1// RUN: mlir-opt %s --sparse-reinterpret-map -sparsification | FileCheck %s --check-prefix=CHECK-HIR 2// 3// RUN: mlir-opt %s --sparse-reinterpret-map -sparsification --sparse-tensor-conversion --cse | \ 4// RUN: FileCheck %s --check-prefix=CHECK-MIR 5// 6// RUN: mlir-opt %s --sparse-reinterpret-map -sparsification --sparse-tensor-conversion --cse \ 7// RUN: --one-shot-bufferize="copy-before-write bufferize-function-boundaries function-boundary-type-conversion=identity-layout-map" | \ 8// RUN: FileCheck %s --check-prefix=CHECK-LIR 9 10#CSR = #sparse_tensor.encoding<{map = (d0, d1) -> (d0 : dense, d1 : compressed)}> 11 12#trait_matvec = { 13 indexing_maps = [ 14 affine_map<(i,j) -> (i,j)>, // A 15 affine_map<(i,j) -> (j)>, // b 16 affine_map<(i,j) -> (i)> // x (out) 17 ], 18 iterator_types = ["parallel","reduction"], 19 doc = "x(i) += A(i,j) * b(j)" 20} 21 22// CHECK-HIR-LABEL: func @matvec( 23// CHECK-HIR-SAME: %[[VAL_0:.*]]: tensor<32x64xf64, #sparse{{[0-9]*}}> 24// CHECK-HIR-SAME: %[[VAL_1:.*]]: tensor<64xf64>, 25// CHECK-HIR-SAME: %[[VAL_2:.*]]: tensor<32xf64>) -> tensor<32xf64> { 26// CHECK-HIR-DAG: %[[VAL_3:.*]] = arith.constant 32 : index 27// CHECK-HIR-DAG: %[[VAL_4:.*]] = arith.constant 0 : index 28// CHECK-HIR-DAG: %[[VAL_5:.*]] = arith.constant 1 : index 29// CHECK-HIR-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x64xf64, #sparse{{[0-9]*}}> 30// CHECK-HIR-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x64xf64, #sparse{{[0-9]*}}> 31// CHECK-HIR-DAG: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x64xf64, #sparse{{[0-9]*}}> 32// CHECK-HIR-DAG: %[[VAL_9:.*]] = bufferization.to_memref %[[VAL_1]] : tensor<64xf64> to memref<64xf64> 33// CHECK-HIR-DAG: %[[VAL_11:.*]] = bufferization.to_memref %[[VAL_2]] : tensor<32xf64> to memref<32xf64> 34// CHECK-HIR: scf.for %[[VAL_12:.*]] = %[[VAL_4]] to %[[VAL_3]] step %[[VAL_5]] { 35// CHECK-HIR-DAG: %[[VAL_13:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_12]]] : memref<?xindex> 36// CHECK-HIR-DAG: %[[VAL_14:.*]] = arith.addi %[[VAL_12]], %[[VAL_5]] : index 37// CHECK-HIR-DAG: %[[VAL_15:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_14]]] : memref<?xindex> 38// CHECK-HIR-DAG: %[[VAL_16:.*]] = memref.load %[[VAL_11]]{{\[}}%[[VAL_12]]] : memref<32xf64> 39// CHECK-HIR: %[[VAL_17:.*]] = scf.for %[[VAL_18:.*]] = %[[VAL_13]] to %[[VAL_15]] step %[[VAL_5]] iter_args(%[[VAL_19:.*]] = %[[VAL_16]]) -> (f64) { 40// CHECK-HIR: %[[VAL_20:.*]] = memref.load %[[VAL_7]]{{\[}}%[[VAL_18]]] : memref<?xindex> 41// CHECK-HIR: %[[VAL_21:.*]] = memref.load %[[VAL_8]]{{\[}}%[[VAL_18]]] : memref<?xf64> 42// CHECK-HIR: %[[VAL_22:.