
| // |
| func @scale_d(%arga: tensor<1024xf32, #DenseVector>, %b: f32, %argx: tensor<1024xf32>) -> tensor<1024xf32> { |
| %0 = linalg.generic #trait_scale_d |
| ins(%arga: tensor<1024xf32, #DenseVector>) |
| outs(%argx: tensor<1024xf32>) { |
| ^bb(%a: f32, %x: f32): |
| %0 = arith.mulf %a, %b : f32 |
| linalg.yield %0 : f32 |
| } -> tensor<1024xf32> |
| return %0 : tensor<1024xf32> |
| } |
| |
| // ----- |
| |
| #SparseVector = #sparse_tensor.encoding<{ |
| dimLevelType = [ "compressed" ], |
| pointerBitWidth = 32, |
| indexBitWidth = 32 |
| }> |
| |
| #trait_mul_s = { |
| indexing_maps = [ |
| affine_map<(i) -> (i)>, // a |
| affine_map<(i) -> (i)>, // b |
| affine_map<(i) -> (i)> // x (out) |
| ], |
| iterator_types = ["parallel"], |
| doc = "x(i) = a(i) * b(i)" |
| } |
| |
| // |
| // CHECK-VEC0-LABEL: func @mul_s |
| // CHECK-VEC0-DAG: %[[c0:.*]] = arith.constant 0 : index |
| // CHECK-VEC0-DAG: %[[c1:.*]] = arith.constant 1 : index |
| // CHECK-VEC0: %[[p:.*]] = memref.load %{{.*}}[%[[c0]]] : memref<?xi32> |
| // CHECK-VEC0: %[[a:.*]] = arith.extui %[[p]] : i32 to i64 |
| // CHECK-VEC0: %[[q:.*]] = arith.index_cast %[[a]] : i64 to index |
| // CHECK-VEC0: %[[r:.*]] = memref.load %{{.*}}[%[[c1]]] : memref<?xi32> |
| // CHECK-VEC0: %[[b:.*]] = arith.extui %[[r]] : i32 to i64 |
| // CHECK-VEC0: %[[s:.*]] = arith.index_cast %[[b]] : i64 to index |
| // CHECK-VEC0: scf.for %[[i:.*]] = %[[q]] to %[[s]] step %[[c1]] { |
| // CHECK-VEC0: %[[li:.*]] = memref.load %{{.*}}[%[[i]]] : memref<?xi32> |
| // CHECK-VEC0: %[[zi:.*]] = arith.extui %[[li]] : i32 to i64 |
| // CHECK-VEC0: %[[ci:.*]] = arith.index_cast %[[zi]] : i64 to index |
| // CHECK-VEC0: %[[la:.*]] = memref.load %{{.*}}[%[[i]]] : memref<?xf32> |
| // CHECK-VEC0: %[[lb:.*]] = memref.load %{{.*}}[%[[ci]]] : memref<1024xf32> |
| // CHECK-VEC0: %[[m:.*]] = arith.mulf %[[la]], %[[lb]] : f32 |
| // CHECK-VEC0: store %[[m]], %{{.*}}[%[[ci]]] : memref<1024xf32> |
| // CHECK-VEC0: } |
| // CHECK-VEC0: return |
| // |
| // CHECK-VEC1-LABEL: func @mul_s |
| // CHECK-VEC1-DAG: %[[c0:.*]] = arith.constant 0 : index |
| // CHECK-VEC1-DAG: %[[c1:.*]] = arith.constant 1 : index |
| // CHECK-VEC1: %[[p:.*]] = memref.load %{{.*}}[%[[c0]]] : memref<?xi32> |
| // CHECK-VEC1: %[[a:.*]] = arith.extui %[[p]] : i32 to i64 |
| // CHECK-VEC1: %[[q:.*]] = arith.index_cast %[[a]] : i64 to index |
| // CHECK-VEC1: %[[r:.*]] = memref.load %{{.*}}[%[[c1]]] : memref<?xi32> |
| // CHECK-VEC1: %[[b:.*]] = arith.extui %[[r]] : i32 to i64 |
| // CHECK-VEC1: %[[s:.*]] = arith.index_cast %[[b]] : i64 to index |
| // CHECK-VEC1: scf.for %[[i:.*]] = %[[q]] to %[[s]] step %[[c1]] { |
| // CHECK-VEC1: %[[li:.*]] = memref.load %{{.*}}[%[[i]]] : memref<?xi32> |
| // CHECK-VEC1: %[[zi:.*]] = arith.extui %[[li]] : i32 to i64 |
| // CHECK-VEC1: %[[ci:.*]] = arith.index_cast %[[zi]] : i64 to index |
| // CHECK-VEC1: %[[la:.*]] = memref.load %{{.*}}[%[[i]]] : memref<?xf32> |
