1// RUN: mlir-opt %s -convert-linalg-to-loops -convert-vector-to-scf='full-unroll=true' -lower-affine -convert-scf-to-cf -convert-vector-to-llvm -finalize-memref-to-llvm -convert-func-to-llvm='use-bare-ptr-memref-call-conv=1' -convert-arith-to-llvm -reconcile-unrealized-casts |\ 2// RUN: mlir-translate --mlir-to-llvmir |\ 3// RUN: %lli --entry-function=entry --mattr="avx512f" --dlopen=%mlir_c_runner_utils |\ 4// RUN: FileCheck %s 5 6module { 7 8 // an array of 16 i32 of values [0..15] 9 llvm.mlir.global private @const16( 10 dense<[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]> : tensor<16 x i32>) 11 : !llvm.array<16 x i32> 12 13 llvm.func @entry() -> i32 { 14 %c0 = llvm.mlir.constant(0 : index) : i64 15 16 %1 = llvm.mlir.addressof @const16 : !llvm.ptr 17 %ptr = llvm.getelementptr %1[%c0, %c0] 18 : (!llvm.ptr, i64, i64) -> !llvm.ptr, !llvm.array<16 x i32> 19 20 // operand_attrs of *m operands need to be piped through to LLVM for 21 // verification to pass. 22 %v = llvm.inline_asm 23 asm_dialect = intel 24 operand_attrs = [{ elementtype = vector<16xi32> }] 25 "vmovdqu32 $0, $1", "=x,*m" %ptr 26 : (!llvm.ptr) -> vector<16xi32> 27 28 // CHECK: 0 29 %v0 = vector.extract %v[0]: i32 from vector<16xi32> 30 vector.print %v0 : i32 31 32 // CHECK: 9 33 %v9 = vector.extract %v[9]: i32 from vector<16xi32> 34 vector.print %v9 : i32 35 36 %i0 = arith.constant 0 : i32 37 llvm.return %i0 : i32 38 } 39} 40 41