*]] = memref.load %[[VAL_9]]{{\[}}%[[VAL_20]]] : memref<64xf64> 43// CHECK-HIR: %[[VAL_23:.*]] = arith.mulf %[[VAL_21]], %[[VAL_22]] : f64 44// CHECK-HIR: %[[VAL_24:.*]] = arith.addf %[[VAL_19]], %[[VAL_23]] : f64 45// CHECK-HIR: scf.yield %[[VAL_24]] : f64 46// CHECK-HIR: } 47// CHECK-HIR: memref.store %[[VAL_17]], %[[VAL_11]]{{\[}}%[[VAL_12]]] : memref<32xf64> 48// CHECK-HIR: } 49// CHECK-HIR: %[[VAL_26:.*]] = bufferization.to_tensor %[[VAL_11]] : memref<32xf64> 50// CHECK-HIR: return %[[VAL_26]] : tensor<32xf64> 51// CHECK-HIR: } 52 53// CHECK-MIR-LABEL: func @matvec( 54// CHECK-MIR-SAME: %[[VAL_0:.*]]: !llvm.ptr, 55// CHECK-MIR-SAME: %[[VAL_1:.*]]: tensor<64xf64>, 56// CHECK-MIR-SAME: %[[VAL_2:.*]]: tensor<32xf64>) -> tensor<32xf64> { 57// CHECK-MIR-DAG: %[[VAL_3:.*]] = arith.constant 32 : index 58// CHECK-MIR-DAG: %[[VAL_4:.*]] = arith.constant 0 : index 59// CHECK-MIR-DAG: %[[VAL_5:.*]] = arith.constant 1 : index 60// CHECK-MIR-DAG: %[[VAL_6:.*]] = call @sparsePositions0(%[[VAL_0]], %[[VAL_5]]) : (!llvm.ptr, index) -> memref<?xindex> 61// CHECK-MIR-DAG: %[[VAL_7:.*]] = call @sparseCoordinates0(%[[VAL_0]], %[[VAL_5]]) : (!llvm.ptr, index) -> memref<?xindex> 62// CHECK-MIR-DAG: %[[VAL_8:.*]] = call @sparseValuesF64(%[[VAL_0]]) : (!llvm.ptr) -> memref<?xf64> 63// CHECK-MIR-DAG: %[[VAL_9:.*]] = bufferization.to_memref %[[VAL_1]] : tensor<64xf64> to memref<64xf64> 64// CHECK-MIR-DAG: %[[VAL_11:.*]] = bufferization.to_memref %[[VAL_2]] : tensor<32xf64> to memref<32xf64> 65// CHECK-MIR: scf.for %[[VAL_14:.*]] = %[[VAL_4]] to %[[VAL_3]] step %[[VAL_5]] { 66// CHECK-MIR-DAG: %[[VAL_15:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_14]]] : memref<?xindex> 67// CHECK-MIR-DAG: %[[VAL_16:.*]] = arith.addi %[[VAL_14]], %[[VAL_5]] : index 68// CHECK-MIR-DAG: %[[VAL_17:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_16]]] : memref<?xindex> 69// CHECK-MIR-DAG: %[[VAL_18:.*]] = memref.load %[[VAL_11]]{{\[}}%[[VAL_14]]] : memref<32xf64> 70// CHECK-MIR: %[[VAL_19:.*]] = scf.for %[[VAL_20:.*]] = %[[VAL_15]] to %[[VAL_17]] step %[[VAL_5]] iter_args(%[[VAL_21:.*]] = %[[VAL_18]]) -> (f64) { 71// CHECK-MIR: %[[VAL_22:.*]] = memref.load %[[VAL_7]]{{\[}}%[[VAL_20]]] : memref<?xindex> 72// CHECK-MIR: %[[VAL_23:.*]] = memref.load %[[VAL_8]]{{\[}}%[[VAL_20]]] : memref<?xf64> 73// CHECK-MIR: %[[VAL_24:.*]] = memref.load %[[VAL_9]]{{\[}}%[[VAL_22]]] : memref<64xf64> 74// CHECK-MIR: %[[VAL_25:.*]] = arith.mulf %[[VAL_23]], %[[VAL_24]] : f64 75// CHECK-MIR: %[[VAL_26:.*]] = arith.addf %[[VAL_21]], %[[VAL_25]] : f64 76// CHECK-MIR: scf.yield %[[VAL_26]] : f64 77// CHECK-MIR: } 78// CHECK-MIR: memref.store %[[VAL_19]], %[[VAL_11]]{{\[}}%[[VAL_14]]] : memref<32xf64> 79// CHECK-MIR: } 80// CHECK-MIR: %[[VAL_28:.