| // CHECK-VEC1: %[[lb:.*]] = memref.load %{{.*}}[%[[ci]]] : memref<1024xf32> |
| // CHECK-VEC1: %[[m:.*]] = arith.mulf %[[la]], %[[lb]] : f32 |
| // CHECK-VEC1: store %[[m]], %{{.*}}[%[[ci]]] : memref<1024xf32> |
| // CHECK-VEC1: } |
| // CHECK-VEC1: return |
| // |
| // CHECK-VEC2: #[[$map:.*]] = affine_map<(d0, d1)[s0] -> (16, d0 - d1) |
| // CHECK-VEC2-LABEL: func @mul_s |
| // CHECK-VEC2-DAG: %[[c0:.*]] = arith.constant 0 : index |
| // CHECK-VEC2-DAG: %[[c1:.*]] = arith.constant 1 : index |
| // CHECK-VEC2-DAG: %[[c16:.*]] = arith.constant 16 : index |
| // CHECK-VEC2: %[[p:.*]] = memref.load %{{.*}}[%[[c0]]] : memref<?xi32> |
| // CHECK-VEC2: %[[a:.*]] = arith.extui %[[p]] : i32 to i64 |
| // CHECK-VEC2: %[[q:.*]] = arith.index_cast %[[a]] : i64 to index |
| // CHECK-VEC2: %[[r:.*]] = memref.load %{{.*}}[%[[c1]]] : memref<?xi32> |
| // CHECK-VEC2: %[[b:.*]] = arith.extui %[[r]] : i32 to i64 |
| // CHECK-VEC2: %[[s:.*]] = arith.index_cast %[[b]] : i64 to index |
| // CHECK-VEC2: scf.for %[[i:.*]] = %[[q]] to %[[s]] step %[[c16]] { |
| // CHECK-VEC2: %[[sub:.*]] = affine.min #[[$map]](%[[s]], %[[i]])[%[[c16]]] |
| // CHECK-VEC2: %[[mask:.*]] = vector.create_mask %[[sub]] : vector<16xi1> |
| // CHECK-VEC2: %[[li:.*]] = vector.maskedload %{{.*}}[%[[i]]], %[[mask]], %{{.*}} : memref<?xi32>, vector<16xi1>, vector<16xi32> into vector<16xi32> |
| // CHECK-VEC2: %[[zi:.*]] = arith.extui %[[li]] : vector<16xi32> to vector<16xi64> |
| // CHECK-VEC2: %[[la:.*]] = vector.maskedload %{{.*}}[%[[i]]], %[[mask]], %{{.*}} : memref<?xf32>, vector<16xi1>, vector<16xf32> into vector<16xf32> |
| // CHECK-VEC2: %[[lb:.*]] = vector.gather %{{.*}}[%[[c0]]] [%[[zi]]], %[[mask]], %{{.*}} : memref<1024xf32>, vector<16xi64>, vector<16xi1>, vector<16xf32> into vector<16xf32> |
| // CHECK-VEC2: %[[m:.*]] = arith.mulf %[[la]], %[[lb]] : vector<16xf32> |
| // CHECK-VEC2: vector.scatter %{{.*}}[%[[c0]]] [%[[zi]]], %[[mask]], %[[m]] : memref<1024xf32>, vector<16xi64>, vector<16xi1>, vector<16xf32> |
| // CHECK-VEC2: } |
| // CHECK-VEC2: return |
| // |
| // CHECK-VEC3: #[[$map:.*]] = affine_map<(d0, d1)[s0] -> (16, d0 - d1) |
| // CHECK-VEC3-LABEL: func @mul_s |
| // CHECK-VEC3-DAG: %[[c0:.*]] = arith.constant 0 : index |
| // CHECK-VEC3-DAG: %[[c1:.*]] = arith.constant 1 : index |
| // CHECK-VEC3-DAG: %[[c16:.*]] = arith.constant 16 : index |
| // CHECK-VEC3: %[[p:.*]] = memref.load %{{.*}}[%[[c0]]] : memref<?xi32> |
| // CHECK-VEC3: %[[a:.*]] = arith.extui %[[p]] : i32 to i64 |
| // CHECK-VEC3: %[[q:.*]] = arith.index_cast %[[a]] : i64 to index |
| // CHECK-VEC3: %[[r:.*]] = memref.load %{{.*}}[%[[c1]]] : memref<?xi32> |
| // CHECK-VEC3: %[[b:.*]] = arith.extui %[[r]] : i32 to i64 |
| // CHECK-VEC3: %[[s:.*]] = arith.index_cast %[[b]] : i64 to index |
| // CHECK-VEC3: scf.for %[[i:.*]] = %[[q]] to %[[s]] step %[[c16]] { |
