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This also implements some new features for the indvars pass, including linear function test replacement, exit value substitution, and it works with a much more general class of induction variables and loops. git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@12620 91177308-0d34-0410-b5e6-96231b3b80d8
421 lines
17 KiB
C++
421 lines
17 KiB
C++
//===- IndVarSimplify.cpp - Induction Variable Elimination ----------------===//
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//
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// The LLVM Compiler Infrastructure
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//
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// This file was developed by the LLVM research group and is distributed under
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// the University of Illinois Open Source License. See LICENSE.TXT for details.
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//
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//===----------------------------------------------------------------------===//
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//
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// This transformation analyzes and transforms the induction variables (and
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// computations derived from them) into simpler forms suitable for subsequent
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// analysis and transformation.
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//
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// This transformation make the following changes to each loop with an
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// identifiable induction variable:
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// 1. All loops are transformed to have a SINGLE canonical induction variable
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// which starts at zero and steps by one.
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// 2. The canonical induction variable is guaranteed to be the first PHI node
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// in the loop header block.
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// 3. Any pointer arithmetic recurrences are raised to use array subscripts.
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//
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// If the trip count of a loop is computable, this pass also makes the following
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// changes:
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// 1. The exit condition for the loop is canonicalized to compare the
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// induction value against the exit value. This turns loops like:
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// 'for (i = 7; i*i < 1000; ++i)' into 'for (i = 0; i != 25; ++i)'
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// 2. Any use outside of the loop of an expression derived from the indvar
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// is changed to compute the derived value outside of the loop, eliminating
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// the dependence on the exit value of the induction variable. If the only
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// purpose of the loop is to compute the exit value of some derived
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// expression, this transformation will make the loop dead.
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//
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// This transformation should be followed by strength reduction after all of the
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// desired loop transformations have been performed. Additionally, on targets
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// where it is profitable, the loop could be transformed to count down to zero
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// (the "do loop" optimization).
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//
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//===----------------------------------------------------------------------===//
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#include "llvm/Transforms/Scalar.h"
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#include "llvm/BasicBlock.h"
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#include "llvm/Constant.h"
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#include "llvm/Instructions.h"
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#include "llvm/Type.h"
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#include "llvm/Analysis/ScalarEvolution.h"
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#include "llvm/Analysis/LoopInfo.h"
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#include "llvm/Support/CFG.h"
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#include "llvm/Transforms/Utils/Local.h"
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#include "Support/CommandLine.h"
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#include "Support/Statistic.h"
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using namespace llvm;
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namespace {
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Statistic<> NumRemoved ("indvars", "Number of aux indvars removed");
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Statistic<> NumPointer ("indvars", "Number of pointer indvars promoted");
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Statistic<> NumInserted("indvars", "Number of canonical indvars added");
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Statistic<> NumReplaced("indvars", "Number of exit values replaced");
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Statistic<> NumLFTR ("indvars", "Number of loop exit tests replaced");
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class IndVarSimplify : public FunctionPass {
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LoopInfo *LI;
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ScalarEvolution *SE;
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bool Changed;
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public:
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virtual bool runOnFunction(Function &) {
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LI = &getAnalysis<LoopInfo>();
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SE = &getAnalysis<ScalarEvolution>();
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Changed = false;
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// Induction Variables live in the header nodes of loops
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for (LoopInfo::iterator I = LI->begin(), E = LI->end(); I != E; ++I)
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runOnLoop(*I);
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return Changed;
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}
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virtual void getAnalysisUsage(AnalysisUsage &AU) const {
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AU.addRequiredID(LoopSimplifyID);
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AU.addRequired<ScalarEvolution>();
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AU.addRequired<LoopInfo>();
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AU.addPreservedID(LoopSimplifyID);
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AU.setPreservesCFG();
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}
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private:
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void runOnLoop(Loop *L);
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void EliminatePointerRecurrence(PHINode *PN, BasicBlock *Preheader,
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std::set<Instruction*> &DeadInsts);
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void LinearFunctionTestReplace(Loop *L, SCEV *IterationCount,
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Value *IndVar, ScalarEvolutionRewriter &RW);
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void RewriteLoopExitValues(Loop *L);
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void DeleteTriviallyDeadInstructions(std::set<Instruction*> &Insts);
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};
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RegisterOpt<IndVarSimplify> X("indvars", "Canonicalize Induction Variables");
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}
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Pass *llvm::createIndVarSimplifyPass() {
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return new IndVarSimplify();
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}
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/// DeleteTriviallyDeadInstructions - If any of the instructions is the
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/// specified set are trivially dead, delete them and see if this makes any of
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/// their operands subsequently dead.
