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//===-- CUFDeviceFuncTransform.cpp ----------------------------------------===//
//
// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
// See https://llvm.org/LICENSE.txt for license information.
// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
//
//===----------------------------------------------------------------------===//
#include "flang/Optimizer/Builder/CUFCommon.h"
#include "flang/Optimizer/Builder/Todo.h"
#include "flang/Optimizer/Dialect/CUF/CUFOps.h"
#include "flang/Optimizer/Dialect/FIRAttr.h"
#include "flang/Optimizer/Dialect/FIRDialect.h"
#include "flang/Optimizer/Dialect/FIROpsSupport.h"
#include "flang/Optimizer/Support/InternalNames.h"
#include "flang/Optimizer/Transforms/Passes.h"
#include "mlir/Dialect/ControlFlow/IR/ControlFlowOps.h"
#include "mlir/Dialect/GPU/IR/GPUDialect.h"
#include "mlir/Dialect/Index/IR/IndexDialect.h"
#include "mlir/Dialect/Index/IR/IndexOps.h"
#include "mlir/Dialect/LLVMIR/LLVMDialect.h"
#include "mlir/Dialect/LLVMIR/NVVMDialect.h"
#include "mlir/Dialect/SCF/IR/SCF.h"
#include "mlir/IR/IRMapping.h"
#include "mlir/Pass/Pass.h"
#include "mlir/Transforms/RegionUtils.h"
#include "llvm/ADT/SetVector.h"
#include "llvm/ADT/StringSet.h"
namespace fir {
#define GEN_PASS_DEF_CUFDEVICEFUNCTRANSFORM
#include "flang/Optimizer/Transforms/Passes.h.inc"
} // namespace fir
using namespace mlir;
namespace {
class CUFDeviceFuncTransform
: public fir::impl::CUFDeviceFuncTransformBase<CUFDeviceFuncTransform> {
using CUFDeviceFuncTransformBase<
CUFDeviceFuncTransform>::CUFDeviceFuncTransformBase;
static gpu::GPUFuncOp createGPUFuncOp(mlir::func::FuncOp funcOp,
bool isGlobal, int computeCap) {
mlir::OpBuilder builder(funcOp.getContext());
mlir::Region &funcOpBody = funcOp.getBody();
SetVector<Value> operands;
for (mlir::Value operand : funcOp.getArguments())
operands.insert(operand);
llvm::SmallVector<mlir::Type> funcOperandTypes;
llvm::SmallVector<mlir::Type> funcResultTypes;
funcOperandTypes.reserve(funcOp.getArgumentTypes().size());
funcResultTypes.reserve(funcOp.getResultTypes().size());
for (mlir::Type opTy : funcOp.getArgumentTypes())
funcOperandTypes.push_back(opTy);
for (mlir::Type resTy : funcOp.getResultTypes())
funcResultTypes.push_back(resTy);
mlir::Location loc = funcOp.getLoc();
mlir::FunctionType type = mlir::FunctionType::get(
funcOp.getContext(), funcOperandTypes, funcResultTypes);
auto deviceFuncOp =
gpu::GPUFuncOp::create(builder, loc, funcOp.getName(), type,
mlir::TypeRange{}, mlir::TypeRange{});
if (isGlobal)
deviceFuncOp->setAttr(gpu::GPUDialect::getKernelFuncAttrName(),
builder.getUnitAttr());
mlir::Region &deviceFuncBody = deviceFuncOp.getBody();
mlir::Block &entryBlock = deviceFuncBody.front();
mlir::IRMapping map;
for (const auto &operand : enumerate(operands))
map.map(operand.value(), entryBlock.getArgument(operand.index()));
funcOpBody.cloneInto(&deviceFuncBody, map);
deviceFuncOp.walk([](func::ReturnOp op) {
mlir::OpBuilder replacer(op);
gpu::ReturnOp gpuReturnOp = gpu::ReturnOp::create(replacer, op.getLoc());
gpuReturnOp->setOperands(op.getOperands());
op.erase();
});
mlir::Block &funcOpEntry = funcOp.front();
mlir::Block *clonedFuncOpEntry = map.lookup(&funcOpEntry);
entryBlock.getOperations().splice(entryBlock.getOperations().end(),
clonedFuncOpEntry->getOperations());
clonedFuncOpEntry->erase();
auto launchBoundsAttr =
funcOp.getOperation()->getAttrOfType<cuf::LaunchBoundsAttr>(
cuf::getLaunchBoundsAttrName());
if (launchBoundsAttr) {
auto maxTPB = launchBoundsAttr.getMaxTPB().getInt();
auto maxntid =
builder.getDenseI32ArrayAttr({static_cast<int32_t>(maxTPB), 1, 1});
deviceFuncOp->setAttr(NVVM::NVVMDialect::getMaxntidAttrName(), maxntid);
deviceFuncOp->setAttr(NVVM::NVVMDialect::getMinctasmAttrName(),
launchBoundsAttr.getMinBPM());
if (computeCap >= 90 && launchBoundsAttr.getUpperBoundClusterSize())
deviceFuncOp->setAttr(NVVM::NVVMDialect::getClusterMaxBlocksAttrName(),
launchBoundsAttr.getUpperBoundClusterSize());
}
return deviceFuncOp;
}
static void createHostStub(mlir::func::FuncOp funcOp,
mlir::SymbolTable &symTab, mlir::ModuleOp mod) {
mlir::Location loc = funcOp.getLoc();
mlir::OpBuilder modBuilder(mod.getBodyRegion());
modBuilder.setInsertionPointToEnd(mod.getBody());
auto emptyStub = func::FuncOp::create(modBuilder, loc, funcOp.getName(),
funcOp.getFunctionType());
emptyStub.setVisibility(funcOp.getVisibility());
emptyStub->setAttrs(funcOp->getAttrs());
auto entryBlock = emptyStub.addEntryBlock();
modBuilder.setInsertionPointToEnd(entryBlock);
func::ReturnOp::create(modBuilder, loc);
symTab.erase(funcOp);
symTab.insert(emptyStub);
}
static bool isDeviceFunc(mlir::func::FuncOp funcOp) {
if (auto cudaProcAttr =
funcOp.getOperation()->getAttrOfType<cuf::ProcAttributeAttr>(
cuf::getProcAttrName()))
if (cudaProcAttr.getValue() == cuf::ProcAttribute::Device ||
cudaProcAttr.getValue() == cuf::ProcAttribute::Global ||
cudaProcAttr.getValue() == cuf::ProcAttribute::GridGlobal ||
cudaProcAttr.getValue() == cuf::ProcAttribute::HostDevice)
return true;
return false;
}
void runOnOperation() override {
// Working on Module operation because inserting/removing function from the
// module is not thread-safe.
