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1// RUN: mlir-opt %s --linalg-generalize-named-ops \2// RUN: --pre-sparsification-rewrite \3// RUN: --sparse-reinterpret-map \4// RUN: --sparsification="parallelization-strategy=dense-outer-loop" \5// RUN: --sparse-gpu-codegen | FileCheck %s6 7#CSR = #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : dense, d1 : compressed) }>8 9//10// Compute matrix vector y = Ax11//12// CHECK-LABEL: gpu.module @sparse_kernels13// CHECK: gpu.func @kernel0(14// CHECK-SAME: %[[VAL_0:.*0]]: index,15// CHECK-SAME: %[[VAL_1:.*1]]: memref<?xf64>,16// CHECK-SAME: %[[VAL_2:.*2]]: memref<?xindex>,17// CHECK-SAME: %[[VAL_3:.*3]]: memref<?xindex>,18// CHECK-SAME: %[[VAL_4:.*4]]: memref<?xf64>,19// CHECK-SAME: %[[VAL_5:.*5]]: memref<?xf64>) kernel {20// CHECK: %[[VAL_6:.*]] = arith.constant 1 : index21// CHECK: %[[VAL_7:.*]] = gpu.block_id x22// CHECK: %[[VAL_8:.*]] = gpu.block_dim x23// CHECK: %[[VAL_9:.*]] = gpu.thread_id x24// CHECK: %[[VAL_10:.*]] = gpu.grid_dim x25// CHECK: %[[VAL_11:.*]] = arith.muli %[[VAL_7]], %[[VAL_8]] : index26// CHECK: %[[VAL_12:.*]] = arith.addi %[[VAL_11]], %[[VAL_9]] : index27// CHECK: %[[VAL_13:.*]] = arith.muli %[[VAL_8]], %[[VAL_10]] : index28// CHECK: scf.for %[[VAL_14:.*]] = %[[VAL_12]] to %[[VAL_0]] step %[[VAL_13]] {29// CHECK: %[[VAL_15:.*]] = memref.load %[[VAL_1]]{{\[}}%[[VAL_14]]] : memref<?xf64>30// CHECK: %[[VAL_16:.*]] = memref.load %[[VAL_2]]{{\[}}%[[VAL_14]]] : memref<?xindex>31// CHECK: %[[VAL_17:.*]] = arith.addi %[[VAL_14]], %[[VAL_6]] : index32// CHECK: %[[VAL_18:.*]] = memref.load %[[VAL_2]]{{\[}}%[[VAL_17]]] : memref<?xindex>33// CHECK: %[[VAL_19:.*]] = scf.for %[[VAL_20:.*]] = %[[VAL_16]] to %[[VAL_18]] step %[[VAL_6]] iter_args(%[[VAL_21:.*]] = %[[VAL_15]]) -> (f64) {34// CHECK: %[[VAL_22:.*]] = memref.load %[[VAL_3]]{{\[}}%[[VAL_20]]] : memref<?xindex>35// CHECK: %[[VAL_23:.*]] = memref.load %[[VAL_4]]{{\[}}%[[VAL_20]]] : memref<?xf64>36// CHECK: %[[VAL_24:.*]] = memref.load %[[VAL_5]]{{\[}}%[[VAL_22]]] : memref<?xf64>37// CHECK: %[[VAL_25:.*]] = arith.mulf %[[VAL_23]], %[[VAL_24]] : f6438// CHECK: %[[VAL_26:.*]] = arith.addf %[[VAL_21]], %[[VAL_25]] : f6439// CHECK: scf.yield %[[VAL_26]] : f6440// CHECK: } {"Emitted from" = "linalg.generic"}41// CHECK: memref.store %[[VAL_27:.*]], %[[VAL_1]]{{\[}}%[[VAL_14]]] : memref<?xf64>42// CHECK: }43// CHECK: gpu.return44// CHECK: }45//46// CHECK-LABEL: func.func @matvec47// CHECK: gpu.wait async48// CHECK: gpu.alloc async49// CHECK: %[[S0:.*]] = gpu.memcpy async50// CHECK: gpu.wait async51// CHECK: gpu.alloc async52// CHECK: %[[S1:.*]] = gpu.memcpy async53// CHECK: gpu.wait async54// CHECK: gpu.alloc async55// CHECK: %[[S2:.*]] = gpu.memcpy async56// CHECK: gpu.wait async57// CHECK: gpu.alloc async58// CHECK: %[[S3:.*]] = gpu.memcpy async59// CHECK: gpu.wait async60// CHECK: gpu.alloc async61// CHECK: %[[S4:.*]] = gpu.memcpy async62// CHECK: gpu.wait [%[[S0]], %[[S1]], %[[S2]], %[[S3]], %[[S4]]63// CHECK: %[[T0:.*]] = gpu.launch_func async @sparse_kernels::@kernel0 blocks64// CHECK: %[[M0:.*]] = gpu.memcpy async [%[[T0]]]65// CHECK: %[[M1:.*]] = gpu.dealloc async [%[[M0]]]66// CHECK: %[[M2:.*]] = gpu.wait async67// CHECK: %[[M3:.*]] = gpu.dealloc async [%[[M2]]]68// CHECK: %[[M4:.*]] = gpu.wait async69// CHECK: %[[M5:.*]] = gpu.dealloc async [%[[M4]]]70// CHECK: %[[M6:.*]] = gpu.wait async71// CHECK: %[[M7:.*]] = gpu.dealloc async [%[[M6]]]72// CHECK: %[[M8:.*]] = gpu.wait async73// CHECK: %[[M9:.*]] = gpu.dealloc async [%[[M8]]]74// CHECK: gpu.wait [%[[M1]], %[[M3]], %[[M5]], %[[M7]], %[[M9]]75//76func.func @matvec(%A: tensor<?x?xf64, #CSR>, %x: tensor<?xf64>, %y_in: tensor<?xf64>) -> tensor<?xf64> {77 %y_out = linalg.matvec78 ins(%A, %x: tensor<?x?xf64, #CSR>, tensor<?xf64>)79 outs(%y_in: tensor<?xf64>) -> tensor<?xf64>80 return %y_out : tensor<?xf64>81}82