| // CHECK-VEC3: %[[sub:.*]] = affine.min #[[$map]](%[[s]], %[[i]])[%[[c16]]] |
| // CHECK-VEC3: %[[mask:.*]] = vector.create_mask %[[sub]] : vector<16xi1> |
| // CHECK-VEC3: %[[li:.*]] = vector.maskedload %{{.*}}[%[[i]]], %[[mask]], %{{.*}} : memref<?xi32>, vector<16xi1>, vector<16xi32> into vector<16xi32> |
| // CHECK-VEC3: %[[la:.*]] = vector.maskedload %{{.*}}[%[[i]]], %[[mask]], %{{.*}} : memref<?xf32>, vector<16xi1>, vector<16xf32> into vector<16xf32> |
| // CHECK-VEC3: %[[lb:.*]] = vector.gather %{{.*}}[%[[c0]]] [%[[li]]], %[[mask]], %{{.*}} : memref<1024xf32>, vector<16xi32>, vector<16xi1>, vector<16xf32> into vector<16xf32> |
| // CHECK-VEC3: %[[m:.*]] = arith.mulf %[[la]], %[[lb]] : vector<16xf32> |
| // CHECK-VEC3: vector.scatter %{{.*}}[%[[c0]]] [%[[li]]], %[[mask]], %[[m]] : memref<1024xf32>, vector<16xi32>, vector<16xi1>, vector<16xf32> |
| // CHECK-VEC3: } |
| // CHECK-VEC3: return |
| // |
| func @mul_s(%arga: tensor<1024xf32, #SparseVector>, %argb: tensor<1024xf32>, %argx: tensor<1024xf32>) -> tensor<1024xf32> { |
| %0 = linalg.generic #trait_mul_s |
| ins(%arga, %argb: tensor<1024xf32, #SparseVector>, tensor<1024xf32>) |
| outs(%argx: tensor<1024xf32>) { |
| ^bb(%a: f32, %b: f32, %x: f32): |
| %0 = arith.mulf %a, %b : f32 |
| linalg.yield %0 : f32 |
| } -> tensor<1024xf32> |
| return %0 : tensor<1024xf32> |
| } |
| |
| // ----- |
| |
| #DenseVector = #sparse_tensor.encoding<{ dimLevelType = [ "dense" ] }> |
| |
| #trait_reduction_d = { |
| indexing_maps = [ |
| affine_map<(i) -> (i)>, // a |
| affine_map<(i) -> (i)>, // b |
| affine_map<(i) -> ()> // x (out) |
| ], |
| iterator_types = ["reduction"], |
| doc = "x += a(i) * b(i)" |
| } |
| |
| // |
| // CHECK-VEC0-LABEL: func @reduction_d |
| // CHECK-VEC0-DAG: %[[c0:.*]] = arith.constant 0 : index |
| // CHECK-VEC0-DAG: %[[c1:.*]] = arith.constant 1 : index |
| // CHECK-VEC0-DAG: %[[c1024:.*]] = arith.constant 1024 : index |
| // CHECK-VEC0: %[[red:.*]] = scf.for %[[i:.*]] = %[[c0]] to %[[c1024]] step %[[c1]] iter_args(%[[red_in:.*]] = %{{.*}}) -> (f32) { |
| // CHECK-VEC0: %[[la:.*]] = memref.load %{{.*}}[%[[i]]] : memref<?xf32> |
| // CHECK-VEC0: %[[lb:.*]] = memref.load %{{.*}}[%[[i]]] : memref<1024xf32> |
| // CHECK-VEC0: %[[m:.*]] = arith.mulf %[[la]], %[[lb]] : f32 |
| // CHECK-VEC0: %[[a:.*]] = arith.addf %[[red_in]], %[[m]] : f32 |
| // CHECK-VEC0: scf.yield %[[a]] : f32 |
| // CHECK-VEC0: } |
| // CHECK-VEC0: return |
| // |
| // CHECK-VEC1-LABEL: func @reduction_d |
| // CHECK-VEC1-DAG: %[[c0:.*]] = arith.constant 0 : index |
| // CHECK-VEC1-DAG: %[[c16:.*]] = arith.constant 16 : index |
| // CHECK-VEC1-DAG: %[[c1024:.*]] = arith.constant 1024 : index |
| // CHECK-VEC1-DAG: %[[v0:.*]] = arith.constant dense<0.000000e+00> : vector<16xf32> |
| // CHECK-VEC1: %[[l:.*]] = memref.load %{{.*}}[] : memref<f32> |
| // CHECK-VEC1: %[[r:.*]] = vector.insertelement %[[l]], %[[v0]][%[[c0]] : index] : vector<16xf32> |
