llvm-project/llvm/lib/Transforms/Scalar/Float2Int.cpp

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//===- Float2Int.cpp - Demote floating point ops to work on integers ------===//
//
// The LLVM Compiler Infrastructure
//
// This file is distributed under the University of Illinois Open Source
// License. See LICENSE.TXT for details.
//
//===----------------------------------------------------------------------===//
//
// This file implements the Float2Int pass, which aims to demote floating
// point operations to work on integers, where that is losslessly possible.
//
//===----------------------------------------------------------------------===//
#define DEBUG_TYPE "float2int"
#include "llvm/ADT/APInt.h"
#include "llvm/ADT/APSInt.h"
#include "llvm/ADT/DenseMap.h"
#include "llvm/ADT/EquivalenceClasses.h"
#include "llvm/ADT/MapVector.h"
#include "llvm/ADT/SmallVector.h"
#include "llvm/Analysis/AliasAnalysis.h"
[PM/AA] Rebuild LLVM's alias analysis infrastructure in a way compatible with the new pass manager, and no longer relying on analysis groups. This builds essentially a ground-up new AA infrastructure stack for LLVM. The core ideas are the same that are used throughout the new pass manager: type erased polymorphism and direct composition. The design is as follows: - FunctionAAResults is a type-erasing alias analysis results aggregation interface to walk a single query across a range of results from different alias analyses. Currently this is function-specific as we always assume that aliasing queries are *within* a function. - AAResultBase is a CRTP utility providing stub implementations of various parts of the alias analysis result concept, notably in several cases in terms of other more general parts of the interface. This can be used to implement only a narrow part of the interface rather than the entire interface. This isn't really ideal, this logic should be hoisted into FunctionAAResults as currently it will cause a significant amount of redundant work, but it faithfully models the behavior of the prior infrastructure. - All the alias analysis passes are ported to be wrapper passes for the legacy PM and new-style analysis passes for the new PM with a shared result object. In some cases (most notably CFL), this is an extremely naive approach that we should revisit when we can specialize for the new pass manager. - BasicAA has been restructured to reflect that it is much more fundamentally a function analysis because it uses dominator trees and loop info that need to be constructed for each function. All of the references to getting alias analysis results have been updated to use the new aggregation interface. All the preservation and other pass management code has been updated accordingly. The way the FunctionAAResultsWrapperPass works is to detect the available alias analyses when run, and add them to the results object. This means that we should be able to continue to respect when various passes are added to the pipeline, for example adding CFL or adding TBAA passes should just cause their results to be available and to get folded into this. The exception to this rule is BasicAA which really needs to be a function pass due to using dominator trees and loop info. As a consequence, the FunctionAAResultsWrapperPass directly depends on BasicAA and always includes it in the aggregation. This has significant implications for preserving analyses. Generally, most passes shouldn't bother preserving FunctionAAResultsWrapperPass because rebuilding the results just updates the set of known AA passes. The exception to this rule are LoopPass instances which need to preserve all the function analyses that the loop pass manager will end up needing. This means preserving both BasicAAWrapperPass and the aggregating FunctionAAResultsWrapperPass. Now, when preserving an alias analysis, you do so by directly preserving that analysis. This is only necessary for non-immutable-pass-provided alias analyses though, and there are only three of interest: BasicAA, GlobalsAA (formerly GlobalsModRef), and SCEVAA. Usually BasicAA is preserved when needed because it (like DominatorTree and LoopInfo) is marked as a CFG-only pass. I've expanded GlobalsAA into the preserved set everywhere we previously were preserving all of AliasAnalysis, and I've added SCEVAA in the intersection of that with where we preserve SCEV itself. One significant challenge to all of this is that the CGSCC passes were actually using the alias analysis implementations by taking advantage of a pretty amazing set of loop holes in the old pass manager's analysis management code which allowed analysis groups to slide through in many cases. Moving away from analysis groups makes this problem