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1// RUN: mlir-opt %s -split-input-file -xegpu-vector-linearize -canonicalize | FileCheck %s2 3// CHECK-LABEL: test_vector_insert_2d_idx4// CHECK-SAME: (%[[DEST:.*]]: vector<2x8x4xf32>, %[[SRC:.*]]: vector<4xf32>) -> vector<2x8x4xf32>5// CHECK: %[[ARG_DEST:.*]] = vector.shape_cast %[[DEST]] : vector<2x8x4xf32> to vector<64xf32>6// CHECK: %[[SHUFFLE:.*]] = vector.shuffle %[[ARG_DEST]], %[[SRC]]7// CHECK: [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 64, 65, 66, 67, 16, 17, 18, 19, 20, 21,8// CHECK-SAME: 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45,9// CHECK-SAME: 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63] : vector<64xf32>, vector<4xf32>10// CHECK: %[[RES:.*]] = vector.shape_cast %[[SHUFFLE]] : vector<64xf32> to vector<2x8x4xf32>11// CHECK: return %[[RES]] : vector<2x8x4xf32>12func.func @test_vector_insert_2d_idx(%arg0: vector<2x8x4xf32>, %arg1: vector<4xf32>) -> vector<2x8x4xf32> {13 %0 = vector.insert %arg1, %arg0[0, 3]: vector<4xf32> into vector<2x8x4xf32>14 return %0 : vector<2x8x4xf32>15}16 17// -----18// CHECK-LABEL: test_vector_transpose19// CHECK-SAME: (%[[ORIG_ARG:.*]]: vector<2x8xf32>) -> vector<8x2xf32>20// CHECK: %[[ARG:.*]] = vector.shape_cast %[[ORIG_ARG]] : vector<2x8xf32> to vector<16xf32>21// CHECK: %[[SHUFFLE:.*]] = vector.shuffle %[[ARG]], %[[ARG]]22// CHECK: [0, 8, 1, 9, 2, 10, 3, 11, 4, 12, 5, 13, 6, 14, 7, 15] : vector<16xf32>, vector<16xf32>23// CHECK: %[[RES:.*]] = vector.shape_cast %[[SHUFFLE]] : vector<16xf32> to vector<8x2xf32>24// CHECK: return %[[RES]] : vector<8x2xf32>25func.func @test_vector_transpose(%arg: vector<2x8xf32>) -> vector<8x2xf32> {26 %0 = vector.transpose %arg, [1, 0] : vector<2x8xf32> to vector<8x2xf32>27 return %0 : vector<8x2xf32>28}29 30// -----31// CHECK-LABEL: test_vector_transpose_16x1632// CHECK: vector.shuffle {{.*}} [0, 16, 1, 17, 4, 20, 5, 21, 8, 24, 9, 25, 12, 28, 13, 29] : vector<16xf32>, vector<16xf32>33// CHECK: vector.shuffle {{.*}} [2, 18, 3, 19, 6, 22, 7, 23, 10, 26, 11, 27, 14, 30, 15, 31] : vector<16xf32>, vector<16xf32>34// CHECK-62: vector.shuffle35func.func @test_vector_transpose_16x16(%arg: vector<16x16xf32>) -> vector<16x16xf32> {36 %0 = vector.transpose %arg, [1, 0] : vector<16x16xf32> to vector<16x16xf32>37 return %0 : vector<16x16xf32>38}39 40// -----41 42// CHECK-LABEL: func.func @test_vector_store_load_4x4_f1643// CHECK-SAME: (%[[ARG0:.*]]: memref<4x4xf16>)44// CHECK-DAG: %[[C3:.*]] = arith.constant 3 : index45// CHECK-DAG: %[[C2:.*]] = arith.constant 2 : index46// CHECK-DAG: %[[C1:.*]] = arith.constant 1 : index47// CHECK-DAG: %[[C0:.*]] = arith.constant 0 : index48// CHECK: %[[LOAD0:.*]] = vector.load %[[ARG0]][%[[C0]], %[[C0]]] : memref<4x4xf16>, vector<4xf16>49// CHECK: %[[LOAD1:.*]] = vector.load %[[ARG0]][%[[C1]], %[[C0]]] : memref<4x4xf16>, vector<4xf16>50// CHECK: %[[LOAD2:.*]] = vector.load %[[ARG0]][%[[C2]], %[[C0]]] : memref<4x4xf16>, vector<4xf16>51// CHECK: %[[LOAD3:.