| // CHECK-VEC1: %[[red:.*]] = scf.for %[[i:.*]] = %[[c0]] to %[[c1024]] step %[[c16]] iter_args(%[[red_in:.*]] = %[[r]]) -> (vector<16xf32>) { |
| // CHECK-VEC1: %[[la:.*]] = vector.load %{{.*}}[%[[i]]] : memref<?xf32>, vector<16xf32> |
| // CHECK-VEC1: %[[lb:.*]] = vector.load %{{.*}}[%[[i]]] : memref<1024xf32>, vector<16xf32> |
| // CHECK-VEC1: %[[m:.*]] = arith.mulf %[[la]], %[[lb]] : vector<16xf32> |
| // CHECK-VEC1: %[[a:.*]] = arith.addf %[[red_in]], %[[m]] : vector<16xf32> |
| // CHECK-VEC1: scf.yield %[[a]] : vector<16xf32> |
| // CHECK-VEC1: } |
| // CHECK-VEC1: %{{.*}} = vector.reduction "add", %[[red]] : vector<16xf32> into f32 |
| // CHECK-VEC1: return |
| // |
| // CHECK-VEC2-LABEL: func @reduction_d |
| // CHECK-VEC2-DAG: %[[c0:.*]] = arith.constant 0 : index |
| // CHECK-VEC2-DAG: %[[c16:.*]] = arith.constant 16 : index |
| // CHECK-VEC2-DAG: %[[c1024:.*]] = arith.constant 1024 : index |
| // CHECK-VEC2-DAG: %[[v0:.*]] = arith.constant dense<0.000000e+00> : vector<16xf32> |
| // CHECK-VEC2: %[[l:.*]] = memref.load %{{.*}}[] : memref<f32> |
| // CHECK-VEC2: %[[r:.*]] = vector.insertelement %[[l]], %[[v0]][%[[c0]] : index] : vector<16xf32> |
| // CHECK-VEC2: %[[red:.*]] = scf.for %[[i:.*]] = %[[c0]] to %[[c1024]] step %[[c16]] iter_args(%[[red_in:.*]] = %[[r]]) -> (vector<16xf32>) { |
| // CHECK-VEC2: %[[la:.*]] = vector.load %{{.*}}[%[[i]]] : memref<?xf32>, vector<16xf32> |
| // CHECK-VEC2: %[[lb:.*]] = vector.load %{{.*}}[%[[i]]] : memref<1024xf32>, vector<16xf32> |
| // CHECK-VEC2: %[[m:.*]] = arith.mulf %[[la]], %[[lb]] : vector<16xf32> |
| // CHECK-VEC2: %[[a:.*]] = arith.addf %[[red_in]], %[[m]] : vector<16xf32> |
| // CHECK-VEC2: scf.yield %[[a]] : vector<16xf32> |
| // CHECK-VEC2: } |
| // CHECK-VEC2: %{{.*}} = vector.reduction "add", %[[red]] : vector<16xf32> into f32 |
| // CHECK-VEC2: return |
| // |
| func @reduction_d(%arga: tensor<1024xf32, #DenseVector>, %argb: tensor<1024xf32>, %argx: tensor<f32>) -> tensor<f32> { |
| %0 = linalg.generic #trait_reduction_d |
| ins(%arga, %argb: tensor<1024xf32, #DenseVector>, tensor<1024xf32>) |
| outs(%argx: tensor<f32>) { |
| ^bb(%a: f32, %b: f32, %x: f32): |
| %0 = arith.mulf %a, %b : f32 |
| %1 = arith.addf %x, %0 : f32 |
| linalg.yield %1 : f32 |
| } -> tensor<f32> |
| return %0 : tensor<f32> |
| } |
| |
| // ----- |
| |
| #SparseMatrix = #sparse_tensor.encoding<{ |
| dimLevelType = [ "dense", "compressed" ], |
| pointerBitWidth = 32, |
| indexBitWidth = 32 |
| }> |
| |
| #trait_mul_ds = { |
| indexing_maps = [ |
| affine_map<(i,j) -> (i,j)>, // A |
| affine_map<(i,j) -> (i,j)>, // B |
| affine_map<(i,j) -> (i,j)> // X (out) |
| ], |
| iterator_types = ["parallel", "parallel"], |
| doc = "X(i,j) = A(i,j) * B(i,j)" |
| } |
| |
| // |
| // CHECK-VEC0-LABEL: func @mul_ds |
| // CHECK-VEC0-DAG: %[[c0:.*]] = arith.constant 0 : index |