much more obvious. To fix it, I've leveraged the flexibility the design of the new PM components provides to just directly construct the relevant alias analyses for the relevant functions in the IPO passes that need them. This is a bit hacky, but should go away with the new pass manager, and is already in many ways cleaner than the prior state. Another significant challenge is that various facilities of the old alias analysis infrastructure just don't fit any more. The most significant of these is the alias analysis 'counter' pass. That pass relied on the ability to snoop on AA queries at different points in the analysis group chain. Instead, I'm planning to build printing functionality directly into the aggregation layer. I've not included that in this patch merely to keep it smaller. Note that all of this needs a nearly complete rewrite of the AA documentation. I'm planning to do that, but I'd like to make sure the new design settles, and to flesh out a bit more of what it looks like in the new pass manager first. Differential Revision: http://reviews.llvm.org/D12080 llvm-svn: 247167
2015-09-10 01:55:00 +08:00
#include "llvm/Analysis/GlobalsModRef.h"
#include "llvm/IR/ConstantRange.h"
#include "llvm/IR/Constants.h"
#include "llvm/IR/IRBuilder.h"
#include "llvm/IR/InstIterator.h"
#include "llvm/IR/Instructions.h"
#include "llvm/IR/Module.h"
#include "llvm/Pass.h"
#include "llvm/Support/Debug.h"
#include "llvm/Support/raw_ostream.h"
#include "llvm/Transforms/Scalar.h"
#include <deque>
#include <functional> // For std::function
using namespace llvm;
// The algorithm is simple. Start at instructions that convert from the
// float to the int domain: fptoui, fptosi and fcmp. Walk up the def-use
// graph, using an equivalence datastructure to unify graphs that interfere.
//
// Mappable instructions are those with an integer corrollary that, given
// integer domain inputs, produce an integer output; fadd, for example.
//
// If a non-mappable instruction is seen, this entire def-use graph is marked
// as non-transformable. If we see an instruction that converts from the
// integer domain to FP domain (uitofp,sitofp), we terminate our walk.
/// The largest integer type worth dealing with.
static cl::opt<unsigned>
MaxIntegerBW("float2int-max-integer-bw", cl::init(64), cl::Hidden,
cl::desc("Max integer bitwidth to consider in float2int"
"(default=64)"));
namespace {
struct Float2Int : public FunctionPass {
static char ID; // Pass identification, replacement for typeid
Float2Int() : FunctionPass(ID) {
initializeFloat2IntPass(*PassRegistry::getPassRegistry());
}
bool runOnFunction(Function &F) override;
void getAnalysisUsage(AnalysisUsage &AU) const override {
AU.setPreservesCFG();
[PM/AA] Rebuild LLVM's alias analysis infrastructure in a way compatible with the new pass manager, and no longer relying on analysis groups. This builds essentially a ground-up new AA infrastructure stack for LLVM. The core ideas are the same that are used throughout the new pass manager: type erased polymorphism and direct composition. The design is as follows: - FunctionAAResults is a type-erasing alias analysis results aggregation interface to walk a single query across a range of results from different alias analyses. Currently this is function-specific as we always assume that aliasing queries are *within* a function. - AAResultBase is a CRTP utility providing stub implementations of various parts of the alias analysis result concept, notably in several cases in terms of other more general parts of the interface. This can be used to implement only a narrow part of the interface rather than the entire interface. This isn't really ideal, this logic should be hoisted into FunctionAAResults as currently it will cause a significant amount of redundant work, but it faithfully models the behavior of the prior infrastructure. - All the alias analysis passes are ported to be wrapper passes for the legacy PM and new-style analysis passes for the new PM with a shared result object. In some cases (most notably CFL), this is an extremely naive approach that we should revisit when we can specialize for the new pass manager. - BasicAA has been restructured to reflect that it is much more fundamentally a function analysis because it uses dominator trees and loop info that need to be constructed for each function. All of the references to getting alias analysis results have been updated to use the new aggregation interface. All the preservation and other pass management code has been updated accordingly. The way the FunctionAAResultsWrapperPass works is to detect the available alias analyses when run, and add them to the results object. This means that we should be able to continue to respect