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// RUN: %{compile} | %{run} | FileCheck %s 22// 23// Do the same run, but now with direct IR generation. 24// REDEFINE: %{sparsifier_opts} = enable-runtime-library=false 25// RUN: %{compile} | %{run} | FileCheck %s 26// 27// Do the same run, but now with direct IR generation and vectorization. 28// REDEFINE: %{sparsifier_opts} = enable-runtime-library=false vl=2 reassociate-fp-reductions=true enable-index-optimizations=true 29// RUN: %{compile} | %{run} | FileCheck %s 30// 31// Do the same run, but now with direct IR generation and VLA vectorization. 32// RUN: %if mlir_arm_sve_tests %{ %{compile_sve} | %{run_sve} | FileCheck %s %} 33 34#CSC = #sparse_tensor.encoding<{ 35 map = (d0, d1) -> (d1 : dense, d0 : compressed) 36}> 37 38module { 39 // 40 // Column-wise storage forces the ijk loop to permute into jki 41 // so that access pattern expansion (workspace) needs to be 42 // done along dimension with size 8. 43 // 44 func.func @matmul(%A: tensor<8x2xf64, #CSC>, 45 %B: tensor<2x4xf64, #CSC>) -> tensor<8x4xf64, #CSC> { 46 %C = tensor.empty() : tensor<8x4xf64, #CSC> 47 %D = linalg.matmul 48 ins(%A, %B: tensor<8x2xf64, #CSC>, tensor<2x4xf64, #CSC>) 49 outs(%C: tensor<8x4xf64, #CSC>) -> tensor<8x4xf64, #CSC> 50 return %D: tensor<8x4xf64, #CSC> 51 } 52 53 // 54 // Main driver. 55 // 56 func.func @main() { 57 %c0 = arith.constant 0 : index 58 %d1 = arith.constant -1.0 : f64 59 60 // Initialize various dense matrices for stress testing. 61 %da = arith.constant dense<[ 62 [ 1.1, 2.1 ], 63 [ 1.2, 2.2 ], 64 [ 1.3, 2.3 ], 65 [ 1.4, 2.4 ], 66 [ 1.5, 2.5 ], 67 [ 1.6, 2.6 ], 68 [ 1.7, 2.7 ], 69 [ 1.8, 2.8 ] 70 ]> : tensor<8x2xf64> 71 %db = arith.constant dense<[ 72 [ 10.1, 11.1, 12.1, 13.1 ], 73 [ 10.2, 11.2, 12.2, 13.2 ] 74 ]> : tensor<2x4xf64> 75 76 // Convert all these matrices to sparse format. 77 %x1 = sparse_tensor.convert %da : tensor<8x2xf64> to tensor<8x2xf64, #CSC> 78 %x2 = sparse_tensor.convert %db : tensor<2x4xf64> to tensor<2x4xf64, #CSC> 79 80 // Call kernels with dense. 81 %x3 = call @matmul(%x1, %x2) 82 : (tensor<8x2xf64, #CSC>, 83 tensor<2x4xf64, #CSC>) -> tensor<8x4xf64, #CSC> 84 85 // 86 // CHECK: ---- Sparse Tensor ---- 87 // CHECK-NEXT: nse = 32 88 // CHECK-NEXT: dim = ( 8, 4 ) 89 // CHECK-NEXT: lvl = ( 4, 8 ) 90 // CHECK-NEXT: pos[1] : ( 0, 8, 16, 24, 32 ) 91 // CHECK-NEXT: crd[1] : ( 0, 1, 2, 3, 4, 5, 6, 7, 0, 1, 2, 3, 4, 5, 6, 7, 0, 92 // CHECK-SAME: 1, 2, 3, 4, 5, 6, 7, 0, 1, 2, 3, 4, 5, 6, 7 ) 93 // CHECK-NEXT: values : ( 32.53, 34.56, 36.59, 38.62, 40.65, 42.68, 44.71, 46.74, 94 // CHECK-SAME: 35.73, 37.96, 40.19, 42.42, 44.65, 46.88, 49.11, 51.34, 95 // CHECK-SAME: 38.93, 41.36, 43.79, 46.22, 48.65, 51.08, 53.51, 55.94, 96 // CHECK-SAME: 42.13, 44.76, 47.39, 50.02, 52.65, 55.28, 57.91, 60.54 ) 97 // CHECK-NEXT: ---- 98 // 99 sparse_tensor.print %x3 : tensor<8x4xf64, #CSC> 100 101 // Release the resources. 102 bufferization.dealloc_tensor %x1 : tensor<8x2xf64, #CSC> 103 bufferization.dealloc_tensor %x2 : tensor<2x4xf64, #CSC> 104 bufferization.dealloc_tensor %x3 : tensor<8x4xf64, #CSC> 105 106 return 107 } 108} 109