| // CHECK-VEC0-DAG: %[[c1:.*]] = arith.constant 1 : index |
| // CHECK-VEC0-DAG: %[[c512:.*]] = arith.constant 512 : index |
| // CHECK-VEC0: scf.for %[[i:.*]] = %[[c0]] to %[[c512]] step %[[c1]] { |
| // CHECK-VEC0: %[[p:.*]] = memref.load %{{.*}}[%[[i]]] : memref<?xi32> |
| // CHECK-VEC0: %[[a:.*]] = arith.extui %[[p]] : i32 to i64 |
| // CHECK-VEC0: %[[q:.*]] = arith.index_cast %[[a]] : i64 to index |
| // CHECK-VEC0: %[[a:.*]] = arith.addi %[[i]], %[[c1]] : index |
| // CHECK-VEC0: %[[r:.*]] = memref.load %{{.*}}[%[[a]]] : memref<?xi32> |
| // CHECK-VEC0: %[[b:.*]] = arith.extui %[[r]] : i32 to i64 |
| // CHECK-VEC0: %[[s:.*]] = arith.index_cast %[[b]] : i64 to index |
| // CHECK-VEC0: scf.for %[[j:.*]] = %[[q]] to %[[s]] step %[[c1]] { |
| // CHECK-VEC0: %[[lj:.*]] = memref.load %{{.*}}[%[[j]]] : memref<?xi32> |
| // CHECK-VEC0: %[[zj:.*]] = arith.extui %[[lj]] : i32 to i64 |
| // CHECK-VEC0: %[[cj:.*]] = arith.index_cast %[[zj]] : i64 to index |
| // CHECK-VEC0: %[[la:.*]] = memref.load %{{.*}}[%[[j]]] : memref<?xf32> |
| // CHECK-VEC0: %[[lb:.*]] = memref.load %{{.*}}[%[[i]], %[[cj]]] : memref<512x1024xf32> |
| // CHECK-VEC0: %[[m:.*]] = arith.mulf %[[la]], %[[lb]] : f32 |
| // CHECK-VEC0: store %[[m]], %{{.*}}[%[[i]], %[[cj]]] : memref<512x1024xf32> |
| // CHECK-VEC0: } |
| // CHECK-VEC0: } |
| // CHECK-VEC0: return |
| // |
| // CHECK-VEC1-LABEL: func @mul_ds |
| // CHECK-VEC1-DAG: %[[c0:.*]] = arith.constant 0 : index |
| // CHECK-VEC1-DAG: %[[c1:.*]] = arith.constant 1 : index |
| // CHECK-VEC1-DAG: %[[c512:.*]] = arith.constant 512 : index |
| // CHECK-VEC1: scf.for %[[i:.*]] = %[[c0]] to %[[c512]] step %[[c1]] { |
| // CHECK-VEC1: %[[p:.*]] = memref.load %{{.*}}[%[[i]]] : memref<?xi32> |
| // CHECK-VEC1: %[[a:.*]] = arith.extui %[[p]] : i32 to i64 |
| // CHECK-VEC1: %[[q:.*]] = arith.index_cast %[[a]] : i64 to index |
| // CHECK-VEC1: %[[a:.*]] = arith.addi %[[i]], %[[c1]] : index |
| // CHECK-VEC1: %[[r:.*]] = memref.load %{{.*}}[%[[a]]] : memref<?xi32> |
| // CHECK-VEC1: %[[b:.*]] = arith.extui %[[r]] : i32 to i64 |
| // CHECK-VEC1: %[[s:.*]] = arith.index_cast %[[b]] : i64 to index |
| // CHECK-VEC1: scf.for %[[j:.*]] = %[[q]] to %[[s]] step %[[c1]] { |
| // CHECK-VEC1: %[[lj:.*]] = memref.load %{{.*}}[%[[j]]] : memref<?xi32> |
| // CHECK-VEC1: %[[zj:.*]] = arith.extui %[[lj]] : i32 to i64 |
| // CHECK-VEC1: %[[cj:.*]] = arith.index_cast %[[zj]] : i64 to index |
| // CHECK-VEC1: %[[la:.*]] = memref.load %{{.*}}[%[[j]]] : memref<?xf32> |
| // CHECK-VEC1: %[[lb:.*]] = memref.load %{{.*}}[%[[i]], %[[cj]]] : memref<512x1024xf32> |
| // CHECK-VEC1: %[[m:.*]] = arith.mulf %[[la]], %[[lb]] : f32 |
| // CHECK-VEC1: store %[[m]], %{{.*}}[%[[i]], %[[cj]]] : memref<512x1024xf32> |
| // CHECK-VEC1: } |
| // CHECK-VEC1: } |
| // CHECK-VEC1: return |
| // |
| // CHECK-VEC2: #[[$map:.*]] = affine_map<(d0, d1)[s0] -> (16, d0 - d1) |
| // CHECK-VEC2-LABEL: func @mul_ds |
