1//-------------------------------------------------------------------------------------------------- 2// WHEN CREATING A NEW TEST, PLEASE JUST COPY & PASTE WITHOUT EDITS. 3// 4// Set-up that's shared across all tests in this directory. In principle, this 5// config could be moved to lit.local.cfg. However, there are downstream users that 6// do not use these LIT config files. Hence why this is kept inline. 7// 8// DEFINE: %{sparsifier_opts} = enable-runtime-library=true 9// DEFINE: %{sparsifier_opts_sve} = enable-arm-sve=true %{sparsifier_opts} 10// DEFINE: %{compile} = mlir-opt %s --sparsifier="%{sparsifier_opts}" 11// DEFINE: %{compile_sve} = mlir-opt %s --sparsifier="%{sparsifier_opts_sve}" 12// DEFINE: %{run_libs} = -shared-libs=%mlir_c_runner_utils,%mlir_runner_utils 13// DEFINE: %{run_libs_sve} = -shared-libs=%native_mlir_runner_utils,%native_mlir_c_runner_utils 14// DEFINE: %{run_opts} = -e main -entry-point-result=void 15// DEFINE: %{run} = mlir-runner %{run_opts} %{run_libs} 16// DEFINE: %{run_sve} = %mcr_aarch64_cmd --march=aarch64 --mattr="+sve" %{run_opts} %{run_libs_sve} 17// 18// DEFINE: %{env} = 19//-------------------------------------------------------------------------------------------------- 20 21// REDEFINE: %{env} = TENSOR0="%mlir_src_dir/test/Integration/data/wide.mtx" 22// RUN: %{compile} | env %{env} %{run} | FileCheck %s 23// 24// Do the same run, but now with direct IR generation. 25// REDEFINE: %{sparsifier_opts} = enable-runtime-library=false 26// RUN: %{compile} | env %{env} %{run} | FileCheck %s 27// 28// Do the same run, but now with vectorization. 29// REDEFINE: %{sparsifier_opts} = enable-runtime-library=false vl=2 reassociate-fp-reductions=true enable-index-optimizations=true 30// RUN: %{compile} | env %{env} %{run} | FileCheck %s 31// 32// Do the same run, but now with VLA vectorization. 33// RUN: %if mlir_arm_sve_tests %{ %{compile_sve} | env %{env} %{run_sve} | FileCheck %s %} 34 35!Filename = !llvm.ptr 36 37#SparseMatrix = #sparse_tensor.encoding<{ 38 map = (d0, d1) -> (d0 : dense, d1 : compressed) 39}> 40 41#spmm = { 42 indexing_maps = [ 43 affine_map<(i,j,k) -> (i,k)>, // A 44 affine_map<(i,j,k) -> (k,j)>, // B 45 affine_map<(i,j,k) -> (i,j)> // X (out) 46 ], 47 iterator_types = ["parallel", "parallel", "reduction"], 48 doc = "X(i,j) += A(i,k) * B(k,j)" 49} 50 51// 52// Integration test that lowers a kernel annotated as sparse to 53// actual sparse code, initializes a matching sparse storage scheme 54// from file, and runs the resulting code with the JIT compiler. 55// 56module { 57 // 58 // A kernel that multiplies a sparse matrix A with a dense matrix B 59 // into a dense matrix X. 60 // 61 func.func @kernel_spmm(%arga: tensor<?x?xf64, #SparseMatrix>, 62 %argb: tensor<?x?xf64>, 63 %argx: tensor<?x?xf64>) -> tensor<?x?xf64> { 64 %0 = linalg.generic #spmm 65 ins(%arga, %argb: tensor<?x?xf64, #SparseMatrix>, tensor<?x?xf64>) 66 outs(%argx: tensor<?x?xf64>) { 67 ^bb(%a: f64, %b: f64, %x: f64): 68 %0 = arith.mulf %a, %b : f64 69 %1 = arith.addf %x, %0 : f64 70 linalg.yield %1 : f64 71 } -> tensor<?x?xf64> 72 return %0 : tensor<?x?xf64> 73 } 74 75 func.func private @getTensorFilename(index) -> (!Filename) 76 77 // 78 // Main driver that reads matrix from file and calls the sparse kernel. 79 // 80 func.func @main() { 81 %i0 = arith.constant 0.0 : f64 82 %c0 = arith.constant 0 : index 83 %c1 = arith.constant 1 : index 84 %c4 = arith.constant 4 : index 85 %c256 = arith.constant 256 : index 86 87 // Read the sparse matrix from file, construct sparse storage. 88 %fileName = call @getTensorFilename(%c0) : (index) -> (!Filename) 89 %a = sparse_tensor.new %fileName : !Filename to tensor<?x?xf64, #SparseMatrix> 90 91 // Initialize dense tensors. 92 %b = tensor.generate %c256, %c4 { 93 ^bb0(%i : index, %j : index): 94 %k0 = arith.muli %i, %c4 : index 95 %k1 = arith.addi %j, %k0 : index 96 %k2 = arith.index_cast %k1 : index to i32 97 %k = arith.sitofp %k2 : i32 to f64 98 tensor.yield %k : f64 99 } : tensor<?x?xf64> 100 101 %x = tensor.generate %c4, %c4 { 102 ^bb0(%i : index, %j : index): 103 tensor.yield %i0 : f64 104 } : tensor<?x?xf64> 105 106 // Call kernel. 107 %0 = call @kernel_spmm(%a, %b, %x) 108 : (tensor<?x?xf64, #SparseMatrix>, tensor<?x?xf64>, tensor<?x?xf64>) -> tensor<?x?xf64> 109 110 // Print the result for verification. 111 // 112 // CHECK: ( ( 3548, 3550, 3552, 3554 ), ( 6052, 6053, 6054, 6055 ), ( -56, -63, -70, -77 ), ( -13704, -13709, -13714, -13719 ) ) 113 // 114 %v = vector.transfer_read %0[%c0, %c0], %i0: tensor<?x?xf64>, vector<4x4xf64> 115 vector.print %v : vector<4x4xf64> 116 117 // Release the resources. 118 bufferization.dealloc_tensor %a : tensor<?x?xf64, #SparseMatrix> 119 bufferization.dealloc_tensor %b : tensor<?x?xf64> 120 bufferization.dealloc_tensor %0 : tensor<?x?xf64> 121 122 return 123 } 124} 125