1// RUN: mlir-opt %s -sparsification | FileCheck %s --check-prefix=CHECK-HIR 2// 3// RUN: mlir-opt %s -sparsification --sparse-tensor-conversion | \ 4// RUN: FileCheck %s --check-prefix=CHECK-MIR 5// 6// RUN: mlir-opt %s -sparsification --sparse-tensor-conversion \ 7// RUN: --func-bufferize --tensor-constant-bufferize \ 8// RUN: --tensor-bufferize --finalizing-bufferize | \ 9// RUN: FileCheck %s --check-prefix=CHECK-LIR 10 11#CSR = #sparse_tensor.encoding<{dimLevelType = [ "dense", "compressed" ]}> 12 13#trait_matvec = { 14 indexing_maps = [ 15 affine_map<(i,j) -> (i,j)>, // A 16 affine_map<(i,j) -> (j)>, // b 17 affine_map<(i,j) -> (i)> // x (out) 18 ], 19 iterator_types = ["parallel","reduction"], 20 doc = "x(i) += A(i,j) * b(j)" 21} 22 23// CHECK-HIR-LABEL: func @matvec( 24// CHECK-HIR-SAME: %[[VAL_0:.*]]: tensor<32x64xf64, #sparse_tensor.encoding<{ dimLevelType = [ "dense", "compressed" ], pointerBitWidth = 0, indexBitWidth = 0 }>>, 25// CHECK-HIR-SAME: %[[VAL_1:.*]]: tensor<64xf64>, 26// CHECK-HIR-SAME: %[[VAL_2:.*]]: tensor<32xf64> {linalg.inplaceable = true}) -> tensor<32xf64> { 27// CHECK-HIR-DAG: %[[VAL_3:.*]] = constant 32 : index 28// CHECK-HIR-DAG: %[[VAL_4:.*]] = constant 0 : index 29// CHECK-HIR-DAG: %[[VAL_5:.*]] = constant 1 : index 30// CHECK-HIR: %[[VAL_6:.*]] = sparse_tensor.pointers %[[VAL_0]], %[[VAL_5]] : tensor<32x64xf64, #sparse_tensor.encoding<{ dimLevelType = [ "dense", "compressed" ], pointerBitWidth = 0, indexBitWidth = 0 }>> to memref<?xindex> 31// CHECK-HIR: %[[VAL_7:.*]] = sparse_tensor.indices %[[VAL_0]], %[[VAL_5]] : tensor<32x64xf64, #sparse_tensor.encoding<{ dimLevelType = [ "dense", "compressed" ], pointerBitWidth = 0, indexBitWidth = 0 }>> to memref<?xindex> 32// CHECK-HIR: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x64xf64, #sparse_tensor.encoding<{ dimLevelType = [ "dense", "compressed" ], pointerBitWidth = 0, indexBitWidth = 0 }>> to memref<?xf64> 33// CHECK-HIR: %[[VAL_9:.*]] = memref.buffer_cast %[[VAL_1]] : memref<64xf64> 34// CHECK-HIR: %[[VAL_10:.*]] = memref.buffer_cast %[[VAL_2]] : memref<32xf64> 35// CHECK-HIR: scf.for %[[VAL_11:.*]] = %[[VAL_4]] to %[[VAL_3]] step %[[VAL_5]] { 36// CHECK-HIR: %[[VAL_12:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_11]]] : memref<?xindex> 37// CHECK-HIR: %[[VAL_13:.*]] = addi %[[VAL_11]], %[[VAL_5]] : index 38// CHECK-HIR: %[[VAL_14:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_13]]] : memref<?xindex> 39// CHECK-HIR: %[[VAL_15:.*]] = memref.load %[[VAL_10]]{{\[}}%[[VAL_11]]] : memref<32xf64> 40// CHECK-HIR: %[[VAL_16:.*]] = scf.for %[[VAL_17:.*]] = %[[VAL_12]] to %[[VAL_14]] step %[[VAL_5]] iter_args(%[[VAL_18:.*]] = %[[VAL_15]]) -> (f64) { 41// CHECK-HIR: %[[VAL_19:.