when various passes are added to the pipeline, for example adding CFL or adding TBAA passes should just cause their results to be available and to get folded into this. The exception to this rule is BasicAA which really needs to be a function pass due to using dominator trees and loop info. As a consequence, the FunctionAAResultsWrapperPass directly depends on BasicAA and always includes it in the aggregation. This has significant implications for preserving analyses. Generally, most passes shouldn't bother preserving FunctionAAResultsWrapperPass because rebuilding the results just updates the set of known AA passes. The exception to this rule are LoopPass instances which need to preserve all the function analyses that the loop pass manager will end up needing. This means preserving both BasicAAWrapperPass and the aggregating FunctionAAResultsWrapperPass. Now, when preserving an alias analysis, you do so by directly preserving that analysis. This is only necessary for non-immutable-pass-provided alias analyses though, and there are only three of interest: BasicAA, GlobalsAA (formerly GlobalsModRef), and SCEVAA. Usually BasicAA is preserved when needed because it (like DominatorTree and LoopInfo) is marked as a CFG-only pass. I've expanded GlobalsAA into the preserved set everywhere we previously were preserving all of AliasAnalysis, and I've added SCEVAA in the intersection of that with where we preserve SCEV itself. One significant challenge to all of this is that the CGSCC passes were actually using the alias analysis implementations by taking advantage of a pretty amazing set of loop holes in the old pass manager's analysis management code which allowed analysis groups to slide through in many cases. Moving away from analysis groups makes this problem much more obvious. To fix it, I've leveraged the flexibility the design of the new PM components provides to just directly construct the relevant alias analyses for the relevant functions in the IPO passes that need them. This is a bit hacky, but should go away with the new pass manager, and is already in many ways cleaner than the prior state. Another significant challenge is that various facilities of the old alias analysis infrastructure just don't fit any more. The most significant of these is the alias analysis 'counter' pass. That pass relied on the ability to snoop on AA queries at different points in the analysis group chain. Instead, I'm planning to build printing functionality directly into the aggregation layer. I've not included that in this patch merely to keep it smaller. Note that all of this needs a nearly complete rewrite of the AA documentation. I'm planning to do that, but I'd like to make sure the new design settles, and to flesh out a bit more of what it looks like in the new pass manager first. Differential Revision: http://reviews.llvm.org/D12080 llvm-svn: 247167
2015-09-10 01:55:00 +08:00
AU.addPreserved<GlobalsAAWrapperPass>();
}
void findRoots(Function &F, SmallPtrSet<Instruction*,8> &Roots);
ConstantRange seen(Instruction *I, ConstantRange R);
ConstantRange badRange();
ConstantRange unknownRange();
ConstantRange validateRange(ConstantRange R);
void walkBackwards(const SmallPtrSetImpl<Instruction*> &Roots);
void walkForwards();
bool validateAndTransform();
Value *convert(Instruction *I, Type *ToTy);
void cleanup();
MapVector<Instruction*, ConstantRange > SeenInsts;
SmallPtrSet<Instruction*,8> Roots;
EquivalenceClasses<Instruction*> ECs;
MapVector<Instruction*, Value*> ConvertedInsts;
LLVMContext *Ctx;
};
}
char Float2Int::ID = 0;
[PM/AA] Rebuild LLVM's alias analysis infrastructure in a way compatible with the new pass manager, and no longer relying on analysis groups. This builds essentially a ground-up new AA infrastructure stack for LLVM. The core ideas are the same that are used throughout the new pass manager: type erased polymorphism and direct composition. The design is as follows: - FunctionAAResults is a type-erasing alias analysis results aggregation interface to walk a single query across a range of results from different alias analyses. Currently this is function-specific as we always assume that aliasing queries are *within* a function. - AAResultBase is a CRTP utility providing stub implementations of various parts of the alias analysis result concept, notably in several cases in terms of other more general parts of the interface. This can be used to implement only a narrow part of the interface rather than the entire interface. This isn't really ideal, this logic should be hoisted into FunctionAAResults as currently it will cause a significant amount of redundant work, but it faithfully models the behavior of the prior infrastructure. - All the alias