ModuleOp mod = getOperation();
mlir::SymbolTable symbolTable(getOperation());
auto *ctx = getOperation().getContext();
mlir::OpBuilder builder(ctx);
gpu::GPUModuleOp gpuMod = cuf::getOrCreateGPUModule(mod, symbolTable);
mlir::SymbolTable gpuModSymTab(gpuMod);
llvm::SetVector<mlir::func::FuncOp> funcsToClone;
llvm::SetVector<mlir::func::FuncOp> deviceFuncs;
llvm::SetVector<mlir::func::FuncOp> keepInModule;
llvm::StringSet<> deviceFuncNames;
// Look for all function to migrate to the GPU module.
mod.walk([&](mlir::func::FuncOp op) {
if (isDeviceFunc(op)) {
deviceFuncs.insert(op);
deviceFuncNames.insert(op.getSymName());
}
});
auto processCallOp = [&](fir::CallOp op) {
if (op.getCallee()) {
auto func = symbolTable.lookup<mlir::func::FuncOp>(
op.getCallee()->getLeafReference());
if (deviceFuncs.count(func) == 0)
funcsToClone.insert(func);
}
};
// Gather all function called by device functions.
for (auto funcOp : deviceFuncs) {
funcOp.walk([&](fir::CallOp op) { processCallOp(op); });
funcOp.walk([&](fir::DispatchOp op) {
TODO(op.getLoc(), "type-bound procedure call with dynamic dispatch "
"in device procedure");
});
}
// Functions that are referenced in a derived-type binding table must be
// kept in the host module to avoid LLVM dialect verification errors.
for (auto globalOp : mod.getOps<fir::GlobalOp>()) {
if (globalOp.getName().contains(fir::kBindingTableSeparator)) {
globalOp.walk([&](fir::AddrOfOp addrOfOp) {
if (deviceFuncNames.contains(addrOfOp.getSymbol().getLeafReference()))
keepInModule.insert(
*llvm::find_if(deviceFuncs, [&](mlir::func::FuncOp f) {
return f.getSymName() ==
addrOfOp.getSymbol().getLeafReference();
}));
});
}
}
// Gather all functions called by CUF kernels.
mod.walk([&](cuf::KernelOp kernelOp) {
kernelOp.walk([&](fir::CallOp op) { processCallOp(op); });
kernelOp.walk([&](fir::DispatchOp op) {
TODO(op.getLoc(),
"type-bound procedure call with dynamic dispatch in cuf kernel");
});
});
for (auto funcOp : funcsToClone)
gpuModSymTab.insert(funcOp->clone());
for (auto funcOp : deviceFuncs) {
auto cudaProcAttr =
funcOp.getOperation()->getAttrOfType<cuf::ProcAttributeAttr>(
cuf::getProcAttrName());
auto isGlobal = cudaProcAttr.getValue() == cuf::ProcAttribute::Global ||
cudaProcAttr.getValue() == cuf::ProcAttribute::GridGlobal;
if (funcOp.isDeclaration()) {
mlir::Operation *clonedFuncOp = funcOp->clone();
if (isGlobal) {
clonedFuncOp->setAttr(gpu::GPUDialect::getKernelFuncAttrName(),
builder.getUnitAttr());
clonedFuncOp->removeAttr(cuf::getProcAttrName());
if (auto funcOp = mlir::dyn_cast<func::FuncOp>(clonedFuncOp))
funcOp.setNested();
}
gpuModSymTab.insert(clonedFuncOp);
} else {
gpu::GPUFuncOp deviceFuncOp =
createGPUFuncOp(funcOp, isGlobal, computeCap);
gpuModSymTab.insert(deviceFuncOp);
if (cudaProcAttr.getValue() != cuf::ProcAttribute::HostDevice) {
// If the function is a global, we need to keep the host side
// declaration for the kernel registration. Currently we just
// erase its body but in the future, the body should be rewritten
// to be able to launch CUDA Fortran kernel from C code.
if (isGlobal || keepInModule.contains(funcOp))
createHostStub(funcOp, symbolTable, mod);
else
funcOp.erase();
}
}
}
}
};
} // end anonymous namespace
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