mirror of
https://github.com/c64scene-ar/llvm-6502.git
synced 2024-12-27 13:30:05 +00:00
697954c15d
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@1503 91177308-0d34-0410-b5e6-96231b3b80d8
157 lines
5.6 KiB
C++
157 lines
5.6 KiB
C++
//===- llvm/Analysis/InductionVariable.h - Induction variable ----*- C++ -*--=//
|
|
//
|
|
// This interface is used to identify and classify induction variables that
|
|
// exist in the program. Induction variables must contain a PHI node that
|
|
// exists in a loop header. Because of this, they are identified an managed by
|
|
// this PHI node.
|
|
//
|
|
// Induction variables are classified into a type. Knowing that an induction
|
|
// variable is of a specific type can constrain the values of the start and
|
|
// step. For example, a SimpleLinear induction variable must have a start and
|
|
// step values that are constants.
|
|
//
|
|
// Induction variables can be created with or without loop information. If no
|
|
// loop information is available, induction variables cannot be recognized to be
|
|
// more than SimpleLinear variables.
|
|
//
|
|
//===----------------------------------------------------------------------===//
|
|
|
|
#include "llvm/Analysis/InductionVariable.h"
|
|
#include "llvm/Analysis/LoopInfo.h"
|
|
#include "llvm/Analysis/Expressions.h"
|
|
#include "llvm/iPHINode.h"
|
|
#include "llvm/InstrTypes.h"
|
|
#include "llvm/Type.h"
|
|
#include "llvm/ConstantVals.h"
|
|
|
|
using analysis::ExprType;
|
|
|
|
|
|
static bool isLoopInvariant(const Value *V, const cfg::Loop *L) {
|
|
if (isa<Constant>(V) || isa<MethodArgument>(V) || isa<GlobalValue>(V))
|
|
return true;
|
|
|
|
const Instruction *I = cast<Instruction>(V);
|
|
const BasicBlock *BB = I->getParent();
|
|
|
|
return !L->contains(BB);
|
|
}
|
|
|
|
enum InductionVariable::iType
|
|
InductionVariable::Classify(const Value *Start, const Value *Step,
|
|
const cfg::Loop *L = 0) {
|
|
// Check for cannonical and simple linear expressions now...
|
|
if (ConstantInt *CStart = dyn_cast<ConstantInt>(Start))
|
|
if (ConstantInt *CStep = dyn_cast<ConstantInt>(Step)) {
|
|
if (CStart->equalsInt(0) && CStep->equalsInt(1))
|
|
return Cannonical;
|
|
else
|
|
return SimpleLinear;
|
|
}
|
|
|
|
// Without loop information, we cannot do any better, so bail now...
|
|
if (L == 0) return Unknown;
|
|
|
|
if (isLoopInvariant(Start, L) && isLoopInvariant(Step, L))
|
|
return Linear;
|
|
return Unknown;
|
|
}
|
|
|
|
// Create an induction variable for the specified value. If it is a PHI, and
|
|
// if it's recognizable, classify it and fill in instance variables.
|
|
//
|
|
InductionVariable::InductionVariable(PHINode *P, cfg::LoopInfo *LoopInfo) {
|
|
InductionType = Unknown; // Assume the worst
|
|
Phi = P;
|
|
|
|
// If the PHI node has more than two predecessors, we don't know how to
|
|
// handle it.
|
|
//
|
|
if (Phi->getNumIncomingValues() != 2) return;
|
|
|
|
// FIXME: Handle FP induction variables.
|
|
if (Phi->getType() == Type::FloatTy || Phi->getType() == Type::DoubleTy)
|
|
return;
|
|
|
|
// If we have loop information, make sure that this PHI node is in the header
|
|
// of a loop...
