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//===- llvm/Analysis/LegacyDivergenceAnalysis.h - KernelDivergence Analysis -*- C++ -*-===//
// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
// See for license information.
// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
// The kernel divergence analysis is an LLVM pass which can be used to find out
// if a branch instruction in a GPU program (kernel) is divergent or not. It can help
// branch optimizations such as jump threading and loop unswitching to make
// better decisions.
#include "llvm/ADT/DenseSet.h"
#include "llvm/IR/Function.h"
#include "llvm/Pass.h"
#include "llvm/Analysis/DivergenceAnalysis.h"
namespace llvm {
class Value;
class GPUDivergenceAnalysis;
class LegacyDivergenceAnalysis : public FunctionPass {
static char ID;
LegacyDivergenceAnalysis() : FunctionPass(ID) {
void getAnalysisUsage(AnalysisUsage &AU) const override;
bool runOnFunction(Function &F) override;
// Print all divergent branches in the function.
void print(raw_ostream &OS, const Module *) const override;
// Returns true if V is divergent at its definition.
// Even if this function returns false, V may still be divergent when used
// in a different basic block.
bool isDivergent(const Value *V) const;
// Returns true if V is uniform/non-divergent.
// Even if this function returns true, V may still be divergent when used
// in a different basic block.
bool isUniform(const Value *V) const { return !isDivergent(V); }
// Keep the analysis results uptodate by removing an erased value.
void removeValue(const Value *V) { DivergentValues.erase(V); }
// Whether analysis should be performed by GPUDivergenceAnalysis.
bool shouldUseGPUDivergenceAnalysis(const Function &F) const;
// (optional) handle to new DivergenceAnalysis
std::unique_ptr<GPUDivergenceAnalysis> gpuDA;
// Stores all divergent values.
DenseSet<const Value *> DivergentValues;
} // End llvm namespace