*]] = vector.load %[[ARG0]][%[[C3]], %[[C0]]] : memref<4x4xf16>, vector<4xf16>52// CHECK: vector.store %[[LOAD0]], %[[ARG0]][%[[C0]], %[[C0]]] : memref<4x4xf16>, vector<4xf16>53// CHECK: vector.store %[[LOAD1]], %[[ARG0]][%[[C1]], %[[C0]]] : memref<4x4xf16>, vector<4xf16>54// CHECK: vector.store %[[LOAD2]], %[[ARG0]][%[[C2]], %[[C0]]] : memref<4x4xf16>, vector<4xf16>55// CHECK: vector.store %[[LOAD3]], %[[ARG0]][%[[C3]], %[[C0]]] : memref<4x4xf16>, vector<4xf16>56func.func @test_vector_store_load_4x4_f16(%buffer: memref<4x4xf16>) {57 %c0 = arith.constant 0 : index58 %0 = vector.load %buffer[%c0, %c0] : memref<4x4xf16>, vector<4x4xf16>59 vector.store %0, %buffer[%c0, %c0] : memref<4x4xf16>, vector<4x4xf16>60 return61}62 63// -----64// CHECK-LABEL: func.func @test_vector_store_load_4x4x465// CHECK-SAME: (%[[BUF:.*]]: memref<4x4x4xf32>)66// Constants (order not important)67// CHECK-DAG: %[[C0:.*]] = arith.constant 0 : index68// CHECK-DAG: %[[C1:.*]] = arith.constant 1 : index69// CHECK-DAG: %[[C2:.*]] = arith.constant 2 : index70// CHECK-DAG: %[[C3:.*]] = arith.constant 3 : index71// All 16 scalar-slice (row/col plane) loads of 1D vectors72// CHECK-COUNT-16: vector.load {{.*}} : memref<4x4x4xf32>, vector<4xf32>73// No remaining 3D vector load74// CHECK-NOT: vector.load {{.*}} : memref<4x4x4xf32>, vector<4x4x4xf32>75// All 16 stores of 1D vectors76// CHECK-COUNT-16: vector.store {{.*}} : memref<4x4x4xf32>, vector<4xf32>77// CHECK: return78func.func @test_vector_store_load_4x4x4(%buffer: memref<4x4x4xf32>) {79 %c0 = arith.constant 0 : index80 %0 = vector.load %buffer[%c0, %c0, %c0] : memref<4x4x4xf32>, vector<4x4x4xf32>81 vector.store %0, %buffer[%c0, %c0, %c0] : memref<4x4x4xf32>, vector<4x4x4xf32>82 return83}84 85// -----86// CHECK-LABEL: func.func @test_linearize_index87// CHECK-SAME: (%[[ARG0:.*]]: vector<2x2xindex>, %[[ARG1:.*]]: vector<2x2xi32>) -> vector<2x2xindex>88// CHECK: %[[CST:.*]] = arith.constant dense<[0, 1, 2, 3]> : vector<4xindex>89// CHECK: %[[CAST1:.*]] = vector.shape_cast %[[ARG1]] : vector<2x2xi32> to vector<4xi32>90// CHECK: %[[CAST2:.*]] = vector.shape_cast %[[ARG0]] : vector<2x2xindex> to vector<4xindex>91// CHECK: %[[ADDI:.*]] = arith.addi %[[CAST2]], %[[CST]] : vector<4xindex>92// CHECK: %[[INDEX_CAST1:.*]] = arith.index_cast %[[ADDI]] : vector<4xindex> to vector<4xi32>93// CHECK: %[[MULI:.*]] = arith.muli %[[INDEX_CAST1]], %[[CAST1]] : vector<4xi32>94// CHECK: %[[INDEX_CAST2:.*]] = arith.index_cast %[[MULI]] : vector<4xi32> to vector<4xindex>95// CHECK: %[[RESULT:.*]] = vector.shape_cast %[[INDEX_CAST2]] : vector<4xindex> to vector<2x2xindex>96// CHECK: return %[[RESULT]] : vector<2x2xindex>97func.func @test_linearize_index(%arg0: vector<2x2xindex>, %arg1: vector<2x2xi32>) -> vector<2x2xindex> {98 %0 = arith.constant dense<[[0, 1], [2, 3]]> : vector<2x2xindex>99 // Arith and math ops are handled in generic way, check some of them100 %1 = arith.addi %arg0, %0 : vector<2x2xindex>101 %2 = arith.index_cast %1 : vector<2x2xindex> to vector<2x2xi32>102 %3 = arith.muli %2, %arg1 : vector<2x2xi32>103 %4 = arith.index_cast %3 : vector<2x2xi32> to vector<2x2xindex>104 return %4 : vector<2x2xindex>105}106 107// -----108// CHECK-LABEL: func.func @broadcast_stretch_at_start109// CHECK-SAME: (%[[ARG0:.