diff --git a/flang/lib/Optimizer/CodeGen/CodeGen.cpp b/flang/lib/Optimizer/CodeGen/CodeGen.cpp index a746beae8d9c2..50603cb86e4a5 100644 --- a/flang/lib/Optimizer/CodeGen/CodeGen.cpp +++ b/flang/lib/Optimizer/CodeGen/CodeGen.cpp @@ -1847,6 +1847,9 @@ struct EmboxOpConversion : public EmboxCommonConversion { }; static bool isDeviceAllocation(mlir::Value val, mlir::Value adaptorVal) { + if (val.getDefiningOp() && + val.getDefiningOp()->getParentOfType()) + return false; // Check if the global symbol is in the device module. if (auto addr = mlir::dyn_cast_or_null(val.getDefiningOp())) if (auto gpuMod = diff --git a/flang/test/Fir/CUDA/cuda-code-gen.mlir b/flang/test/Fir/CUDA/cuda-code-gen.mlir index 632f8afebbb92..bbd3f9fbd351b 100644 --- a/flang/test/Fir/CUDA/cuda-code-gen.mlir +++ b/flang/test/Fir/CUDA/cuda-code-gen.mlir @@ -241,7 +241,7 @@ module attributes {gpu.container_module, dlti.dl_spec = #dlti.dl_spec<#dlti.dl_e gpu.launch_func @cuda_device_mod::@_QMm1Psub2 blocks in (%c1, %c1, %c1) threads in (%c64, %c1, %c1) dynamic_shared_memory_size %c0_i32 args(%9 : !fir.box>) {cuf.proc_attr = #cuf.cuda_proc} return } - gpu.module @cuda_device_mod [#nvvm.target] attributes {llvm.data_layout = "e-p:64:64:64-p3:32:32:32-i1:8:8-i8:8:8-i16:16:16-i32:32:32-i64:64:64-i128:128:128-f32:32:32-f64:64:64-v16:16:16-v32:32:32-v64:64:64-v128:128:128-n16:32:64"} { + gpu.module @cuda_device_mod { fir.global @_QMm1Eda {data_attr = #cuf.cuda} : !fir.box>> { %c0 = arith.constant 0 : index %0 = fir.zero_bits !fir.heap> @@ -256,3 +256,31 @@ module attributes {gpu.container_module, dlti.dl_spec = #dlti.dl_spec<#dlti.dl_e // CHECK-LABEL: llvm.func @_QQmain() // CHECK: llvm.call @_FortranACUFAllocDescriptor + +// ----- + +module attributes {gpu.container_module, dlti.dl_spec = #dlti.dl_spec<#dlti.dl_entry : vector<2xi64>>, #dlti.dl_entry : vector<2xi64>>, #dlti.dl_entry : vector<2xi64>>, #dlti.dl_entry, dense<64> : vector<4xi64>>, #dlti.dl_entry, dense<32> : vector<4xi64>>, #dlti.dl_entry, dense<32> : vector<4xi64>>, #dlti.dl_entry : vector<2xi64>>, #dlti.dl_entry : vector<2xi64>>, #dlti.dl_entry : vector<2xi64>>, #dlti.dl_entry : vector<2xi64>>, #dlti.dl_entry : vector<2xi64>>, #dlti.dl_entry : vector<2xi64>>, #dlti.dl_entry : vector<2xi64>>, #dlti.dl_entry : vector<4xi64>>, #dlti.dl_entry<"dlti.endianness", "little">, #dlti.dl_entry<"dlti.stack_alignment", 128 : i64>>} { + fir.global @_QMm1Eda {data_attr = #cuf.cuda} : !fir.box>> { + %c0 = arith.constant 0 : index + %0 = fir.zero_bits !fir.heap> + %1 = fircg.ext_embox %0(%c0, %c0) {allocator_idx = 2 : i32} : (!fir.heap>, index, index) -> !fir.box>> + fir.has_value %1 : !fir.box>> + } + gpu.module @cuda_device_mod { + fir.global @_QMm1Eda {data_attr = #cuf.cuda} : !fir.box>> { + %c0 = arith.constant 0 : index + %0 = fir.zero_bits !fir.heap> + %1 = fircg.ext_embox %0(%c0, %c0) {allocator_idx = 2 : i32} : (!fir.heap>, index, index) -> !fir.box>> + fir.has_value %1 : !fir.box>> + } + func.func @_QQxxx() { + %0 = fir.address_of(@_QMm1Eda) : !fir.ref>>> + %8 = fir.load %0 : !fir.ref>>> + return + } + } +} + +// CHECK-LABEL: llvm.func @_QQxxx() +// CHECK: llvm.alloca %{{.*}} x !llvm.struct<(ptr, i64, i32, i8, i8, i8, i8, array<2 x array<3 x i64>>)> {alignment = 8 : i64} : (i32) -> !llvm.ptr +// CHECK-NOT: llvm.call @_FortranACUFAllocDescriptor