*]] = memref.load %[[VAL_7]]{{\[}}%[[VAL_17]]] : memref<?xindex> 42// CHECK-HIR: %[[VAL_20:.*]] = memref.load %[[VAL_8]]{{\[}}%[[VAL_17]]] : memref<?xf64> 43// CHECK-HIR: %[[VAL_21:.*]] = memref.load %[[VAL_9]]{{\[}}%[[VAL_19]]] : memref<64xf64> 44// CHECK-HIR: %[[VAL_22:.*]] = mulf %[[VAL_20]], %[[VAL_21]] : f64 45// CHECK-HIR: %[[VAL_23:.*]] = addf %[[VAL_18]], %[[VAL_22]] : f64 46// CHECK-HIR: scf.yield %[[VAL_23]] : f64 47// CHECK-HIR: } 48// CHECK-HIR: memref.store %[[VAL_24:.*]], %[[VAL_10]]{{\[}}%[[VAL_11]]] : memref<32xf64> 49// CHECK-HIR: } 50// CHECK-HIR: %[[VAL_25:.*]] = memref.tensor_load %[[VAL_10]] : memref<32xf64> 51// CHECK-HIR: return %[[VAL_25]] : tensor<32xf64> 52// CHECK-HIR: } 53 54// CHECK-MIR-LABEL: func @matvec( 55// CHECK-MIR-SAME: %[[VAL_0:.*]]: !llvm.ptr<i8>, 56// CHECK-MIR-SAME: %[[VAL_1:.*]]: tensor<64xf64>, 57// CHECK-MIR-SAME: %[[VAL_2:.*]]: tensor<32xf64> {linalg.inplaceable = true}) -> tensor<32xf64> { 58// CHECK-MIR-DAG: %[[VAL_3:.*]] = constant 32 : index 59// CHECK-MIR-DAG: %[[VAL_4:.*]] = constant 0 : index 60// CHECK-MIR-DAG: %[[VAL_5:.*]] = constant 1 : index 61// CHECK-MIR: %[[VAL_6:.*]] = call @sparsePointers(%[[VAL_0]], %[[VAL_5]]) : (!llvm.ptr<i8>, index) -> memref<?xindex> 62// CHECK-MIR: %[[VAL_7:.*]] = call @sparseIndices(%[[VAL_0]], %[[VAL_5]]) : (!llvm.ptr<i8>, index) -> memref<?xindex> 63// CHECK-MIR: %[[VAL_8:.*]] = call @sparseValuesF64(%[[VAL_0]]) : (!llvm.ptr<i8>) -> memref<?xf64> 64// CHECK-MIR: %[[VAL_9:.*]] = memref.buffer_cast %[[VAL_1]] : memref<64xf64> 65// CHECK-MIR: %[[VAL_10:.*]] = memref.buffer_cast %[[VAL_2]] : memref<32xf64> 66// CHECK-MIR: scf.for %[[VAL_11:.*]] = %[[VAL_4]] to %[[VAL_3]] step %[[VAL_5]] { 67// CHECK-MIR: %[[VAL_12:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_11]]] : memref<?xindex> 68// CHECK-MIR: %[[VAL_13:.*]] = addi %[[VAL_11]], %[[VAL_5]] : index 69// CHECK-MIR: %[[VAL_14:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_13]]] : memref<?xindex> 70// CHECK-MIR: %[[VAL_15:.*]] = memref.load %[[VAL_10]]{{\[}}%[[VAL_11]]] : memref<32xf64> 71// CHECK-MIR: %[[VAL_16:.*]] = scf.for %[[VAL_17:.*]] = %[[VAL_12]] to %[[VAL_14]] step %[[VAL_5]] iter_args(%[[VAL_18:.*]] = %[[VAL_15]]) -> (f64) { 72// CHECK-MIR: %[[VAL_19:.*]] = memref.load %[[VAL_7]]{{\[}}%[[VAL_17]]] : memref<?xindex> 73// CHECK-MIR: %[[VAL_20:.*]] = memref.load %[[VAL_8]]{{\[}}%[[VAL_17]]] : memref<?xf64> 74// CHECK-MIR: %[[VAL_21:.*]] = memref.load %[[VAL_9]]{{\[}}%[[VAL_19]]] : memref<64xf64> 75// CHECK-MIR: %[[VAL_22:.*]] = mulf %[[VAL_20]], %[[VAL_21]] : f64 76// CHECK-MIR: %[[VAL_23:.*]] = addf %[[VAL_18]], %[[VAL_22]] : f64 77// CHECK-MIR: scf.yield %[[VAL_23]] : f64 78// CHECK-MIR: } 79// CHECK-MIR: memref.store %[[VAL_24:.