*]]: vector<1x4xf32>) -> vector<3x4xf32>110// CHECK: %[[POISON:.*]] = ub.poison : vector<12xf32>111// CHECK: %[[CAST:.*]] = vector.shape_cast %[[ARG0]] : vector<1x4xf32> to vector<4xf32>112// CHECK: %[[SHUFFLE1:.*]] = vector.shuffle %[[POISON]], %[[CAST]] [12, 13, 14, 15, 4, 5, 6, 7, 8, 9, 10, 11] : vector<12xf32>, vector<4xf32>113// CHECK: %[[SHUFFLE2:.*]] = vector.shuffle %[[SHUFFLE1]], %[[CAST]] [0, 1, 2, 3, 12, 13, 14, 15, 8, 9, 10, 11] : vector<12xf32>, vector<4xf32>114// CHECK: %[[SHUFFLE3:.*]] = vector.shuffle %[[SHUFFLE2]], %[[CAST]] [0, 1, 2, 3, 4, 5, 6, 7, 12, 13, 14, 15] : vector<12xf32>, vector<4xf32>115// CHECK: %[[RESULT:.*]] = vector.shape_cast %[[SHUFFLE3]] : vector<12xf32> to vector<3x4xf32>116func.func @broadcast_stretch_at_start(%arg0: vector<1x4xf32>) -> vector<3x4xf32> {117 %0 = vector.broadcast %arg0 : vector<1x4xf32> to vector<3x4xf32>118 return %0 : vector<3x4xf32>119}120 121// -----122// CHECK-LABEL: func.func @broadcast_stretch_at_end123// CHECK-SAME: (%[[ARG0:.*]]: vector<4x1xf32>) -> vector<4x3xf32>124// CHECK: %[[POISON:.*]] = ub.poison : vector<12xf32>125// CHECK: %[[EXTRACT1:.*]] = vector.extract %[[ARG0]][0, 0] : f32 from vector<4x1xf32>126// CHECK: %[[BROADCAST1:.*]] = vector.broadcast %[[EXTRACT1]] : f32 to vector<3xf32>127// CHECK: vector.shuffle128// CHECK: %[[EXTRACT2:.*]] = vector.extract %[[ARG0]][1, 0] : f32 from vector<4x1xf32>129// CHECK: %[[BROADCAST2:.*]] = vector.broadcast %[[EXTRACT2]] : f32 to vector<3xf32>130// CHECK: vector.shuffle131// CHECK: %[[EXTRACT3:.*]] = vector.extract %[[ARG0]][2, 0] : f32 from vector<4x1xf32>132// CHECK: %[[BROADCAST3:.*]] = vector.broadcast %[[EXTRACT3]] : f32 to vector<3xf32>133// CHECK: vector.shuffle134// CHECK: %[[EXTRACT4:.*]] = vector.extract %[[ARG0]][3, 0] : f32 from vector<4x1xf32>135// CHECK: %[[BROADCAST4:.*]] = vector.broadcast %[[EXTRACT4]] : f32 to vector<3xf32>136// CHECK: vector.shuffle137// CHECK: vector.shape_cast {{.*}} : vector<12xf32> to vector<4x3xf32>138func.func @broadcast_stretch_at_end(%arg0: vector<4x1xf32>) -> vector<4x3xf32> {139 %0 = vector.broadcast %arg0 : vector<4x1xf32> to vector<4x3xf32>140 return %0 : vector<4x3xf32>141}142 143// -----144// CHECK-LABEL: func.func @broadcast_stretch_in_middle145// CHECK-SAME: (%[[ARG0:.*]]: vector<4x1x2xf32>) -> vector<4x3x2xf32>146// CHECK: ub.poison : vector<6xf32>147// CHECK: ub.poison : vector<24xf32>148// CHECK: %[[CAST:.*]] = vector.shape_cast %[[ARG0]] : vector<4x1x2xf32> to vector<8xf32>149// CHECK-COUNT-20: vector.shuffle150// CHECK: vector.shape_cast {{.