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void IndVarSimplify::
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DeleteTriviallyDeadInstructions(std::set<Instruction*> &Insts) {
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while (!Insts.empty()) {
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Instruction *I = *Insts.begin();
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Insts.erase(Insts.begin());
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if (isInstructionTriviallyDead(I)) {
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for (unsigned i = 0, e = I->getNumOperands(); i != e; ++i)
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if (Instruction *U = dyn_cast<Instruction>(I->getOperand(i)))
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Insts.insert(U);
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SE->deleteInstructionFromRecords(I);
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I->getParent()->getInstList().erase(I);
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Changed = true;
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}
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}
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}
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/// EliminatePointerRecurrence - Check to see if this is a trivial GEP pointer
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/// recurrence. If so, change it into an integer recurrence, permitting
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/// analysis by the SCEV routines.
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void IndVarSimplify::EliminatePointerRecurrence(PHINode *PN,
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BasicBlock *Preheader,
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std::set<Instruction*> &DeadInsts) {
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assert(PN->getNumIncomingValues() == 2 && "Noncanonicalized loop!");
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unsigned PreheaderIdx = PN->getBasicBlockIndex(Preheader);
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unsigned BackedgeIdx = PreheaderIdx^1;
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if (GetElementPtrInst *GEPI =
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dyn_cast<GetElementPtrInst>(PN->getIncomingValue(BackedgeIdx)))
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if (GEPI->getOperand(0) == PN) {
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assert(GEPI->getNumOperands() == 2 && "GEP types must mismatch!");
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// Okay, we found a pointer recurrence. Transform this pointer
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// recurrence into an integer recurrence. Compute the value that gets
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// added to the pointer at every iteration.
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Value *AddedVal = GEPI->getOperand(1);
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// Insert a new integer PHI node into the top of the block.
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PHINode *NewPhi = new PHINode(AddedVal->getType(),
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PN->getName()+".rec", PN);
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NewPhi->addIncoming(Constant::getNullValue(NewPhi->getType()),
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Preheader);
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// Create the new add instruction.
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Value *NewAdd = BinaryOperator::create(Instruction::Add, NewPhi,
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AddedVal,
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GEPI->getName()+".rec", GEPI);
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NewPhi->addIncoming(NewAdd, PN->getIncomingBlock(BackedgeIdx));
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// Update the existing GEP to use the recurrence.
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GEPI->setOperand(0, PN->getIncomingValue(PreheaderIdx));
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// Update the GEP to use the new recurrence we just inserted.
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GEPI->setOperand(1, NewAdd);
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// Finally, if there are any other users of the PHI node, we must
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// insert a new GEP instruction that uses the pre-incremented version
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// of the induction amount.
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if (!PN->use_empty()) {
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BasicBlock::iterator InsertPos = PN; ++InsertPos;
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while (isa<PHINode>(InsertPos)) ++InsertPos;
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std::string Name = PN->getName(); PN->setName("");
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Value *PreInc =
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new GetElementPtrInst(PN->getIncomingValue(PreheaderIdx),
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std::vector<Value*>(1, NewPhi), Name,
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InsertPos);
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PN->replaceAllUsesWith(PreInc);
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}
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// Delete the old PHI for sure, and the GEP if its otherwise unused.
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DeadInsts.insert(PN);
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++NumPointer;
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Changed = true;
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}
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}
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/// LinearFunctionTestReplace - This method rewrites the exit condition of the
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/// loop to be a canonical != comparison against the loop induction variable.
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/// This pass is able to rewrite the exit tests of any loop where the SCEV
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/// analysis can determine the trip count of the loop, which is actually a much
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/// broader range than just linear tests.
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void IndVarSimplify::LinearFunctionTestReplace(Loop *L, SCEV *IterationCount,
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Value *IndVar,
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ScalarEvolutionRewriter &RW) {
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// Find the exit block for the loop. We can currently only handle loops with
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// a single exit.
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if (L->getExitBlocks().size() != 1) return;
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BasicBlock *ExitBlock = L->getExitBlocks()[0];
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// Make sure there is only one predecessor block in the loop.
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BasicBlock *ExitingBlock = 0;
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for (pred_iterator PI = pred_begin(ExitBlock), PE = pred_end(ExitBlock);
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PI != PE; ++PI)
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if (L->contains(*PI)) {
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if (ExitingBlock == 0)
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ExitingBlock = *PI;
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else
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return; // Multiple exits from loop to this block.
