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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, this5// config could be moved to lit.local.cfg. However, there are downstream users that6// do not use these LIT config files. Hence why this is kept inline.7//8// DEFINE: %{sparsifier_opts} = enable-runtime-library=true9// 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_utils13// DEFINE: %{run_libs_sve} = -shared-libs=%native_mlir_runner_utils,%native_mlir_c_runner_utils14// DEFINE: %{run_opts} = -e main -entry-point-result=void15// 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_symmetric.mtx22// RUN: %{compile} | env %{env} %{run} | FileCheck %s23//24// Do the same run, but now with direct IR generation.25// REDEFINE: %{sparsifier_opts} = enable-runtime-library=false26// RUN: %{compile} | env %{env} %{run} | FileCheck %s27//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=true30// RUN: %{compile} | env %{env} %{run} | FileCheck %s31//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// TODO: The test currently only operates on the triangular part of the36// symmetric matrix.37 38!Filename = !llvm.ptr39 40#SparseMatrix = #sparse_tensor.encoding<{41 map = (d0, d1) -> (d0 : compressed, d1 : compressed)42}>43 44#trait_sum_reduce = {45 indexing_maps = [46 affine_map<(i,j) -> (i,j)>, // A47 affine_map<(i,j) -> ()> // x (out)48 ],49 iterator_types = ["reduction", "reduction"],50 doc = "x += A(i,j)"51}52 53//54// Integration test that lowers a kernel annotated as sparse to55// actual sparse code, initializes a matching sparse storage scheme56// from file, and runs the resulting code with the JIT compiler.57//58module {59 //60 // A kernel that sum-reduces a matrix to a single scalar.61 //62 func.func @kernel_sum_reduce(%arga: tensor<?x?xf64, #SparseMatrix>,63 %argx: tensor<f64>) -> tensor<f64> {64 %0 = linalg.generic #trait_sum_reduce65 ins(%arga: tensor<?x?xf64, #SparseMatrix>)66 outs(%argx: tensor<f64>) {67 ^bb(%a: f64, %x: f64):68 %0 = arith.addf %x, %a : f6469 linalg.yield %0 : f6470 } -> tensor<f64>71 return %0 : tensor<f64>72 }73 74 func.func private @getTensorFilename(index) -> (!Filename)75 76 //77 // Main driver that reads matrix from file and calls the sparse kernel.78 //79 func.func @main() {80 %d0 = arith.constant 0.0 : f6481 %c0 = arith.constant 0 : index82 83 // Setup memory for a single reduction scalar,84 // initialized to zero.85 %x = tensor.from_elements %d0 : tensor<f64>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 // Call the kernel.92 %0 = call @kernel_sum_reduce(%a, %x)93 : (tensor<?x?xf64, #SparseMatrix>, tensor<f64>) -> tensor<f64>94 95 // Print the result for verification.96 //97 // CHECK: 24.198 //99 %v = tensor.extract %0[] : tensor<f64>100 vector.print %v : f64101 102 // Release the resources.103 bufferization.dealloc_tensor %a : tensor<?x?xf64, #SparseMatrix>104 bufferization.dealloc_tensor %0 : tensor<f64>105 106 return107 }108}109