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/test.mtx" 22// RUN: %{compile} | env %{env} %{run} | FileCheck %s 23// 24// Do the same run, but now with direct IR generation and vectorization. 25// REDEFINE: %{sparsifier_opts} = enable-runtime-library=false vl=2 reassociate-fp-reductions=true enable-index-optimizations=true 26// RUN: %{compile} | env %{env} %{run} | FileCheck %s 27// 28// Do the same run, but now with direct IR generation and, if available, VLA 29// vectorization. 30// RUN: %if mlir_arm_sve_tests %{ %{compile_sve} | env %{env} %{run_sve} | FileCheck %s %} 31 32!Filename = !llvm.ptr 33 34#DCSR = #sparse_tensor.encoding<{ 35 map = (d0, d1) -> (d0 : compressed, d1 : compressed) 36}> 37 38#eltwise_mult = { 39 indexing_maps = [ 40 affine_map<(i,j) -> (i,j)> // X (out) 41 ], 42 iterator_types = ["parallel", "parallel"], 43 doc = "X(i,j) *= X(i,j)" 44} 45 46// 47// Integration test that lowers a kernel annotated as sparse to 48// actual sparse code, initializes a matching sparse storage scheme 49// from file, and runs the resulting code with the JIT compiler. 50// 51module { 52 // 53 // A kernel that multiplies a sparse matrix A with itself 54 // in an element-wise fashion. In this operation, we have 55 // a sparse tensor as output, but although the values of the 56 // sparse tensor change, its nonzero structure remains the same. 57 // 58 func.func @kernel_eltwise_mult(%argx: tensor<?x?xf64, #DCSR>) 59 -> tensor<?x?xf64, #DCSR> { 60 %0 = linalg.generic #eltwise_mult 61 outs(%argx: tensor<?x?xf64, #DCSR>) { 62 ^bb(%x: f64): 63 %0 = arith.mulf %x, %x : f64 64 linalg.yield %0 : f64 65 } -> tensor<?x?xf64, #DCSR> 66 return %0 : tensor<?x?xf64, #DCSR> 67 } 68 69 func.func private @getTensorFilename(index) -> (!Filename) 70 71 // 72 // Main driver that reads matrix from file and calls the sparse kernel. 73 // 74 func.func @main() { 75 %d0 = arith.constant 0.0 : f64 76 %c0 = arith.constant 0 : index 77 78 // Read the sparse matrix from file, construct sparse storage. 79 %fileName = call @getTensorFilename(%c0) : (index) -> (!Filename) 80 %x = sparse_tensor.new %fileName : !Filename to tensor<?x?xf64, #DCSR> 81 82 // Call kernel. 83 %0 = call @kernel_eltwise_mult(%x) : (tensor<?x?xf64, #DCSR>) -> tensor<?x?xf64, #DCSR> 84 85 // Print the result for verification. 86 // 87 // CHECK: ---- Sparse Tensor ---- 88 // CHECK-NEXT: nse = 9 89 // CHECK-NEXT: dim = ( 5, 5 ) 90 // CHECK-NEXT: lvl = ( 5, 5 ) 91 // CHECK-NEXT: pos[0] : ( 0, 5 ) 92 // CHECK-NEXT: crd[0] : ( 0, 1, 2, 3, 4 ) 93 // CHECK-NEXT: pos[1] : ( 0, 2, 4, 5, 7, 9 ) 94 // CHECK-NEXT: crd[1] : ( 0, 3, 1, 4, 2, 0, 3, 1, 4 ) 95 // CHECK-NEXT: values : ( 1, 1.96, 4, 6.25, 9, 16.81, 16, 27.04, 25 ) 96 // CHECK-NEXT: ---- 97 // 98 sparse_tensor.print %0 : tensor<?x?xf64, #DCSR> 99 100 // Release the resources. 101 bufferization.dealloc_tensor %x : tensor<?x?xf64, #DCSR> 102 103 return 104 } 105} 106