analysis passes are ported to be wrapper passes for the legacy PM and new-style analysis passes for the new PM with a shared result object. In some cases (most notably CFL), this is an extremely naive approach that we should revisit when we can specialize for the new pass manager. - BasicAA has been restructured to reflect that it is much more fundamentally a function analysis because it uses dominator trees and loop info that need to be constructed for each function. All of the references to getting alias analysis results have been updated to use the new aggregation interface. All the preservation and other pass management code has been updated accordingly. The way the FunctionAAResultsWrapperPass works is to detect the available alias analyses when run, and add them to the results object. This means that we should be able to continue to respect when various passes are added to the pipeline, for example adding CFL or adding TBAA passes should just cause their results to be available and to get folded into this. The exception to this rule is BasicAA which really needs to be a function pass due to using dominator trees and loop info. As a consequence, the FunctionAAResultsWrapperPass directly depends on BasicAA and always includes it in the aggregation. This has significant implications for preserving analyses. Generally, most passes shouldn't bother preserving FunctionAAResultsWrapperPass because rebuilding the results just updates the set of known AA passes. The exception to this rule are LoopPass instances which need to preserve all the function analyses that the loop pass manager will end up needing. This means preserving both BasicAAWrapperPass and the aggregating FunctionAAResultsWrapperPass. Now, when preserving an alias analysis, you do so by directly preserving that analysis. This is only necessary for non-immutable-pass-provided alias analyses though, and there are only three of interest: BasicAA, GlobalsAA (formerly GlobalsModRef), and SCEVAA. Usually BasicAA is preserved when needed because it (like DominatorTree and LoopInfo) is marked as a CFG-only pass. I've expanded GlobalsAA into the preserved set everywhere we previously were preserving all of AliasAnalysis, and I've added SCEVAA in the intersection of that with where we preserve SCEV itself. One significant challenge to all of this is that the CGSCC passes were actually using the alias analysis implementations by taking advantage of a pretty amazing set of loop holes in the old pass manager's analysis management code which allowed analysis groups to slide through in many cases. Moving away from analysis groups makes this problem much more obvious. To fix it, I've leveraged the flexibility the design of the new PM components provides to just directly construct the relevant alias analyses for the relevant functions in the IPO passes that need them. This is a bit hacky, but should go away with the new pass manager, and is already in many ways cleaner than the prior state. Another significant challenge is that various facilities of the old alias analysis infrastructure just don't fit any more. The most significant of these is the alias analysis 'counter' pass. That pass relied on the ability to snoop on AA queries at different points in the analysis group chain. Instead, I'm planning to build printing functionality directly into the aggregation layer. I've not included that in this patch merely to keep it smaller. Note that all of this needs a nearly complete rewrite of the AA documentation. I'm planning to do that, but I'd like to make sure the new design settles, and to flesh out a bit more of what it looks like in the new pass manager first. Differential Revision: http://reviews.llvm.org/D12080 llvm-svn: 247167
2015-09-10 01:55:00 +08:00
INITIALIZE_PASS_BEGIN(Float2Int, "float2int", "Float to int", false, false)
INITIALIZE_PASS_DEPENDENCY(GlobalsAAWrapperPass)
INITIALIZE_PASS_END(Float2Int, "float2int", "Float to int", false, false)
// Given a FCmp predicate, return a matching ICmp predicate if one
// exists, otherwise return BAD_ICMP_PREDICATE.
static CmpInst::Predicate mapFCmpPred(CmpInst::Predicate P) {
switch (P) {
case CmpInst::FCMP_OEQ:
case CmpInst::FCMP_UEQ:
return CmpInst::ICMP_EQ;
case CmpInst::FCMP_OGT:
case CmpInst::FCMP_UGT:
return CmpInst::ICMP_SGT;
case CmpInst::FCMP_OGE:
case CmpInst::FCMP_UGE:
return CmpInst::ICMP_SGE;
case CmpInst::FCMP_OLT:
case CmpInst::FCMP_ULT:
return CmpInst::ICMP_SLT;
case CmpInst::FCMP_OLE:
case CmpInst::FCMP_ULE:
return CmpInst::ICMP_SLE;
case CmpInst::FCMP_ONE:
case CmpInst::FCMP_UNE:
return CmpInst::ICMP_NE;
default:
return CmpInst::BAD_ICMP_PREDICATE;
}
}
// Given a floating point binary operator, return the matching
// integer version.
