llvm-6502/lib/Transforms/Scalar/IndVarSimplify.cpp
Chris Lattner cda9ca5a4f Allow indvar simplify to canonicalize ANY affine IV, not just affine IVs with
constant stride.  This implements Transforms/IndVarsSimplify/variable-stride-ivs.ll


git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@22744 91177308-0d34-0410-b5e6-96231b3b80d8
2005-08-10 01:12:06 +00:00

531 lines
22 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/Constants.h"
#include "llvm/Instructions.h"
#include "llvm/Type.h"
#include "llvm/Analysis/ScalarEvolutionExpander.h"
#include "llvm/Analysis/LoopInfo.h"
#include "llvm/Support/CFG.h"
#include "llvm/Support/GetElementPtrTypeIterator.h"
#include "llvm/Transforms/Utils/Local.h"
#include "llvm/Support/CommandLine.h"
#include "llvm/ADT/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,
SCEVExpander &RW);
void RewriteLoopExitValues(Loop *L);
void DeleteTriviallyDeadInstructions(std::set<Instruction*> &Insts);
};
RegisterOpt<IndVarSimplify> X("indvars", "Canonicalize Induction Variables");
}
FunctionPass *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->eraseFromParent();
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 match!");
// 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::createAdd(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);
// If the incoming value is a constant expr GEP, try peeling out the array
// 0 index if possible to make things simpler.
if (ConstantExpr *CE = dyn_cast<ConstantExpr>(GEPI->getOperand(0)))
if (CE->getOpcode() == Instruction::GetElementPtr) {
unsigned NumOps = CE->getNumOperands();
assert(NumOps > 1 && "CE folding didn't work!");
if (CE->getOperand(NumOps-1)->isNullValue()) {
// Check to make sure the last index really is an array index.
gep_type_iterator GTI = gep_type_begin(GEPI);
for (unsigned i = 1, e = GEPI->getNumOperands()-1;
i != e; ++i, ++GTI)
/*empty*/;
if (isa<SequentialType>(*GTI)) {
// Pull the last index out of the constant expr GEP.
std::vector<Value*> CEIdxs(CE->op_begin()+1, CE->op_end()-1);
Constant *NCE = ConstantExpr::getGetElementPtr(CE->getOperand(0),
CEIdxs);
GetElementPtrInst *NGEPI =
new GetElementPtrInst(NCE, Constant::getNullValue(Type::IntTy),
NewAdd, GEPI->getName(), GEPI);
GEPI->replaceAllUsesWith(NGEPI);
GEPI->eraseFromParent();
GEPI = NGEPI;
}
}
}
// 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 incremented loop induction
/// variable. This pass is able to rewrite the exit tests of any loop where the
/// SCEV analysis can determine a loop-invariant trip count of the loop, which
/// is actually a much broader range than just linear tests.
void IndVarSimplify::LinearFunctionTestReplace(Loop *L, SCEV *IterationCount,
SCEVExpander &RW) {
// Find the exit block for the loop. We can currently only handle loops with
// a single exit.
std::vector<BasicBlock*> ExitBlocks;
L->getExitBlocks(ExitBlocks);
if (ExitBlocks.size() != 1) return;
BasicBlock *ExitBlock = ExitBlocks[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);
// If the exiting block is not the same as the backedge block, we must compare
// against the preincremented value, otherwise we prefer to compare against
// the post-incremented value.
BasicBlock *Header = L->getHeader();
pred_iterator HPI = pred_begin(Header);
assert(HPI != pred_end(Header) && "Loop with zero preds???");
if (!L->contains(*HPI)) ++HPI;
assert(HPI != pred_end(Header) && L->contains(*HPI) &&
"No backedge in loop?");
SCEVHandle TripCount = IterationCount;
Value *IndVar;
if (*HPI == ExitingBlock) {
// The IterationCount expression contains the number of times that the
// backedge actually branches to the loop header. This is one less than the
// number of times the loop executes, so add one to it.
Constant *OneC = ConstantInt::get(IterationCount->getType(), 1);
TripCount = SCEVAddExpr::get(IterationCount, SCEVUnknown::get(OneC));
IndVar = L->getCanonicalInductionVariableIncrement();
} else {
// We have to use the preincremented value...
IndVar = L->getCanonicalInductionVariable();
}
// Expand the code for the iteration count into the preheader of the loop.
BasicBlock *Preheader = L->getLoopPreheader();
Value *ExitCnt = RW.expandCodeFor(TripCount, 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.
