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Avoid running forever by checking we are not reassociating an expression into the same form. Tested with @avoid_infinite_loops in nary-add.ll git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@237269 91177308-0d34-0410-b5e6-96231b3b80d8
258 lines
9.1 KiB
C++
258 lines
9.1 KiB
C++
//===- NaryReassociate.cpp - Reassociate n-ary expressions ----------------===//
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//
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// The LLVM Compiler Infrastructure
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//
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// This file is distributed under the University of Illinois Open Source
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// License. See LICENSE.TXT for details.
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//
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//===----------------------------------------------------------------------===//
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//
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// This pass reassociates n-ary add expressions and eliminates the redundancy
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// exposed by the reassociation.
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//
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// A motivating example:
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//
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// void foo(int a, int b) {
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// bar(a + b);
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// bar((a + 2) + b);
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// }
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//
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// An ideal compiler should reassociate (a + 2) + b to (a + b) + 2 and simplify
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// the above code to
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//
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// int t = a + b;
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// bar(t);
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// bar(t + 2);
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//
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// However, the Reassociate pass is unable to do that because it processes each
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// instruction individually and believes (a + 2) + b is the best form according
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// to its rank system.
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//
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// To address this limitation, NaryReassociate reassociates an expression in a
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// form that reuses existing instructions. As a result, NaryReassociate can
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// reassociate (a + 2) + b in the example to (a + b) + 2 because it detects that
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// (a + b) is computed before.
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//
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// NaryReassociate works as follows. For every instruction in the form of (a +
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// b) + c, it checks whether a + c or b + c is already computed by a dominating
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// instruction. If so, it then reassociates (a + b) + c into (a + c) + b or (b +
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// c) + a and removes the redundancy accordingly. To efficiently look up whether
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// an expression is computed before, we store each instruction seen and its SCEV
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// into an SCEV-to-instruction map.
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//
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// Although the algorithm pattern-matches only ternary additions, it
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// automatically handles many >3-ary expressions by walking through the function
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// in the depth-first order. For example, given
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//
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// (a + c) + d
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// ((a + b) + c) + d
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//
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// NaryReassociate first rewrites (a + b) + c to (a + c) + b, and then rewrites
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// ((a + c) + b) + d into ((a + c) + d) + b.
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//
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// Finally, the above dominator-based algorithm may need to be run multiple
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// iterations before emitting optimal code. One source of this need is that we
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// only split an operand when it is used only once. The above algorithm can
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// eliminate an instruction and decrease the usage count of its operands. As a
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// result, an instruction that previously had multiple uses may become a
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// single-use instruction and thus eligible for split consideration. For
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// example,
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//
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// ac = a + c
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// ab = a + b
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// abc = ab + c
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// ab2 = ab + b
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// ab2c = ab2 + c
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//
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// In the first iteration, we cannot reassociate abc to ac+b because ab is used
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// twice. However, we can reassociate ab2c to abc+b in the first iteration. As a
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// result, ab2 becomes dead and ab will be used only once in the second
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// iteration.
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//
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// Limitations and TODO items:
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//
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// 1) We only considers n-ary adds for now. This should be extended and
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// generalized.
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//
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// 2) Besides arithmetic operations, similar reassociation can be applied to
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// GEPs. For example, if
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// X = &arr[a]
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// dominates
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// Y = &arr[a + b]
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// we may rewrite Y into X + b.
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//
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//===----------------------------------------------------------------------===//
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#include "llvm/Analysis/ScalarEvolution.h"
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#include "llvm/Analysis/TargetLibraryInfo.h"
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#include "llvm/IR/Dominators.h"
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#include "llvm/IR/Module.h"
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#include "llvm/IR/PatternMatch.h"
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#include "llvm/Transforms/Scalar.h"
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#include "llvm/Transforms/Utils/Local.h"
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using namespace llvm;
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using namespace PatternMatch;
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#define DEBUG_TYPE "nary-reassociate"
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namespace {
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class NaryReassociate : public FunctionPass {
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public:
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static char ID;
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NaryReassociate(): FunctionPass(ID) {
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initializeNaryReassociatePass(*PassRegistry::getPassRegistry());
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}
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bool runOnFunction(Function &F) override;
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void getAnalysisUsage(AnalysisUsage &AU) const override {
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AU.addPreserved<DominatorTreeWrapperPass>();
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AU.addPreserved<ScalarEvolution>();
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AU.addPreserved<TargetLibraryInfoWrapperPass>();
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AU.addRequired<DominatorTreeWrapperPass>();
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AU.addRequired<ScalarEvolution>();
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AU.addRequired<TargetLibraryInfoWrapperPass>();
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AU.setPreservesCFG();
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}
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private:
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// Runs only one iteration of the dominator-based algorithm. See the header
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// comments for why we need multiple iterations.
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bool doOneIteration(Function &F);
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// Reasssociates I to a better form.
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Instruction *tryReassociateAdd(Instruction *I);
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// A helper function for tryReassociateAdd. LHS and RHS are explicitly passed.
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Instruction *tryReassociateAdd(Value *LHS, Value *RHS, Instruction *I);
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// Rewrites I to LHS + RHS if LHS is computed already.
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Instruction *tryReassociatedAdd(const SCEV *LHS, Value *RHS, Instruction *I);
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DominatorTree *DT;
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ScalarEvolution *SE;
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TargetLibraryInfo *TLI;
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// A lookup table quickly telling which instructions compute the given SCEV.