*]], %[[VAL_10]]{{\[}}%[[VAL_11]]] : memref<32xf64> 80// CHECK-MIR: } 81// CHECK-MIR: %[[VAL_25:.*]] = memref.tensor_load %[[VAL_10]] : memref<32xf64> 82// CHECK-MIR: return %[[VAL_25]] : tensor<32xf64> 83// CHECK-MIR: } 84 85// CHECK-LIR-LABEL: func @matvec( 86// CHECK-LIR-SAME: %[[VAL_0:.*]]: !llvm.ptr<i8>, 87// CHECK-LIR-SAME: %[[VAL_1:.*]]: memref<64xf64>, 88// CHECK-LIR-SAME: %[[VAL_2:.*]]: memref<32xf64> {linalg.inplaceable = true}) -> memref<32xf64> { 89// CHECK-LIR-DAG: %[[VAL_3:.*]] = constant 32 : index 90// CHECK-LIR-DAG: %[[VAL_4:.*]] = constant 0 : index 91// CHECK-LIR-DAG: %[[VAL_5:.*]] = constant 1 : index 92// CHECK-LIR: %[[VAL_6:.*]] = call @sparsePointers(%[[VAL_0]], %[[VAL_5]]) : (!llvm.ptr<i8>, index) -> memref<?xindex> 93// CHECK-LIR: %[[VAL_7:.*]] = call @sparseIndices(%[[VAL_0]], %[[VAL_5]]) : (!llvm.ptr<i8>, index) -> memref<?xindex> 94// CHECK-LIR: %[[VAL_8:.*]] = call @sparseValuesF64(%[[VAL_0]]) : (!llvm.ptr<i8>) -> memref<?xf64> 95// CHECK-LIR: scf.for %[[VAL_9:.*]] = %[[VAL_4]] to %[[VAL_3]] step %[[VAL_5]] { 96// CHECK-LIR: %[[VAL_10:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_9]]] : memref<?xindex> 97// CHECK-LIR: %[[VAL_11:.*]] = addi %[[VAL_9]], %[[VAL_5]] : index 98// CHECK-LIR: %[[VAL_12:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_11]]] : memref<?xindex> 99// CHECK-LIR: %[[VAL_13:.*]] = memref.load %[[VAL_2]]{{\[}}%[[VAL_9]]] : memref<32xf64> 100// CHECK-LIR: %[[VAL_14:.*]] = scf.for %[[VAL_15:.*]] = %[[VAL_10]] to %[[VAL_12]] step %[[VAL_5]] iter_args(%[[VAL_16:.*]] = %[[VAL_13]]) -> (f64) { 101// CHECK-LIR: %[[VAL_17:.*]] = memref.load %[[VAL_7]]{{\[}}%[[VAL_15]]] : memref<?xindex> 102// CHECK-LIR: %[[VAL_18:.*]] = memref.load %[[VAL_8]]{{\[}}%[[VAL_15]]] : memref<?xf64> 103// CHECK-LIR: %[[VAL_19:.*]] = memref.load %[[VAL_1]]{{\[}}%[[VAL_17]]] : memref<64xf64> 104// CHECK-LIR: %[[VAL_20:.*]] = mulf %[[VAL_18]], %[[VAL_19]] : f64 105// CHECK-LIR: %[[VAL_21:.*]] = addf %[[VAL_16]], %[[VAL_20]] : f64 106// CHECK-LIR: scf.yield %[[VAL_21]] : f64 107// CHECK-LIR: } 108// CHECK-LIR: memref.store %[[VAL_22:.*]], %[[VAL_2]]{{\[}}%[[VAL_9]]] : memref<32xf64> 109// CHECK-LIR: } 110// CHECK-LIR: return %[[VAL_2]] : memref<32xf64> 111// CHECK-LIR: } 112 113func @matvec(%arga: tensor<32x64xf64, #CSR>, 114 %argb: tensor<64xf64>, 115 %argx: tensor<32xf64> {linalg.inplaceable = true}) -> tensor<32xf64> { 116 %0 = linalg.generic #trait_matvec 117 ins(%arga, %argb : tensor<32x64xf64, #CSR>, tensor<64xf64>) 118 outs(%argx: tensor<32xf64>) { 119 ^bb(%A: f64, %b: f64, %x: f64): 120 %0 = mulf %A, %b : f64 121 %1 = addf %x, %0 : f64 122 linalg.yield %1 : f64 123 } -> tensor<32xf64> 124 return %0 : tensor<32xf64> 125} 126