[flang][cuda] Do not use managed memory inside gpu module #160730
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@llvm/pr-subscribers-flang-fir-hlfir Author: Valentin Clement (バレンタイン クレメン) (clementval) ChangesDo not issue call to _FortranACUFAllocDescriptor inside gpu module. Full diff: https://github.com/llvm/llvm-project/pull/160730.diff 2 Files Affected:
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<fir::EmboxOp> {
};
static bool isDeviceAllocation(mlir::Value val, mlir::Value adaptorVal) {
+ if (val.getDefiningOp() &&
+ val.getDefiningOp()->getParentOfType<mlir::gpu::GPUModuleOp>())
+ return false;
// Check if the global symbol is in the device module.
if (auto addr = mlir::dyn_cast_or_null<fir::AddrOfOp>(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..8114f20e3f601 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<!fir.array<?x?xf32>>) {cuf.proc_attr = #cuf.cuda_proc<global>}
return
}
- gpu.module @cuda_device_mod [#nvvm.target<chip = "sm_90", features = "+ptx75", link = ["/proj/ng/Linux_x86_64/dev/compilers/lib/nvvm-next/12/libdevice_nvhpc_cuda_builtin_intrinsics_runtime.10.bc", "/proj/ng/Linux_x86_64/dev/compilers/lib/nvvm-next/12/libdevice_nvhpc_utils_runtime.10.bc", "/proj/ng/Linux_x86_64/dev/compilers/lib/nvvm-next/12/libdevice_nvhpc_cuda_cpp_builtins.10.bc", "/proj/ng/Linux_x86_64/dev/compilers/lib/nvvm-next/12/libdevice_nvhpc_cuda_runtime.10.bc", "/proj/ng/Linux_x86_64/dev/compilers/lib/nvvm-next/12//libdevice_nvhpc_cuda_runtime_builtins_cc90.10.bc", "/proj/ng/Linux_x86_64/dev/cuda/12.9/nvvm/libdevice/libdevice.10.bc"]>] 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<device>} : !fir.box<!fir.heap<!fir.array<?x?xf32>>> {
%c0 = arith.constant 0 : index
%0 = fir.zero_bits !fir.heap<!fir.array<?x?xf32>>
@@ -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<f80, dense<128> : vector<2xi64>>, #dlti.dl_entry<i128, dense<128> : vector<2xi64>>, #dlti.dl_entry<i64, dense<64> : vector<2xi64>>, #dlti.dl_entry<!llvm.ptr<272>, dense<64> : vector<4xi64>>, #dlti.dl_entry<!llvm.ptr<271>, dense<32> : vector<4xi64>>, #dlti.dl_entry<!llvm.ptr<270>, dense<32> : vector<4xi64>>, #dlti.dl_entry<f128, dense<128> : vector<2xi64>>, #dlti.dl_entry<f64, dense<64> : vector<2xi64>>, #dlti.dl_entry<f16, dense<16> : vector<2xi64>>, #dlti.dl_entry<i32, dense<32> : vector<2xi64>>, #dlti.dl_entry<i16, dense<16> : vector<2xi64>>, #dlti.dl_entry<i8, dense<8> : vector<2xi64>>, #dlti.dl_entry<i1, dense<8> : vector<2xi64>>, #dlti.dl_entry<!llvm.ptr, dense<64> : vector<4xi64>>, #dlti.dl_entry<"dlti.endianness", "little">, #dlti.dl_entry<"dlti.stack_alignment", 128 : i64>>} {
+ fir.global @_QMm1Eda {data_attr = #cuf.cuda<device>} : !fir.box<!fir.heap<!fir.array<?x?xf32>>> {
+ %c0 = arith.constant 0 : index
+ %0 = fir.zero_bits !fir.heap<!fir.array<?x?xf32>>
+ %1 = fircg.ext_embox %0(%c0, %c0) {allocator_idx = 2 : i32} : (!fir.heap<!fir.array<?x?xf32>>, index, index) -> !fir.box<!fir.heap<!fir.array<?x?xf32>>>
+ fir.has_value %1 : !fir.box<!fir.heap<!fir.array<?x?xf32>>>
+ }
+ gpu.module @cuda_device_mod {
+ fir.global @_QMm1Eda {data_attr = #cuf.cuda<device>} : !fir.box<!fir.heap<!fir.array<?x?xf32>>> {
+ %c0 = arith.constant 0 : index
+ %0 = fir.zero_bits !fir.heap<!fir.array<?x?xf32>>
+ %1 = fircg.ext_embox %0(%c0, %c0) {allocator_idx = 2 : i32} : (!fir.heap<!fir.array<?x?xf32>>, index, index) -> !fir.box<!fir.heap<!fir.array<?x?xf32>>>
+ fir.has_value %1 : !fir.box<!fir.heap<!fir.array<?x?xf32>>>
+ }
+ func.func @_QQxxx() {
+ %0 = fir.address_of(@_QMm1Eda) : !fir.ref<!fir.box<!fir.heap<!fir.array<?x?xf32>>>>
+ %8 = fir.load %0 : !fir.ref<!fir.box<!fir.heap<!fir.array<?x?xf32>>>>
+ return
+ }
+ }
+}
+
+// CHECK-LABEL: func.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
|
|
@llvm/pr-subscribers-flang-codegen Author: Valentin Clement (バレンタイン クレメン) (clementval) ChangesDo not issue call to _FortranACUFAllocDescriptor inside gpu module. Full diff: https://github.com/llvm/llvm-project/pull/160730.diff 2 Files Affected:
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<fir::EmboxOp> {
};
static bool isDeviceAllocation(mlir::Value val, mlir::Value adaptorVal) {
+ if (val.getDefiningOp() &&
+ val.getDefiningOp()->getParentOfType<mlir::gpu::GPUModuleOp>())
+ return false;
// Check if the global symbol is in the device module.