| // CHECK-VEC2-DAG: %[[c0:.*]] = arith.constant 0 : index |
| // CHECK-VEC2-DAG: %[[c1:.*]] = arith.constant 1 : index |
| // CHECK-VEC2-DAG: %[[c16:.*]] = arith.constant 16 : index |
| // CHECK-VEC2-DAG: %[[c512:.*]] = arith.constant 512 : index |
| // CHECK-VEC2: scf.for %[[i:.*]] = %[[c0]] to %[[c512]] step %[[c1]] { |
| // CHECK-VEC2: %[[p:.*]] = memref.load %{{.*}}[%[[i]]] : memref<?xi32> |
| // CHECK-VEC2: %[[a:.*]] = arith.extui %[[p]] : i32 to i64 |
| // CHECK-VEC2: %[[q:.*]] = arith.index_cast %[[a]] : i64 to index |
| // CHECK-VEC2: %[[a:.*]] = arith.addi %[[i]], %[[c1]] : index |
| // CHECK-VEC2: %[[r:.*]] = memref.load %{{.*}}[%[[a]]] : memref<?xi32> |
| // CHECK-VEC2: %[[b:.*]] = arith.extui %[[r]] : i32 to i64 |
| // CHECK-VEC2: %[[s:.*]] = arith.index_cast %[[b]] : i64 to index |
| // CHECK-VEC2: scf.for %[[j:.*]] = %[[q]] to %[[s]] step %[[c16]] { |
| // CHECK-VEC2: %[[sub:.*]] = affine.min #[[$map]](%[[s]], %[[j]])[%[[c16]]] |
| // CHECK-VEC2: %[[mask:.*]] = vector.create_mask %[[sub]] : vector<16xi1> |
| // CHECK-VEC2: %[[lj:.*]] = vector.maskedload %{{.*}}[%[[j]]], %[[mask]], %{{.*}} : memref<?xi32>, vector<16xi1>, vector<16xi32> into vector<16xi32> |
| // CHECK-VEC2: %[[zj:.*]] = arith.extui %[[lj]] : vector<16xi32> to vector<16xi64> |
| // CHECK-VEC2: %[[la:.*]] = vector.maskedload %{{.*}}[%[[j]]], %[[mask]], %{{.*}} : memref<?xf32>, vector<16xi1>, vector<16xf32> into vector<16xf32> |
| // CHECK-VEC2: %[[lb:.*]] = vector.gather %{{.*}}[%[[i]], %[[c0]]] [%[[zj]]], %[[mask]], %{{.*}} : memref<512x1024xf32>, vector<16xi64>, vector<16xi1>, vector<16xf32> into vector<16xf32> |
| // CHECK-VEC2: %[[m:.*]] = arith.mulf %[[la]], %[[lb]] : vector<16xf32> |
| // CHECK-VEC2: vector.scatter %{{.*}}[%[[i]], %[[c0]]] [%[[zj]]], %[[mask]], %[[m]] : memref<512x1024xf32>, vector<16xi64>, vector<16xi1>, vector<16xf32> |
| // CHECK-VEC2: } |
| // CHECK-VEC2: } |
| // CHECK-VEC2: return |
| // |
| // CHECK-VEC3: #[[$map:.*]] = affine_map<(d0, d1)[s0] -> (16, d0 - d1) |
| // CHECK-VEC3-LABEL: func @mul_ds |
| // CHECK-VEC3-DAG: %[[c0:.*]] = arith.constant 0 : index |
| // CHECK-VEC3-DAG: %[[c1:.*]] = arith.constant 1 : index |
| // CHECK-VEC3-DAG: %[[c16:.*]] = arith.constant 16 : index |
| // CHECK-VEC3-DAG: %[[c512:.*]] = arith.constant 512 : index |
| // CHECK-VEC3: scf.for %[[i:.*]] = %[[c0]] to %[[c512]] step %[[c1]] { |
| // CHECK-VEC3: %[[p:.*]] = memref.load %{{.*}}[%[[i]]] : memref<?xi32> |
| // CHECK-VEC3: %[[a:.*]] = arith.extui %[[p]] : i32 to i64 |
| // CHECK-VEC3: %[[q:.*]] = arith.index_cast %[[a]] : i64 to index |
| // CHECK-VEC3: %[[a:.*]] = arith.addi %[[i]], %[[c1]] : index |
| // CHECK-VEC3: %[[r:.*]] = memref.load %{{.*}}[%[[a]]] : memref<?xi32> |
| // CHECK-VEC3: %[[b:.*]] = arith.extui %[[r]] : i32 to i64 |
| // CHECK-VEC3: %[[s:.*]] = arith.index_cast %[[b]] : i64 to index |
| // CHECK-VEC3: scf.for %[[j:.*]] = %[[q]] to %[[s]] step %[[c16]] { |