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}
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assert(ExitingBlock && "Loop info is broken");
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if (!isa<BranchInst>(ExitingBlock->getTerminator()))
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return; // Can't rewrite non-branch yet
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BranchInst *BI = cast<BranchInst>(ExitingBlock->getTerminator());
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assert(BI->isConditional() && "Must be conditional to be part of loop!");
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std::set<Instruction*> InstructionsToDelete;
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if (Instruction *Cond = dyn_cast<Instruction>(BI->getCondition()))
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InstructionsToDelete.insert(Cond);
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// Expand the code for the iteration count into the preheader of the loop.
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BasicBlock *Preheader = L->getLoopPreheader();
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Value *ExitCnt = RW.ExpandCodeFor(IterationCount, Preheader->getTerminator(),
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IndVar->getType());
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// Insert a new setne or seteq instruction before the branch.
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Instruction::BinaryOps Opcode;
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if (L->contains(BI->getSuccessor(0)))
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Opcode = Instruction::SetNE;
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else
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Opcode = Instruction::SetEQ;
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Value *Cond = new SetCondInst(Opcode, IndVar, ExitCnt, "exitcond", BI);
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BI->setCondition(Cond);
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++NumLFTR;
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Changed = true;
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DeleteTriviallyDeadInstructions(InstructionsToDelete);
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}
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/// RewriteLoopExitValues - Check to see if this loop has a computable
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/// loop-invariant execution count. If so, this means that we can compute the
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/// final value of any expressions that are recurrent in the loop, and
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/// substitute the exit values from the loop into any instructions outside of
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/// the loop that use the final values of the current expressions.
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void IndVarSimplify::RewriteLoopExitValues(Loop *L) {
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BasicBlock *Preheader = L->getLoopPreheader();
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// Scan all of the instructions in the loop, looking at those that have
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// extra-loop users and which are recurrences.
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ScalarEvolutionRewriter Rewriter(*SE, *LI);
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// We insert the code into the preheader of the loop if the loop contains
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// multiple exit blocks, or in the exit block if there is exactly one.
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BasicBlock *BlockToInsertInto;
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if (L->getExitBlocks().size() == 1)
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BlockToInsertInto = L->getExitBlocks()[0];
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else
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BlockToInsertInto = Preheader;
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BasicBlock::iterator InsertPt = BlockToInsertInto->begin();
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while (isa<PHINode>(InsertPt)) ++InsertPt;
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std::set<Instruction*> InstructionsToDelete;
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for (unsigned i = 0, e = L->getBlocks().size(); i != e; ++i)
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if (LI->getLoopFor(L->getBlocks()[i]) == L) { // Not in a subloop...
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BasicBlock *BB = L->getBlocks()[i];
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for (BasicBlock::iterator I = BB->begin(), E = BB->end(); I != E; ++I)
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if (I->getType()->isInteger()) { // Is an integer instruction
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SCEVHandle SH = SE->getSCEV(I);
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if (SH->hasComputableLoopEvolution(L)) { // Varies predictably
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// Find out if this predictably varying value is actually used
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// outside of the loop. "extra" as opposed to "intra".
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std::vector<User*> ExtraLoopUsers;
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for (Value::use_iterator UI = I->use_begin(), E = I->use_end();
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UI != E; ++UI)
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if (!L->contains(cast<Instruction>(*UI)->getParent()))
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ExtraLoopUsers.push_back(*UI);
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if (!ExtraLoopUsers.empty()) {
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// Okay, this instruction has a user outside of the current loop
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// and varies predictably in this loop. Evaluate the value it
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// contains when the loop exits, and insert code for it.
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SCEVHandle ExitValue = SE->getSCEVAtScope(I,L->getParentLoop());
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if (!isa<SCEVCouldNotCompute>(ExitValue)) {
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Changed = true;
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++NumReplaced;
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Value *NewVal = Rewriter.ExpandCodeFor(ExitValue, InsertPt,
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I->getType());
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// Rewrite any users of the computed value outside of the loop
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// with the newly computed value.
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for (unsigned i = 0, e = ExtraLoopUsers.size(); i != e; ++i)
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ExtraLoopUsers[i]->replaceUsesOfWith(I, NewVal);
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// If this instruction is dead now, schedule it to be removed.
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if (I->use_empty())
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InstructionsToDelete.insert(I);
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}
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}
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}
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}
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}
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DeleteTriviallyDeadInstructions(InstructionsToDelete);
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}
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void IndVarSimplify::runOnLoop(Loop *L) {
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// First step. Check to see if there are any trivial GEP pointer recurrences.
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// If there are, change them into integer recurrences, permitting analysis by
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// the SCEV routines.
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//
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BasicBlock *Header = L->getHeader();
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BasicBlock *Preheader = L->getLoopPreheader();
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std::set<Instruction*> DeadInsts;
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for (BasicBlock::iterator I = Header->begin();
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PHINode *PN = dyn_cast<PHINode>(I); ++I)
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if (isa<PointerType>(PN->getType()))
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EliminatePointerRecurrence(PN, Preheader, DeadInsts);
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if (!DeadInsts.empty())
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DeleteTriviallyDeadInstructions(DeadInsts);
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// Next, transform all loops nesting inside of this loop.