if (auto addr = mlir::dyn_cast_or_null<fir::AddrOfOp>(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..8114f20e3f601 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<!fir.array<?x?xf32>>) {cuf.proc_attr = #cuf.cuda_proc<global>}
return
}
- gpu.module @cuda_device_mod [#nvvm.target<chip = "sm_90", features = "+ptx75", link = ["/proj/ng/Linux_x86_64/dev/compilers/lib/nvvm-next/12/libdevice_nvhpc_cuda_builtin_intrinsics_runtime.10.bc", "/proj/ng/Linux_x86_64/dev/compilers/lib/nvvm-next/12/libdevice_nvhpc_utils_runtime.10.bc", "/proj/ng/Linux_x86_64/dev/compilers/lib/nvvm-next/12/libdevice_nvhpc_cuda_cpp_builtins.10.bc", "/proj/ng/Linux_x86_64/dev/compilers/lib/nvvm-next/12/libdevice_nvhpc_cuda_runtime.10.bc", "/proj/ng/Linux_x86_64/dev/compilers/lib/nvvm-next/12//libdevice_nvhpc_cuda_runtime_builtins_cc90.10.bc", "/proj/ng/Linux_x86_64/dev/cuda/12.9/nvvm/libdevice/libdevice.10.bc"]>] 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<device>} : !fir.box<!fir.heap<!fir.array<?x?xf32>>> {
%c0 = arith.constant 0 : index
%0 = fir.zero_bits !fir.heap<!fir.array<?x?xf32>>
@@ -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<f80, dense<128> : vector<2xi64>>, #dlti.dl_entry<i128, dense<128> : vector<2xi64>>, #dlti.dl_entry<i64, dense<64> : vector<2xi64>>, #dlti.dl_entry<!llvm.ptr<272>, dense<64> : vector<4xi64>>, #dlti.dl_entry<!llvm.ptr<271>, dense<32> : vector<4xi64>>, #dlti.dl_entry<!llvm.ptr<270>, dense<32> : vector<4xi64>>, #dlti.dl_entry<f128, dense<128> : vector<2xi64>>, #dlti.dl_entry<f64, dense<64> : vector<2xi64>>, #dlti.dl_entry<f16, dense<16> : vector<2xi64>>, #dlti.dl_entry<i32, dense<32> : vector<2xi64>>, #dlti.dl_entry<i16, dense<16> : vector<2xi64>>, #dlti.dl_entry<i8, dense<8> : vector<2xi64>>, #dlti.dl_entry<i1, dense<8> : vector<2xi64>>, #dlti.dl_entry<!llvm.ptr, dense<64> : vector<4xi64>>, #dlti.dl_entry<"dlti.endianness", "little">, #dlti.dl_entry<"dlti.stack_alignment", 128 : i64>>} {
+ fir.global @_QMm1Eda {data_attr = #cuf.cuda<device>} : !fir.box<!fir.heap<!fir.array<?x?xf32>>> {
+ %c0 = arith.constant 0 : index
+ %0 = fir.zero_bits !fir.heap<!fir.array<?x?xf32>>
+ %1 = fircg.ext_embox %0(%c0, %c0) {allocator_idx = 2 : i32} : (!fir.heap<!fir.array<?x?xf32>>, index, index) -> !fir.box<!fir.heap<!fir.array<?x?xf32>>>
+ fir.has_value %1 : !fir.box<!fir.heap<!fir.array<?x?xf32>>>
+ }
+ gpu.module @cuda_device_mod {
+ fir.global @_QMm1Eda {data_attr = #cuf.cuda<device>} : !fir.box<!fir.heap<!fir.array<?x?xf32>>> {
+ %c0 = arith.constant 0 : index
+ %0 = fir.zero_bits !fir.heap<!fir.array<?x?xf32>>
+ %1 = fircg.ext_embox %0(%c0, %c0) {allocator_idx = 2 : i32} : (!fir.heap<!fir.array<?x?xf32>>, index, index) -> !fir.box<!fir.heap<!fir.array<?x?xf32>>>
+ fir.has_value %1 : !fir.box<!fir.heap<!fir.array<?x?xf32>>>
+ }
+ func.func @_QQxxx() {
+ %0 = fir.address_of(@_QMm1Eda) : !fir.ref<!fir.box<!fir.heap<!fir.array<?x?xf32>>>>
+ %8 = fir.load %0 : !fir.ref<!fir.box<!fir.heap<!fir.array<?x?xf32>>>>
+ return
+ }
+ }
+}
+
+// CHECK-LABEL: func.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
|
wangzpgi
approved these changes
Sep 25, 2025
mahesh-attarde
pushed a commit
to mahesh-attarde/llvm-project
that referenced
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Oct 3, 2025
Do not issue call to _FortranACUFAllocDescriptor inside gpu module.
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Do not issue call to _FortranACUFAllocDescriptor inside gpu module.