[flang][cuda] Adding support for registration of boxes (#114323)
Needed to take into account that `fir::getTypeSizeAndAlignmentOrCrash`
does not work with box types but requires the `fir::LLVMTypeConverter`
GitOrigin-RevId: 423f35410a217c39fb429d49193871a42cf49e2c
diff --git a/lib/Optimizer/Transforms/CUFAddConstructor.cpp b/lib/Optimizer/Transforms/CUFAddConstructor.cpp
index 7cdb2f7..dd20412 100644
--- a/lib/Optimizer/Transforms/CUFAddConstructor.cpp
+++ b/lib/Optimizer/Transforms/CUFAddConstructor.cpp
@@ -11,11 +11,13 @@
#include "flang/Optimizer/Builder/Runtime/RTBuilder.h"
#include "flang/Optimizer/Builder/Todo.h"
#include "flang/Optimizer/CodeGen/Target.h"
+#include "flang/Optimizer/CodeGen/TypeConverter.h"
#include "flang/Optimizer/Dialect/CUF/CUFOps.h"
#include "flang/Optimizer/Dialect/FIRAttr.h"
#include "flang/Optimizer/Dialect/FIRDialect.h"
#include "flang/Optimizer/Dialect/FIROps.h"
#include "flang/Optimizer/Dialect/FIROpsSupport.h"
+#include "flang/Optimizer/Dialect/FIRType.h"
#include "flang/Optimizer/Support/DataLayout.h"
#include "flang/Optimizer/Transforms/CUFCommon.h"
#include "flang/Runtime/CUDA/registration.h"
@@ -84,6 +86,8 @@
auto registeredMod = builder.create<cuf::RegisterModuleOp>(
loc, llvmPtrTy, mlir::SymbolRefAttr::get(ctx, gpuMod.getName()));
+ fir::LLVMTypeConverter typeConverter(mod, /*applyTBAA=*/false,
+ /*forceUnifiedTBAATree=*/false, *dl);
// Register kernels
for (auto func : gpuMod.getOps<mlir::gpu::GPUFuncOp>()) {
if (func.isKernel()) {
@@ -115,17 +119,25 @@
fir::factory::createStringLiteral(builder, loc, gblNameStr));
// Global variable size
- auto sizeAndAlign = fir::getTypeSizeAndAlignmentOrCrash(
- loc, globalOp.getType(), *dl, kindMap);
- auto size =
- builder.createIntegerConstant(loc, idxTy, sizeAndAlign.first);
+ std::optional<uint64_t> size;
+ if (auto boxTy =
+ mlir::dyn_cast<fir::BaseBoxType>(globalOp.getType())) {
+ mlir::Type structTy = typeConverter.convertBoxTypeAsStruct(boxTy);
+ size = dl->getTypeSizeInBits(structTy) / 8;
+ }
+ if (!size) {
+ size = fir::getTypeSizeAndAlignmentOrCrash(loc, globalOp.getType(),
+ *dl, kindMap)
+ .first;
+ }
+ auto sizeVal = builder.createIntegerConstant(loc, idxTy, *size);
// Global variable address
mlir::Value addr = builder.create<fir::AddrOfOp>(
loc, globalOp.resultType(), globalOp.getSymbol());
llvm::SmallVector<mlir::Value> args{fir::runtime::createArguments(
- builder, loc, fTy, registeredMod, addr, gblName, size)};
+ builder, loc, fTy, registeredMod, addr, gblName, sizeVal)};
builder.create<fir::CallOp>(loc, func, args);
} break;
case cuf::DataAttribute::Managed:
diff --git a/test/Fir/CUDA/cuda-constructor-2.f90 b/test/Fir/CUDA/cuda-constructor-2.f90
index 378dabb..99386ab 100644
--- a/test/Fir/CUDA/cuda-constructor-2.f90
+++ b/test/Fir/CUDA/cuda-constructor-2.f90
@@ -3,6 +3,12 @@
module attributes {dlti.dl_spec = #dlti.dl_spec<#dlti.dl_entry<!llvm.ptr, 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<f80, dense<128> : 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<i128, dense<128> : vector<2xi64>>, #dlti.dl_entry<i8, dense<8> : vector<2xi64>>, #dlti.dl_entry<!llvm.ptr<272>, dense<64> : vector<4xi64>>, #dlti.dl_entry<i64, dense<64> : vector<2xi64>>, #dlti.dl_entry<i1, dense<8> : vector<2xi64>>, #dlti.dl_entry<"dlti.endianness", "little">, #dlti.dl_entry<"dlti.stack_alignment", 128 : i64>>, fir.defaultkind = "a1c4d8i4l4r4", fir.kindmap = "", gpu.container_module, llvm.data_layout = "e-m:e-p270:32:32-p271:32:32-p272:64:64-i64:64-i128:128-f80:128-n8:16:32:64-S128", llvm.ident = "flang version 20.0.0 (https://github.com/llvm/llvm-project.git cae351f3453a0a26ec8eb2ddaf773c24a29d929e)", llvm.target_triple = "x86_64-unknown-linux-gnu"} {