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for (LoopInfo::iterator I = L->begin(), E = L->end(); I != E; ++I)
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runOnLoop(*I);
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// Check to see if this loop has a computable loop-invariant execution count.
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// If so, this means that we can compute the final value of any expressions
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// that are recurrent in the loop, and substitute the exit values from the
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// loop into any instructions outside of the loop that use the final values of
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// the current expressions.
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//
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SCEVHandle IterationCount = SE->getIterationCount(L);
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if (!isa<SCEVCouldNotCompute>(IterationCount))
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RewriteLoopExitValues(L);
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// Next, analyze all of the induction variables in the loop, canonicalizing
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// auxillary induction variables.
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std::vector<std::pair<PHINode*, SCEVHandle> > IndVars;
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for (BasicBlock::iterator I = Header->begin();
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PHINode *PN = dyn_cast<PHINode>(I); ++I)
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if (PN->getType()->isInteger()) { // FIXME: when we have fast-math, enable!
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SCEVHandle SCEV = SE->getSCEV(PN);
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if (SCEV->hasComputableLoopEvolution(L))
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if (SE->shouldSubstituteIndVar(SCEV)) // HACK!
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IndVars.push_back(std::make_pair(PN, SCEV));
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}
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// If there are no induction variables in the loop, there is nothing more to
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// do.
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if (IndVars.empty()) return;
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// Compute the type of the largest recurrence expression.
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//
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const Type *LargestType = IndVars[0].first->getType();
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bool DifferingSizes = false;
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for (unsigned i = 1, e = IndVars.size(); i != e; ++i) {
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const Type *Ty = IndVars[i].first->getType();
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DifferingSizes |= Ty->getPrimitiveSize() != LargestType->getPrimitiveSize();
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if (Ty->getPrimitiveSize() > LargestType->getPrimitiveSize())
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LargestType = Ty;
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}
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// Create a rewriter object which we'll use to transform the code with.
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ScalarEvolutionRewriter Rewriter(*SE, *LI);
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// Now that we know the largest of of the induction variables in this loop,
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// insert a canonical induction variable of the largest size.
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Value *IndVar = Rewriter.GetOrInsertCanonicalInductionVariable(L,LargestType);
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++NumInserted;
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Changed = true;
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if (!isa<SCEVCouldNotCompute>(IterationCount))
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LinearFunctionTestReplace(L, IterationCount, IndVar, Rewriter);
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#if 0
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// If there were induction variables of other sizes, cast the primary
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// induction variable to the right size for them, avoiding the need for the
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// code evaluation methods to insert induction variables of different sizes.
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// FIXME!
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if (DifferingSizes) {
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std::map<unsigned, Value*> InsertedSizes;
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for (unsigned i = 0, e = IndVars.size(); i != e; ++i) {
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}
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}
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#endif
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// Now that we have a canonical induction variable, we can rewrite any
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// recurrences in terms of the induction variable. Start with the auxillary
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// induction variables, and recursively rewrite any of their uses.
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BasicBlock::iterator InsertPt = Header->begin();
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while (isa<PHINode>(InsertPt)) ++InsertPt;
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while (!IndVars.empty()) {
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PHINode *PN = IndVars.back().first;
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Value *NewVal = Rewriter.ExpandCodeFor(IndVars.back().second, InsertPt,
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PN->getType());
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// Replace the old PHI Node with the inserted computation.
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PN->replaceAllUsesWith(NewVal);
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DeadInsts.insert(PN);
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IndVars.pop_back();
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++NumRemoved;
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Changed = true;
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}
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DeleteTriviallyDeadInstructions(DeadInsts);
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// TODO: In the future we could replace all instructions in the loop body with
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// simpler expressions. It's not clear how useful this would be though or if
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// the code expansion cost would be worth it! We probably shouldn't do this
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// until we have a way to reuse expressions already in the code.
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#if 0
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for (unsigned i = 0, e = L->getBlocks().size(); i != e; ++i)
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if (LI->getLoopFor(L->getBlocks()[i]) == L) { // Not in a subloop...
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BasicBlock *BB = L->getBlocks()[i];
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for (BasicBlock::iterator I = BB->begin(), E = BB->end(); I != E; ++I)
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if (I->getType()->isInteger() && // Is an integer instruction
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!Rewriter.isInsertedInstruction(I)) {
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SCEVHandle SH = SE->getSCEV(I);
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}
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}
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#endif
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}
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