|
|
//
|
|
const cfg::Loop *L = LoopInfo ? LoopInfo->getLoopFor(Phi->getParent()) : 0;
|
|
if (L && L->getHeader() != Phi->getParent())
|
|
return;
|
|
|
|
Value *V1 = Phi->getIncomingValue(0);
|
|
Value *V2 = Phi->getIncomingValue(1);
|
|
|
|
if (L == 0) { // No loop information? Base everything on expression analysis
|
|
ExprType E1 = analysis::ClassifyExpression(V1);
|
|
ExprType E2 = analysis::ClassifyExpression(V2);
|
|
|
|
if (E1.ExprTy > E2.ExprTy) // Make E1 be the simpler expression
|
|
std::swap(E1, E2);
|
|
|
|
// E1 must be a constant incoming value, and E2 must be a linear expression
|
|
// with respect to the PHI node.
|
|
//
|
|
if (E1.ExprTy > ExprType::Constant || E2.ExprTy != ExprType::Linear ||
|
|
E2.Var != Phi)
|
|
return;
|
|
|
|
// Okay, we have found an induction variable. Save the start and step values
|
|
const Type *ETy = Phi->getType();
|
|
if (ETy->isPointerType()) ETy = Type::ULongTy;
|
|
|
|
Start = (Value*)(E1.Offset ? E1.Offset : ConstantInt::get(ETy, 0));
|
|
Step = (Value*)(E2.Offset ? E2.Offset : ConstantInt::get(ETy, 0));
|
|
} else {
|
|
// Okay, at this point, we know that we have loop information...
|
|
|
|
// Make sure that V1 is the incoming value, and V2 is from the backedge of
|
|
// the loop.
|
|
if (L->contains(Phi->getIncomingBlock(0))) // Wrong order. Swap now.
|
|
std::swap(V1, V2);
|
|
|
|
Start = V1; // We know that Start has to be loop invariant...
|
|
Step = 0;
|
|
|
|
if (V2 == Phi) { // referencing the PHI directly? Must have zero step
|
|
Step = Constant::getNullConstant(Phi->getType());
|
|
} else if (BinaryOperator *I = dyn_cast<BinaryOperator>(V2)) {
|
|
// TODO: This could be much better...
|
|
if (I->getOpcode() == Instruction::Add) {
|
|
if (I->getOperand(0) == Phi)
|
|
Step = I->getOperand(1);
|
|
else if (I->getOperand(1) == Phi)
|
|
Step = I->getOperand(0);
|
|
}
|
|
}
|
|
|
|
if (Step == 0) { // Unrecognized step value...
|
|
ExprType StepE = analysis::ClassifyExpression(V2);
|
|
if (StepE.ExprTy != ExprType::Linear ||
|
|
StepE.Var != Phi) return;
|
|
|
|
const Type *ETy = Phi->getType();
|
|
if (ETy->isPointerType()) ETy = Type::ULongTy;
|
|
Step = (Value*)(StepE.Offset ? StepE.Offset : ConstantInt::get(ETy, 0));
|
|
} else { // We were able to get a step value, simplify with expr analysis
|
|
ExprType StepE = analysis::ClassifyExpression(Step);
|
|
if (StepE.ExprTy == ExprType::Linear && StepE.Offset == 0) {
|
|
// No offset from variable? Grab the variable
|
|
Step = StepE.Var;
|
|
} else if (StepE.ExprTy == ExprType::Constant) {
|
|
if (StepE.Offset)
|
|
Step = (Value*)StepE.Offset;
|
|
else
|
|
Step = Constant::getNullConstant(Step->getType());
|
|
const Type *ETy = Phi->getType();
|
|
if (ETy->isPointerType()) ETy = Type::ULongTy;
|
|
Step = (Value*)(StepE.Offset ? StepE.Offset : ConstantInt::get(ETy,0));
|
|
}
|
|
}
|
|
}
|
|
|
|
// Classify the induction variable type now...
|
|
InductionType = InductionVariable::Classify(Start, Step, L);
|
|
}
|