llvm-6502/lib/Transforms/Scalar/IndVarSimplify.cpp
Chris Lattner 40bf8b48cd Rewrite the indvars pass to use the ScalarEvolution analysis.
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
2004-04-02 20:24:31 +00:00

421 lines
17 KiB
C++

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