| // CHECK-VEC3: %[[sub:.*]] = affine.min #[[$map]](%[[s]], %[[j]])[%[[c16]]] |
| // CHECK-VEC3: %[[mask:.*]] = vector.create_mask %[[sub]] : vector<16xi1> |
| // CHECK-VEC3: %[[lj:.*]] = vector.maskedload %{{.*}}[%[[j]]], %[[mask]], %{{.*}} : memref<?xi32>, vector<16xi1>, vector<16xi32> into vector<16xi32> |
| // CHECK-VEC3: %[[la:.*]] = vector.maskedload %{{.*}}[%[[j]]], %[[mask]], %{{.*}} : memref<?xf32>, vector<16xi1>, vector<16xf32> into vector<16xf32> |
| // CHECK-VEC3: %[[lb:.*]] = vector.gather %{{.*}}[%[[i]], %[[c0]]] [%[[lj]]], %[[mask]], %{{.*}} : memref<512x1024xf32>, vector<16xi32>, vector<16xi1>, vector<16xf32> into vector<16xf32> |
| // CHECK-VEC3: %[[m:.*]] = arith.mulf %[[la]], %[[lb]] : vector<16xf32> |
| // CHECK-VEC3: vector.scatter %{{.*}}[%[[i]], %[[c0]]] [%[[lj]]], %[[mask]], %[[m]] : memref<512x1024xf32>, vector<16xi32>, vector<16xi1>, vector<16xf32> |
| // CHECK-VEC3: } |
| // CHECK-VEC3: } |
| // CHECK-VEC3: return |
| // |
| func @mul_ds(%arga: tensor<512x1024xf32, #SparseMatrix>, %argb: tensor<512x1024xf32>, %argx: tensor<512x1024xf32>) -> tensor<512x1024xf32> { |
| %0 = linalg.generic #trait_mul_ds |
| ins(%arga, %argb: tensor<512x1024xf32, #SparseMatrix>, tensor<512x1024xf32>) |
| outs(%argx: tensor<512x1024xf32>) { |
| ^bb(%a: f32, %b: f32, %x: f32): |
| %0 = arith.mulf %a, %b : f32 |
| linalg.yield %0 : f32 |
| } -> tensor<512x1024xf32> |
| return %0 : tensor<512x1024xf32> |
| } |
| |
| // ----- |
| |
| #SparseMatrix = #sparse_tensor.encoding<{dimLevelType = ["dense","compressed"]}> |
| |
| #trait_affine = { |
| indexing_maps = [ |
| affine_map<(i,j) -> (i,j)>, |
| affine_map<(i,j) -> (i+1,j)> |
| ], |
| iterator_types = ["parallel","parallel"], |
| doc = "X(i+1,j) += A(i,j)" |
| } |
| |
| // |
| // CHECK-VEC0-LABEL: func @add_dense |
| // CHECK-VEC0-DAG: %[[c0:.*]] = arith.constant 0 : index |
| // CHECK-VEC0-DAG: %[[c1:.*]] = arith.constant 1 : index |
| // CHECK-VEC0-DAG: %[[c32:.*]] = arith.constant 32 : index |
| // CHECK-VEC0: scf.for %[[i:.*]] = %[[c0]] to %[[c32]] step %[[c1]] { |
| // CHECK-VEC0: %[[lo:.*]] = memref.load %{{.*}}[%[[i]]] : memref<?xindex> |
| // CHECK-VEC0: %[[i1:.*]] = arith.addi %[[i]], %[[c1]] : index |
| // CHECK-VEC0: %[[hi:.*]] = memref.load %{{.*}}[%[[i1]]] : memref<?xindex> |
| // CHECK-VEC0: scf.for %[[jj:.*]] = %[[lo]] to %[[hi]] step %[[c1]] { |
| // CHECK-VEC0: %[[j:.*]] = memref.load %{{.*}}[%[[jj]]] : memref<?xindex> |
| // CHECK-VEC0: %[[x:.*]] = memref.load %{{.*}}[%[[i1]], %[[j]]] : memref<33x64xf64> |
| // CHECK-VEC0: %[[a:.*]] = memref.load %{{.*}}[%[[jj]]] : memref<?xf64> |
| // CHECK-VEC0: %[[s:.*]] = arith.addf %[[x]], %[[a]] : f64 |
| // CHECK-VEC0: memref.store %[[s]], %{{.*}}[%[[i1]], %[[j]]] : memref<33x64xf64> |
| // CHECK-VEC0: } |
| // CHECK-VEC0: } |
| // CHECK-VEC0: return |
| // |
| // CHECK-VEC1-LABEL: func @add_dense |