*}} : vector<24xf32> to vector<4x3x2xf32>151// CHECK-NOT: vector.broadcast152func.func @broadcast_stretch_in_middle(%arg0: vector<4x1x2xf32>) -> vector<4x3x2xf32> {153 %0 = vector.broadcast %arg0 : vector<4x1x2xf32> to vector<4x3x2xf32>154 return %0 : vector<4x3x2xf32>155}156 157// CHECK-LABEL: func.func @gather_memref_2d158// CHECK-SAME: (%arg0: memref<?x?xf32>, %arg1: vector<2x3xindex>, %arg2: vector<2x3xi1>, %arg3: vector<2x3xf32>) -> vector<2x3xf32> {159 160// CHECK: %0 = ub.poison : vector<6xf32>161// CHECK: %c1 = arith.constant 1 : index162// CHECK: %c0 = arith.constant 0 : index163// CHECK: %1 = vector.shape_cast %arg3 : vector<2x3xf32> to vector<6xf32>164 165// First shuffle + if ladder for row 0166// CHECK: %2 = vector.shuffle %1, %1 [0, 1, 2]167// CHECK: %3 = vector.extract %arg2[0, 0]168// CHECK: %4 = vector.extract %arg1[0, 0]169// CHECK: %5 = arith.addi %4, %c1170// CHECK: %6 = scf.if %3 -> (vector<3xf32>) {171// CHECK: %{{.*}} = vector.load %arg0[%c0, %5] : memref<?x?xf32>, vector<1xf32>172// CHECK: %{{.*}} = vector.extract {{.*}}[0] : f32173// CHECK: %{{.*}} = vector.insert {{.*}}, %2 [0] : f32 into vector<3xf32>174// CHECK: scf.yield {{.*}} : vector<3xf32>175// CHECK: } else {176// CHECK: scf.yield %2 : vector<3xf32>177// CHECK: }178 179// CHECK: %7 = vector.extract %arg2[0, 1]180// CHECK: %8 = vector.extract %arg1[0, 1]181// CHECK: %9 = arith.addi %8, %c1182// CHECK: %10 = scf.if %7 -> (vector<3xf32>)183 184// … (similar checks for the rest of row 0, then row 1)185 186// CHECK: %15 = vector.shuffle %0, %{{.*}} [6, 7, 8, 3, 4, 5]187// CHECK: %16 = vector.shuffle %1, %1 [3, 4, 5]188 189// Row 1 if ladder checks190// CHECK: %17 = vector.extract %arg2[1, 0]191// CHECK: %18 = vector.extract %arg1[1, 0]192// CHECK: %19 = arith.addi %18, %c1193// CHECK: %20 = scf.if %17 -> (vector<3xf32>)194 195// … (similar checks for remaining row 1 inserts)196 197// Final reshuffle and cast198// CHECK: %29 = vector.shuffle %15, %{{.*}} [0, 1, 2, 6, 7, 8]199// CHECK: %30 = vector.shape_cast %29 : vector<6xf32> to vector<2x3xf32>200// CHECK: return %30 : vector<2x3xf32>201func.func @gather_memref_2d(%base: memref<?x?xf32>, %v: vector<2x3xindex>, %mask: vector<2x3xi1>, %pass_thru: vector<2x3xf32>) -> vector<2x3xf32> {202 %c0 = arith.constant 0 : index203 %c1 = arith.constant 1 : index204 %0 = vector.gather %base[%c0, %c1][%v], %mask, %pass_thru : memref<?x?xf32>, vector<2x3xindex>, vector<2x3xi1>, vector<2x3xf32> into vector<2x3xf32>205 return %0 : vector<2x3xf32>206}207 208// -----209// Check for vector linearization interoperability with XeGPU dialect ops.210// The `xegpu-vector-linearize` pass does not itself affect the XeGPU ops.211 212// CHECK: gpu.func @test_kernel(%arg0: memref<8x16xf16>, %arg1: memref<16x16xf16>, %arg2: memref<8x16xf32>) kernel {213// CHECK: %c0 = arith.constant 0 : index214// CHECK: %cst = arith.constant dense<0.000000e+00> : vector<64xf16>215// CHECK: %cst_0 = arith.constant dense<5.000000e+00> : vector<64xf32>216 217// CHECK: %0 = xegpu.create_nd_tdesc %arg0[%c0, %c0]218// CHECK: %1 = xegpu.load_nd %0219// CHECK: %2 = vector.shape_cast %1 : vector<8x16xf16> to vector<128xf16>220// CHECK: %3 = vector.shuffle %2, %cst {{.