SCEVExpander 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;
std::vector<BasicBlock*> ExitBlocks;
L->getExitBlocks(ExitBlocks);
if (ExitBlocks.size() == 1)
BlockToInsertInto = ExitBlocks[0];
else
BlockToInsertInto = Preheader;
BasicBlock::iterator InsertPt = BlockToInsertInto->begin();
while (isa<PHINode>(InsertPt)) ++InsertPt;
bool HasConstantItCount = isa<SCEVConstant>(SE->getIterationCount(L));
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;) {
if (I->getType()->isInteger()) { // Is an integer instruction
SCEVHandle SH = SE->getSCEV(I);
if (SH->hasComputableLoopEvolution(L) || // Varies predictably
HasConstantItCount) {
// 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;
// Remember the next instruction. The rewriter can move code
// around in some cases.
BasicBlock::iterator NextI = I; ++NextI;
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);
I = NextI;
continue; // Skip the ++I
}
}
}
}
// Next instruction. Continue instruction skips this.
++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(); isa<PHINode>(I); ++I) {
PHINode *PN = cast<PHINode>(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(); isa<PHINode>(I); ++I) {
PHINode *PN = cast<PHINode>(I);
if (PN->getType()->isInteger()) { // FIXME: when we have fast-math, enable!
SCEVHandle SCEV = SE->getSCEV(PN);
if (SCEV->hasComputableLoopEvolution(L))
// FIXME: It is an extremely bad idea to indvar substitute anything more
// complex than affine induction variables. Doing so will put expensive
// polynomial evaluations inside of the loop, and the str reduction pass
// currently can only reduce affine polynomials. For now just disable
// indvar subst on anything more complex than an affine addrec.
if (SCEVAddRecExpr *AR = dyn_cast<SCEVAddRecExpr>(SCEV))
if (AR->isAffine())
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()) {
// Actually, if we know how many times the loop iterates, lets insert a
// canonical induction variable to help subsequent passes.
if (!isa<SCEVCouldNotCompute>(IterationCount)) {
SCEVExpander Rewriter(*SE, *LI);
Rewriter.getOrInsertCanonicalInductionVariable(L,
IterationCount->getType());
LinearFunctionTestReplace(L, IterationCount, Rewriter);
}
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.
SCEVExpander 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.
LargestType = LargestType->getUnsignedVersion();
Value *IndVar = Rewriter.getOrInsertCanonicalInductionVariable(L,LargestType);
++NumInserted;
Changed = true;
if (!isa<SCEVCouldNotCompute>(IterationCount))
LinearFunctionTestReplace(L, IterationCount, Rewriter);
// 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;
// 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.
if (DifferingSizes) {
bool InsertedSizes[17] = { false };
InsertedSizes[LargestType->getPrimitiveSize()] = true;
for (unsigned i = 0, e = IndVars.size(); i != e; ++i)
if (!InsertedSizes[IndVars[i].first->getType()->getPrimitiveSize()]) {
PHINode *PN = IndVars[i].first;
InsertedSizes[PN->getType()->getPrimitiveSize()] = true;
Instruction *New = new CastInst(IndVar,
PN->getType()->getUnsignedVersion(),
"indvar", InsertPt);
Rewriter.addInsertedValue(New, SE->getSCEV(New));
}
}
// 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.
std::map<unsigned, Value*> InsertedSizes;
while (!IndVars.empty()) {
PHINode *PN = IndVars.back().first;
Value *NewVal = Rewriter.expandCodeFor(IndVars.back().second, InsertPt,
PN->getType());
std::string Name = PN->getName();
PN->setName("");
NewVal->setName(Name);
// Replace the old PHI Node with the inserted computation.
PN->replaceAllUsesWith(NewVal);
DeadInsts.insert(PN);
IndVars.pop_back();
++NumRemoved;
Changed = true;
}
#if 0
// Now replace all derived expressions in the loop body with simpler
// expressions.
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
!I->use_empty() &&
!Rewriter.isInsertedInstruction(I)) {
SCEVHandle SH = SE->getSCEV(I);
Value *V = Rewriter.expandCodeFor(SH, I, I->getType());
if (V != I) {
if (isa<Instruction>(V)) {
std::string Name = I->getName();
I->setName("");
V->setName(Name);
}
I->replaceAllUsesWith(V);
DeadInsts.insert(I);
++NumRemoved;
Changed = true;
}
}
}
#endif
DeleteTriviallyDeadInstructions(DeadInsts);
}