static Instruction::BinaryOps mapBinOpcode(unsigned Opcode) {
switch (Opcode) {
default: llvm_unreachable("Unhandled opcode!");
case Instruction::FAdd: return Instruction::Add;
case Instruction::FSub: return Instruction::Sub;
case Instruction::FMul: return Instruction::Mul;
}
}
// Find the roots - instructions that convert from the FP domain to
// integer domain.
void Float2Int::findRoots(Function &F, SmallPtrSet<Instruction*,8> &Roots) {
for (auto &I : instructions(F)) {
switch (I.getOpcode()) {
default: break;
case Instruction::FPToUI:
case Instruction::FPToSI:
Roots.insert(&I);
break;
case Instruction::FCmp:
if (mapFCmpPred(cast<CmpInst>(&I)->getPredicate()) !=
CmpInst::BAD_ICMP_PREDICATE)
Roots.insert(&I);
break;
}
}
}
// Helper - mark I as having been traversed, having range R.
ConstantRange Float2Int::seen(Instruction *I, ConstantRange R) {
DEBUG(dbgs() << "F2I: " << *I << ":" << R << "\n");
if (SeenInsts.find(I) != SeenInsts.end())
SeenInsts.find(I)->second = R;
else
SeenInsts.insert(std::make_pair(I, R));
return R;
}
// Helper - get a range representing a poison value.
ConstantRange Float2Int::badRange() {
return ConstantRange(MaxIntegerBW + 1, true);
}
ConstantRange Float2Int::unknownRange() {
return ConstantRange(MaxIntegerBW + 1, false);
}
ConstantRange Float2Int::validateRange(ConstantRange R) {
if (R.getBitWidth() > MaxIntegerBW + 1)
return badRange();
return R;
}
// The most obvious way to structure the search is a depth-first, eager
// search from each root. However, that require direct recursion and so
// can only handle small instruction sequences. Instead, we split the search
// up into two phases:
// - walkBackwards: A breadth-first walk of the use-def graph starting from
// the roots. Populate "SeenInsts" with interesting
// instructions and poison values if they're obvious and
// cheap to compute. Calculate the equivalance set structure
// while we're here too.
// - walkForwards: Iterate over SeenInsts in reverse order, so we visit
// defs before their uses. Calculate the real range info.
// Breadth-first walk of the use-def graph; determine the set of nodes
// we care about and eagerly determine if some of them are poisonous.
void Float2Int::walkBackwards(const SmallPtrSetImpl<Instruction*> &Roots) {
std::deque<Instruction*> Worklist(Roots.begin(), Roots.end());
while (!Worklist.empty()) {
Instruction *I = Worklist.back();
Worklist.pop_back();
if (SeenInsts.find(I) != SeenInsts.end())
// Seen already.
continue;
switch (I->getOpcode()) {
// FIXME: Handle select and phi nodes.
default:
// Path terminated uncleanly.
seen(I, badRange());
break;
case Instruction::UIToFP: {
// Path terminated cleanly.
unsigned BW = I->getOperand(0)->getType()->getPrimitiveSizeInBits();
APInt Min = APInt::getMinValue(BW).zextOrSelf(MaxIntegerBW+1);
APInt Max = APInt::getMaxValue(BW).zextOrSelf(MaxIntegerBW+1);
seen(I, validateRange(ConstantRange(Min, Max)));
continue;
}
case Instruction::SIToFP: {
// Path terminated cleanly.
unsigned BW = I->getOperand(0)->getType()->getPrimitiveSizeInBits();
APInt SMin = APInt::getSignedMinValue(BW).sextOrSelf(MaxIntegerBW+1);
APInt SMax = APInt::getSignedMaxValue(BW).sextOrSelf(MaxIntegerBW+1);
seen(I, validateRange(ConstantRange(SMin, SMax)));
continue;
}
case Instruction::FAdd:
case Instruction::FSub:
case Instruction::FMul:
case Instruction::FPToUI:
case Instruction::FPToSI:
case Instruction::FCmp:
seen(I, unknownRange());
break;
}
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for (Value *O : I->operands()) {
if (Instruction *OI = dyn_cast<Instruction>(O)) {
// Unify def-use chains if they interfere.