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// Note that there can be multiple instructions at different locations
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// computing to the same SCEV, so we map a SCEV to an instruction list. For
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// example,
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//
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// if (p1)
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// foo(a + b);
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// if (p2)
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// bar(a + b);
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DenseMap<const SCEV *, SmallVector<Instruction *, 2>> SeenExprs;
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};
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} // anonymous namespace
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char NaryReassociate::ID = 0;
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INITIALIZE_PASS_BEGIN(NaryReassociate, "nary-reassociate", "Nary reassociation",
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false, false)
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INITIALIZE_PASS_DEPENDENCY(DominatorTreeWrapperPass)
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INITIALIZE_PASS_DEPENDENCY(ScalarEvolution)
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INITIALIZE_PASS_DEPENDENCY(TargetLibraryInfoWrapperPass)
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INITIALIZE_PASS_END(NaryReassociate, "nary-reassociate", "Nary reassociation",
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false, false)
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FunctionPass *llvm::createNaryReassociatePass() {
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return new NaryReassociate();
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}
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bool NaryReassociate::runOnFunction(Function &F) {
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if (skipOptnoneFunction(F))
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return false;
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DT = &getAnalysis<DominatorTreeWrapperPass>().getDomTree();
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SE = &getAnalysis<ScalarEvolution>();
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TLI = &getAnalysis<TargetLibraryInfoWrapperPass>().getTLI();
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bool Changed = false, ChangedInThisIteration;
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do {
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ChangedInThisIteration = doOneIteration(F);
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Changed |= ChangedInThisIteration;
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} while (ChangedInThisIteration);
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return Changed;
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}
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bool NaryReassociate::doOneIteration(Function &F) {
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bool Changed = false;
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SeenExprs.clear();
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// Traverse the dominator tree in the depth-first order. This order makes sure
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// all bases of a candidate are in Candidates when we process it.
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for (auto Node = GraphTraits<DominatorTree *>::nodes_begin(DT);
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Node != GraphTraits<DominatorTree *>::nodes_end(DT); ++Node) {
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BasicBlock *BB = Node->getBlock();
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for (auto I = BB->begin(); I != BB->end(); ++I) {
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// Skip vector types which are not SCEVable.
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if (I->getOpcode() == Instruction::Add && !I->getType()->isVectorTy()) {
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if (Instruction *NewI = tryReassociateAdd(I)) {
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Changed = true;
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SE->forgetValue(I);
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I->replaceAllUsesWith(NewI);
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RecursivelyDeleteTriviallyDeadInstructions(I, TLI);
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I = NewI;
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}
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// We should add the rewritten instruction because tryReassociateAdd may
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// have invalidated the original one.
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SeenExprs[SE->getSCEV(I)].push_back(I);
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}
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}
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}
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return Changed;
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}
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Instruction *NaryReassociate::tryReassociateAdd(Instruction *I) {
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Value *LHS = I->getOperand(0), *RHS = I->getOperand(1);
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if (auto *NewI = tryReassociateAdd(LHS, RHS, I))
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return NewI;
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if (auto *NewI = tryReassociateAdd(RHS, LHS, I))
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return NewI;
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return nullptr;
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}
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Instruction *NaryReassociate::tryReassociateAdd(Value *LHS, Value *RHS,
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Instruction *I) {
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Value *A = nullptr, *B = nullptr;
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// To be conservative, we reassociate I only when it is the only user of A+B.
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if (LHS->hasOneUse() && match(LHS, m_Add(m_Value(A), m_Value(B)))) {
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// I = (A + B) + RHS
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// = (A + RHS) + B or (B + RHS) + A
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const SCEV *AExpr = SE->getSCEV(A), *BExpr = SE->getSCEV(B);
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const SCEV *RHSExpr = SE->getSCEV(RHS);
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if (BExpr != RHSExpr) {
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if (auto *NewI = tryReassociatedAdd(SE->getAddExpr(AExpr, RHSExpr), B, I))
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return NewI;
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}
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if (AExpr != RHSExpr) {
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if (auto *NewI = tryReassociatedAdd(SE->getAddExpr(BExpr, RHSExpr), A, I))
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return NewI;
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}
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}
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return nullptr;
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}
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Instruction *NaryReassociate::tryReassociatedAdd(const SCEV *LHSExpr,
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Value *RHS, Instruction *I) {
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auto Pos = SeenExprs.find(LHSExpr);
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// Bail out if LHSExpr is not previously seen.
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if (Pos == SeenExprs.end())
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return nullptr;
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auto &LHSCandidates = Pos->second;
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// Look for the closest dominator LHS of I that computes LHSExpr, and replace
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// I with LHS + RHS.
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//
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// Because we traverse the dominator tree in the pre-order, a
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// candidate that doesn't dominate the current instruction won't dominate any
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// future instruction either. Therefore, we pop it out of the stack. This
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// optimization makes the algorithm O(n).
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while (!LHSCandidates.empty()) {
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Instruction *LHS = LHSCandidates.back();
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if (DT->dominates(LHS, I)) {
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Instruction *NewI = BinaryOperator::CreateAdd(LHS, RHS, "", I);
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NewI->takeName(I);
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return NewI;
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}
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LHSCandidates.pop_back();
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}
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return nullptr;
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}
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