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1// NOTE: this test requires gpu-sm802//3// DEFINE: %{compile} = mlir-opt %s \4// DEFINE: --sparsifier="enable-gpu-libgen gpu-triple=nvptx64-nvidia-cuda gpu-chip=sm_80 gpu-features=+ptx71 gpu-format=%gpu_compilation_format5// DEFINE: %{run} = mlir-runner \6// DEFINE: --shared-libs=%mlir_cuda_runtime \7// DEFINE: --shared-libs=%mlir_c_runner_utils \8// DEFINE: --e main --entry-point-result=void \9// DEFINE: | FileCheck %s10//11// with RT lib:12//13// RUN: %{compile} enable-runtime-library=true" | %{run}14//15// without RT lib:16//17// RUN: %{compile} enable-runtime-library=false" | %{run}18 19#CSR = #sparse_tensor.encoding<{20 map = (d0, d1) -> (d0 : dense, d1 : compressed),21 posWidth = 32,22 crdWidth = 3223}>24 25module {26 llvm.func @mgpuCreateSparseEnv()27 llvm.func @mgpuDestroySparseEnv()28 29 // Computes C = A x B with A,B,C sparse CSR.30 func.func @matmulCSR(%A: tensor<8x8xf32, #CSR>,31 %B: tensor<8x8xf32, #CSR>) -> tensor<8x8xf32, #CSR> {32 %init = tensor.empty() : tensor<8x8xf32, #CSR>33 %C = linalg.matmul34 ins(%A, %B: tensor<8x8xf32, #CSR>,35 tensor<8x8xf32, #CSR>)36 outs(%init: tensor<8x8xf32, #CSR>) -> tensor<8x8xf32, #CSR>37 return %C: tensor<8x8xf32, #CSR>38 }39 40 //41 // Main driver.42 //43 func.func @main() {44 llvm.call @mgpuCreateSparseEnv(): () -> ()45 46 %c0 = arith.constant 0 : index47 %f0 = arith.constant 0.0 : f3248 49 %t = arith.constant dense<[50 [ 1.0, 0.0, 2.0, 0.0, 0.0, 0.0, 0.0, 3.0],51 [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],52 [ 0.0, 0.0, 4.0, 0.0, 0.0, 0.0, 0.0, 0.0],53 [ 0.0, 0.0, 0.0, 5.0, 0.0, 0.0, 0.0, 0.0],54 [ 0.0, 0.0, 0.0, 0.0, 6.0, 0.0, 0.0, 0.0],55 [ 0.0, 7.0, 8.0, 0.0, 0.0, 0.0, 0.0, 9.0],56 [ 0.0, 0.0, 10.0, 0.0, 0.0, 0.0, 11.0, 12.0],57 [ 0.0, 13.0, 14.0, 0.0, 0.0, 0.0, 15.0, 16.0]58 ]> : tensor<8x8xf32>59 %Acsr = sparse_tensor.convert %t : tensor<8x8xf32> to tensor<8x8xf32, #CSR>60 61 %Ccsr = call @matmulCSR(%Acsr, %Acsr) : (tensor<8x8xf32, #CSR>,62 tensor<8x8xf32, #CSR>) -> tensor<8x8xf32, #CSR>63 64 //65 // Verify computed result.66 //67 // CHECK: ---- Sparse Tensor ----68 // CHECK-NEXT: nse = 2069 // CHECK-NEXT: dim = ( 8, 8 )70 // CHECK-NEXT: lvl = ( 8, 8 )71 // CHECK-NEXT: pos[1] : ( 0, 5, 5, 6, 7, 8, 12, 16, 20 )72 // CHECK-NEXT: crd[1] : ( 0, 1, 2, 6, 7, 2, 3, 4, 1, 2, 6, 7, 1, 2, 6, 7, 1, 2, 6, 7 )73 // CHECK-NEXT: values : ( 1, 39, 52, 45, 51, 16, 25, 36, 117, 158, 135, 144, 156, 318, 301, 324, 208, 430, 405, 436 )74 // CHECK-NEXT: ----75 sparse_tensor.print %Ccsr : tensor<8x8xf32, #CSR>76 77 llvm.call @mgpuDestroySparseEnv(): () -> ()78 return79 }80}81