ECs.unionSets(I, OI);
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if (SeenInsts.find(I)->second != badRange())
Worklist.push_back(OI);
} else if (!isa<ConstantFP>(O)) {
// Not an instruction or ConstantFP? we can't do anything.
seen(I, badRange());
}
}
}
}
// Walk forwards down the list of seen instructions, so we visit defs before
// uses.
void Float2Int::walkForwards() {
for (auto &It : make_range(SeenInsts.rbegin(), SeenInsts.rend())) {
if (It.second != unknownRange())
continue;
Instruction *I = It.first;
std::function<ConstantRange(ArrayRef<ConstantRange>)> Op;
switch (I->getOpcode()) {
// FIXME: Handle select and phi nodes.
default:
case Instruction::UIToFP:
case Instruction::SIToFP:
llvm_unreachable("Should have been handled in walkForwards!");
case Instruction::FAdd:
Op = [](ArrayRef<ConstantRange> Ops) {
assert(Ops.size() == 2 && "FAdd is a binary operator!");
return Ops[0].add(Ops[1]);
};
break;
case Instruction::FSub:
Op = [](ArrayRef<ConstantRange> Ops) {
assert(Ops.size() == 2 && "FSub is a binary operator!");
return Ops[0].sub(Ops[1]);
};
break;
case Instruction::FMul:
Op = [](ArrayRef<ConstantRange> Ops) {
assert(Ops.size() == 2 && "FMul is a binary operator!");
return Ops[0].multiply(Ops[1]);
};
break;
//
// Root-only instructions - we'll only see these if they're the
// first node in a walk.
//
case Instruction::FPToUI:
case Instruction::FPToSI:
Op = [](ArrayRef<ConstantRange> Ops) {
assert(Ops.size() == 1 && "FPTo[US]I is a unary operator!");
return Ops[0];
};
break;
case Instruction::FCmp:
Op = [](ArrayRef<ConstantRange> Ops) {
assert(Ops.size() == 2 && "FCmp is a binary operator!");
return Ops[0].unionWith(Ops[1]);
};
break;
}
bool Abort = false;
SmallVector<ConstantRange,4> OpRanges;
for (Value *O : I->operands()) {
if (Instruction *OI = dyn_cast<Instruction>(O)) {
assert(SeenInsts.find(OI) != SeenInsts.end() &&
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"def not seen before use!");
OpRanges.push_back(SeenInsts.find(OI)->second);
} else if (ConstantFP *CF = dyn_cast<ConstantFP>(O)) {
// Work out if the floating point number can be losslessly represented
// as an integer.
// APFloat::convertToInteger(&Exact) purports to do what we want, but
// the exactness can be too precise. For example, negative zero can
// never be exactly converted to an integer.
//
// Instead, we ask APFloat to round itself to an integral value - this
// preserves sign-of-zero - then compare the result with the original.
//
APFloat F = CF->getValueAPF();
// First, weed out obviously incorrect values. Non-finite numbers
// can't be represented and neither can negative zero, unless
// we're in fast math mode.
if (!F.isFinite() ||
(F.isZero() && F.isNegative() && isa<FPMathOperator>(I) &&
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!I->hasNoSignedZeros())) {
seen(I, badRange());
Abort = true;
break;
}
APFloat NewF = F;
auto Res = NewF.roundToIntegral(APFloat::rmNearestTiesToEven);
if (Res != APFloat::opOK || NewF.compare(F) != APFloat::cmpEqual) {
seen(I, badRange());
Abort = true;
break;
}
// OK, it's representable. Now get it.
APSInt Int(MaxIntegerBW+1, false);
bool Exact;
CF->getValueAPF().convertToInteger(Int,
APFloat::rmNearestTiesToEven,
&Exact);
OpRanges.push_back(ConstantRange(Int));
} else {
llvm_unreachable("Should have already marked this as badRange!");
}
}
// Reduce the operands' ranges to a single range and return.
if (!Abort)
seen(I, Op(OpRanges));
}
}
// If there is a valid transform to be done, do it.
bool Float2Int::validateAndTransform() {
bool MadeChange = false;
// Iterate over every disjoint partition of the def-use graph.
for (auto It = ECs.begin(), E = ECs.end(); It != E; ++It) {
ConstantRange R(MaxIntegerBW + 1, false);
bool Fail = false;
Type *ConvertedToTy = nullptr;
// For every member of the partition, union all the ranges together.
for (auto MI = ECs.member_begin(It), ME = ECs.member_end();
MI != ME; ++MI) {
Instruction *I = *MI;
auto SeenI = SeenInsts.find(I);
if (SeenI == SeenInsts.end())
continue;
R = R.unionWith(SeenI->second);
// We need to ensure I has no users that have not been seen.