fir.global @_QMmtestsEn(dense<[3, 4, 5, 6, 7]> : tensor<5xi32>) {data_attr = #cuf.cuda<device>} : !fir.array<5xi32>
+ fir.global @_QMmtestsEndev {data_attr = #cuf.cuda<device>} : !fir.box<!fir.heap<!fir.array<?xi32>>> {
+ %c0 = arith.constant 0 : index
+ %0 = fir.zero_bits !fir.heap<!fir.array<?xi32>>
+ %1 = fircg.ext_embox %0(%c0) {allocator_idx = 2 : i32} : (!fir.heap<!fir.array<?xi32>>, index) -> !fir.box<!fir.heap<!fir.array<?xi32>>>
+ fir.has_value %1 : !fir.box<!fir.heap<!fir.array<?xi32>>>
+ }
gpu.module @cuda_device_mod [#nvvm.target] {
}
@@ -18,5 +24,9 @@
// CHECK-DAG: %[[VAR_ADDR2:.*]] = fir.convert %[[VAR_ADDR]] : (!fir.ref<!fir.array<5xi32>>) -> !fir.ref<i8>
// CHECK-DAG: %[[VAR_NAME2:.*]] = fir.convert %[[VAR_NAME]] : (!fir.ref<!fir.char<1,12>>) -> !fir.ref<i8>
// CHECK-DAG: %[[CST:.*]] = arith.constant 20 : index
-// CHECK-DAG %[[CST2:.*]] = fir.convert %[[CST]] : (index) -> i64
-// CHECK fir.call @_FortranACUFRegisterVariable(%[[MODULE2]], %[[VAR_ADDR2]], %[[VAR_NAME2]], %[[CST2]]) : (!fir.ref<!fir.llvm_ptr<i8>>, !fir.ref<i8>, !fir.ref<i8>, i64) -> none
+// CHECK-DAG: %[[CST2:.*]] = fir.convert %[[CST]] : (index) -> i64
+// CHECK-DAG: fir.call @_FortranACUFRegisterVariable(%[[MODULE2]], %[[VAR_ADDR2]], %[[VAR_NAME2]], %[[CST2]]) : (!fir.ref<!fir.llvm_ptr<i8>>, !fir.ref<i8>, !fir.ref<i8>, i64) -> none
+// CHECK-DAG: %[[BOX:.*]] = fir.address_of(@_QMmtestsEndev) : !fir.ref<!fir.box<!fir.heap<!fir.array<?xi32>>>>
+// CHECK-DAG: %[[BOXREF:.*]] = fir.convert %[[BOX]] : (!fir.ref<!fir.box<!fir.heap<!fir.array<?xi32>>>>) -> !fir.ref<i8>
+// CHECK-DAG: fir.call @_FortranACUFRegisterVariable(%[[MODULE:.*]], %[[BOXREF]], %{{.*}}, %{{.*}})
+//
diff --git a/test/Fir/CUDA/cuda-register-func.fir b/test/Fir/CUDA/cuda-register-func.fir
index 6b0cbfd..25ab8dd 100644
--- a/test/Fir/CUDA/cuda-register-func.fir
+++ b/test/Fir/CUDA/cuda-register-func.fir
@@ -1,6 +1,6 @@
// RUN: fir-opt --cuf-add-constructor %s | FileCheck %s
-module attributes {gpu.container_module} {
+module attributes {dlti.dl_spec = #dlti.dl_spec<#dlti.dl_entry<!llvm.ptr, 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<f80, dense<128> : 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<i128, dense<128> : vector<2xi64>>, #dlti.dl_entry<i8, dense<8> : vector<2xi64>>, #dlti.dl_entry<!llvm.ptr<272>, dense<64> : vector<4xi64>>, #dlti.dl_entry<i64, dense<64> : vector<2xi64>>, #dlti.dl_entry<i1, dense<8> : vector<2xi64>>, #dlti.dl_entry<"dlti.endianness", "little">, #dlti.dl_entry<"dlti.stack_alignment", 128 : i64>>, fir.defaultkind = "a1c4d8i4l4r4", fir.kindmap = "", gpu.container_module, llvm.data_layout = "e-m:e-p270:32:32-p271:32:32-p272:64:64-i64:64-i128:128-f80:128-n8:16:32:64-S128", llvm.ident = "flang version 20.0.0 (https://github.com/llvm/llvm-project.git cae351f3453a0a26ec8eb2ddaf773c24a29d929e)", llvm.target_triple = "x86_64-unknown-linux-gnu"} {
gpu.module @cuda_device_mod {
gpu.func @_QPsub_device1() kernel {
gpu.return