*]] = bufferization.to_tensor %[[VAL_11]] : memref<32xf64> 81// CHECK-MIR: return %[[VAL_28]] : tensor<32xf64> 82// CHECK-MIR: } 83 84// CHECK-LIR-LABEL: func @matvec( 85// CHECK-LIR-SAME: %[[VAL_0:.*]]: !llvm.ptr, 86// CHECK-LIR-SAME: %[[VAL_1:.*]]: memref<64xf64>, 87// CHECK-LIR-SAME: %[[VAL_2:.*]]: memref<32xf64>) -> memref<32xf64> { 88// CHECK-LIR-DAG: %[[VAL_3:.*]] = arith.constant 32 : index 89// CHECK-LIR-DAG: %[[VAL_4:.*]] = arith.constant 0 : index 90// CHECK-LIR-DAG: %[[VAL_5:.*]] = arith.constant 1 : index 91// CHECK-LIR-DAG: %[[VAL_6:.*]] = call @sparsePositions0(%[[VAL_0]], %[[VAL_5]]) : (!llvm.ptr, index) -> memref<?xindex> 92// CHECK-LIR-DAG: %[[VAL_7:.*]] = call @sparseCoordinates0(%[[VAL_0]], %[[VAL_5]]) : (!llvm.ptr, index) -> memref<?xindex> 93// CHECK-LIR-DAG: %[[VAL_8:.*]] = call @sparseValuesF64(%[[VAL_0]]) : (!llvm.ptr) -> memref<?xf64> 94// CHECK-LIR: scf.for %[[VAL_12:.*]] = %[[VAL_4]] to %[[VAL_3]] step %[[VAL_5]] { 95// CHECK-LIR-DAG: %[[VAL_13:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_12]]] : memref<?xindex> 96// CHECK-LIR-DAG: %[[VAL_14:.*]] = arith.addi %[[VAL_12]], %[[VAL_5]] : index 97// CHECK-LIR-DAG: %[[VAL_15:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_14]]] : memref<?xindex> 98// CHECK-LIR-DAG: %[[VAL_16:.*]] = memref.load %[[VAL_2]]{{\[}}%[[VAL_12]]] : memref<32xf64> 99// CHECK-LIR: %[[VAL_17:.*]] = scf.for %[[VAL_18:.*]] = %[[VAL_13]] to %[[VAL_15]] step %[[VAL_5]] iter_args(%[[VAL_19:.*]] = %[[VAL_16]]) -> (f64) { 100// CHECK-LIR: %[[VAL_20:.*]] = memref.load %[[VAL_7]]{{\[}}%[[VAL_18]]] : memref<?xindex> 101// CHECK-LIR: %[[VAL_21:.*]] = memref.load %[[VAL_8]]{{\[}}%[[VAL_18]]] : memref<?xf64> 102// CHECK-LIR: %[[VAL_22:.*]] = memref.load %[[VAL_1]]{{\[}}%[[VAL_20]]] : memref<64xf64> 103// CHECK-LIR: %[[VAL_23:.*]] = arith.mulf %[[VAL_21]], %[[VAL_22]] : f64 104// CHECK-LIR: %[[VAL_24:.*]] = arith.addf %[[VAL_19]], %[[VAL_23]] : f64 105// CHECK-LIR: scf.yield %[[VAL_24]] : f64 106// CHECK-LIR: } 107// CHECK-LIR: memref.store %[[VAL_17]], %[[VAL_2]]{{\[}}%[[VAL_12]]] : memref<32xf64> 108// CHECK-LIR: } 109// CHECK-LIR: return %[[VAL_2]] : memref<32xf64> 110// CHECK-LIR: } 111 112func.func @matvec(%arga: tensor<32x64xf64, #CSR>, 113 %argb: tensor<64xf64>, 114 %argx: tensor<32xf64>) -> tensor<32xf64> { 115 %0 = linalg.generic #trait_matvec 116 ins(%arga, %argb : tensor<32x64xf64, #CSR>, tensor<64xf64>) 117 outs(%argx: tensor<32xf64>) { 118 ^bb(%A: f64, %b: f64, %x: f64): 119 %0 = arith.mulf %A, %b : f64 120 %1 = arith.addf %x, %0 : f64 121 linalg.yield %1 : f64 122 } -> tensor<32xf64> 123 return %0 : tensor<32xf64> 124} 125