*}} : vector<128xf16>, vector<64xf16>221// CHECK: %4 = vector.shape_cast %3 : vector<128xf16> to vector<8x16xf16>222 223// CHECK: %5 = xegpu.create_nd_tdesc %arg1[%c0, %c0]224// CHECK: %6 = xegpu.load_nd %5225// CHECK: %7 = vector.shape_cast %6 : vector<16x16xf16> to vector<256xf16>226// CHECK: %8 = vector.shuffle %7, %cst {{.*}} : vector<256xf16>, vector<64xf16>227// CHECK: %9 = vector.shape_cast %8 : vector<256xf16> to vector<16x16xf16>228 229// CHECK: %10 = xegpu.dpas %4, %9 : vector<8x16xf16>, vector<16x16xf16> -> vector<8x16xf32>230// CHECK: %11 = vector.shape_cast %10 : vector<8x16xf32> to vector<128xf32>231// CHECK: %12 = vector.shuffle %11, %11 {{.*}} : vector<128xf32>, vector<128xf32>232// CHECK: %13 = arith.addf %12, %cst_0 : vector<64xf32>233// CHECK: %14 = vector.shuffle %11, %13 {{.*}} : vector<128xf32>, vector<64xf32>234// CHECK: %15 = vector.shape_cast %14 : vector<128xf32> to vector<8x16xf32>235 236// CHECK: %16 = xegpu.create_nd_tdesc %arg2[%c0, %c0]237// CHECK: xegpu.store_nd %15, %16238// CHECK: gpu.return239 240gpu.module @test_kernel {241 gpu.func @test_kernel(%A: memref<8x16xf16>, %B: memref<16x16xf16>, %C: memref<8x16xf32>) kernel {242 %c0 = arith.constant 0 : index243 %cst_vec_0 = arith.constant dense<0.000000e+00> : vector<8x8xf16>244 %cst_vec_1 = arith.constant dense<0.000000e+00> : vector<8x8xf16>245 %cst_vec_2 = arith.constant dense<5.000000e+00> : vector<8x8xf32>246 %a_tdesc = xegpu.create_nd_tdesc %A[%c0, %c0] : memref<8x16xf16> -> !xegpu.tensor_desc<8x16xf16, #xegpu.block_tdesc_attr<array_length = 1>>247 %a_val = xegpu.load_nd %a_tdesc : !xegpu.tensor_desc<8x16xf16, #xegpu.block_tdesc_attr<array_length = 1>> -> vector<8x16xf16>248 %a_val_0 = vector.insert_strided_slice %cst_vec_0, %a_val{offsets = [0, 0], sizes = [8, 8], strides = [1, 1]}: vector<8x8xf16> into vector<8x16xf16>249 %b_tdesc = xegpu.create_nd_tdesc %B[%c0, %c0] : memref<16x16xf16> -> !xegpu.tensor_desc<16x16xf16, #xegpu.block_tdesc_attr<array_length = 1>>250 251 %b_val = xegpu.load_nd %b_tdesc : !xegpu.tensor_desc<16x16xf16, #xegpu.block_tdesc_attr<array_length = 1>> -> vector<16x16xf16>252 %b_val_0 = vector.insert_strided_slice %cst_vec_1, %b_val{offsets = [0, 0], sizes = [8, 8], strides = [1, 1]}: vector<8x8xf16> into vector<16x16xf16>253 %c_val = xegpu.dpas %a_val_0, %b_val_0 : vector<8x16xf16>, vector<16x16xf16> -> vector<8x16xf32>254 %c_val_0 = vector.extract_strided_slice %c_val {offsets = [0, 0], sizes = [8, 8], strides = [1, 1]} : vector<8x16xf32> to vector<8x8xf32>255 %c_addf = arith.addf %c_val_0, %cst_vec_2 : vector<8x8xf32>256 %c_result = vector.insert_strided_slice %c_addf, %c_val {offsets = [0, 0], sizes = [8, 8], strides = [1, 1]} : vector<8x8xf32> into vector<8x16xf32>257 %c_tdesc = xegpu.create_nd_tdesc %C[%c0, %c0] : memref<8x16xf32> -> !xegpu.tensor_desc<8x16xf32, #xegpu.block_tdesc_attr<array_length = 1>>258 xegpu.store_nd %c_result, %c_tdesc : vector<8x16xf32>, !xegpu.tensor_desc<8x16xf32>259 gpu.return260 }261}262 263 264