| // CHECK-VEC1-DAG: %[[c0:.*]] = arith.constant 0 : index |
| // CHECK-VEC1-DAG: %[[c1:.*]] = arith.constant 1 : index |
| // CHECK-VEC1-DAG: %[[c32:.*]] = arith.constant 32 : index |
| // CHECK-VEC1: scf.for %[[i:.*]] = %[[c0]] to %[[c32]] step %[[c1]] { |
| // CHECK-VEC1: %[[lo:.*]] = memref.load %{{.*}}[%[[i]]] : memref<?xindex> |
| // CHECK-VEC1: %[[i1:.*]] = arith.addi %[[i]], %[[c1]] : index |
| // CHECK-VEC1: %[[hi:.*]] = memref.load %{{.*}}[%[[i1]]] : memref<?xindex> |
| // CHECK-VEC1: scf.for %[[jj:.*]] = %[[lo]] to %[[hi]] step %[[c1]] { |
| // CHECK-VEC1: %[[j:.*]] = memref.load %{{.*}}[%[[jj]]] : memref<?xindex> |
| // CHECK-VEC1: %[[x:.*]] = memref.load %{{.*}}[%[[i1]], %[[j]]] : memref<33x64xf64> |
| // CHECK-VEC1: %[[a:.*]] = memref.load %{{.*}}[%[[jj]]] : memref<?xf64> |
| // CHECK-VEC1: %[[s:.*]] = arith.addf %[[x]], %[[a]] : f64 |
| // CHECK-VEC1: memref.store %[[s]], %{{.*}}[%[[i1]], %[[j]]] : memref<33x64xf64> |
| // CHECK-VEC1: } |
| // CHECK-VEC1: } |
| // CHECK-VEC1: return |
| // |
| // CHECK-VEC2: #[[$map:.*]] = affine_map<(d0, d1)[s0] -> (16, d0 - d1) |
| // CHECK-VEC2-LABEL: func @add_dense |
| // CHECK-VEC2-DAG: %[[c0:.*]] = arith.constant 0 : index |
| // CHECK-VEC2-DAG: %[[c1:.*]] = arith.constant 1 : index |
| // CHECK-VEC2-DAG: %[[c16:.*]] = arith.constant 16 : index |
| // CHECK-VEC2-DAG: %[[c32:.*]] = arith.constant 32 : index |
| // CHECK-VEC2: scf.for %[[i:.*]] = %[[c0]] to %[[c32]] step %[[c1]] { |
| // CHECK-VEC2: %[[lo:.*]] = memref.load %{{.*}}[%[[i]]] : memref<?xindex> |
| // CHECK-VEC2: %[[i1:.*]] = arith.addi %[[i]], %[[c1]] : index |
| // CHECK-VEC2: %[[hi:.*]] = memref.load %{{.*}}[%[[i1]]] : memref<?xindex> |
| // CHECK-VEC2: scf.for %[[jj:.*]] = %[[lo]] to %[[hi]] step %[[c16]] { |
| // CHECK-VEC2: %[[sub:.*]] = affine.min #[[$map]](%[[hi]], %[[jj]])[%[[c16]]] |
| // CHECK-VEC2: %[[mask:.*]] = vector.create_mask %[[sub]] : vector<16xi1> |
| // CHECK-VEC2: %[[j:.*]] = vector.maskedload %{{.*}}[%[[jj]]], %[[mask]], %{{.*}} : memref<?xindex> |
| // CHECK-VEC2: %[[x:.*]] = vector.gather %{{.*}}[%[[i1]], %[[c0]]] [%[[j]]], %[[mask]], %{{.*}} : memref<33x64xf64> |
| // CHECK-VEC2: %[[a:.*]] = vector.maskedload %{{.*}}[%[[jj]]], %[[mask]], %{{.*}} : memref<?xf64> |
| // CHECK-VEC2: %[[s:.*]] = arith.addf %[[x]], %[[a]] : vector<16xf64> |
| // CHECK-VEC2: vector.scatter %{{.*}}[%[[i1]], %[[c0]]] [%[[j]]], %[[mask]], %[[s]] : memref<33x64xf64> |
| // CHECK-VEC2: } |
| // CHECK-VEC2: } |
| // CHECK-VEC2: return |
| // |
| func @add_dense(%arga: tensor<32x64xf64, #SparseMatrix>, |
| %argx: tensor<33x64xf64> {linalg.inplaceable = true}) -> tensor<33x64xf64> { |
| %0 = linalg.generic #trait_affine |
| ins(%arga: tensor<32x64xf64, #SparseMatrix>) |
| outs(%argx: tensor<33x64xf64>) { |
| ^bb(%a: f64, %x: f64): |
| %0 = arith.addf %x, %a : f64 |
| linalg.yield %0 : f64 |
| } -> tensor<33x64xf64> |
| return %0 : tensor<33x64xf64> |
| } |