// If it does, transformation would be illegal.
//
// Don't count the roots, as they terminate the graphs.
if (Roots.count(I) == 0) {
// Set the type of the conversion while we're here.
if (!ConvertedToTy)
ConvertedToTy = I->getType();
for (User *U : I->users()) {
Instruction *UI = dyn_cast<Instruction>(U);
if (!UI || SeenInsts.find(UI) == SeenInsts.end()) {
DEBUG(dbgs() << "F2I: Failing because of " << *U << "\n");
Fail = true;
break;
}
}
}
if (Fail)
break;
}
// If the set was empty, or we failed, or the range is poisonous,
// bail out.
if (ECs.member_begin(It) == ECs.member_end() || Fail ||
R.isFullSet() || R.isSignWrappedSet())
continue;
assert(ConvertedToTy && "Must have set the convertedtoty by this point!");
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// The number of bits required is the maximum of the upper and
// lower limits, plus one so it can be signed.
unsigned MinBW = std::max(R.getLower().getMinSignedBits(),
R.getUpper().getMinSignedBits()) + 1;
DEBUG(dbgs() << "F2I: MinBitwidth=" << MinBW << ", R: " << R << "\n");
// If we've run off the realms of the exactly representable integers,
// the floating point result will differ from an integer approximation.
// Do we need more bits than are in the mantissa of the type we converted
// to? semanticsPrecision returns the number of mantissa bits plus one
// for the sign bit.
unsigned MaxRepresentableBits
= APFloat::semanticsPrecision(ConvertedToTy->getFltSemantics()) - 1;
if (MinBW > MaxRepresentableBits) {
DEBUG(dbgs() << "F2I: Value not guaranteed to be representable!\n");
continue;
}
if (MinBW > 64) {
DEBUG(dbgs() << "F2I: Value requires more than 64 bits to represent!\n");
continue;
}
// OK, R is known to be representable. Now pick a type for it.
// FIXME: Pick the smallest legal type that will fit.
Type *Ty = (MinBW > 32) ? Type::getInt64Ty(*Ctx) : Type::getInt32Ty(*Ctx);
for (auto MI = ECs.member_begin(It), ME = ECs.member_end();
MI != ME; ++MI)
convert(*MI, Ty);
MadeChange = true;
}
return MadeChange;
}
Value *Float2Int::convert(Instruction *I, Type *ToTy) {
if (ConvertedInsts.find(I) != ConvertedInsts.end())
// Already converted this instruction.
return ConvertedInsts[I];
SmallVector<Value*,4> NewOperands;
for (Value *V : I->operands()) {
// Don't recurse if we're an instruction that terminates the path.
if (I->getOpcode() == Instruction::UIToFP ||
I->getOpcode() == Instruction::SIToFP) {
NewOperands.push_back(V);
} else if (Instruction *VI = dyn_cast<Instruction>(V)) {
NewOperands.push_back(convert(VI, ToTy));
} else if (ConstantFP *CF = dyn_cast<ConstantFP>(V)) {
APSInt Val(ToTy->getPrimitiveSizeInBits(), /*IsUnsigned=*/false);
bool Exact;
CF->getValueAPF().convertToInteger(Val,
APFloat::rmNearestTiesToEven,
&Exact);
NewOperands.push_back(ConstantInt::get(ToTy, Val));
} else {
llvm_unreachable("Unhandled operand type?");
}
}
// Now create a new instruction.
IRBuilder<> IRB(I);
Value *NewV = nullptr;
switch (I->getOpcode()) {
default: llvm_unreachable("Unhandled instruction!");
case Instruction::FPToUI:
NewV = IRB.CreateZExtOrTrunc(NewOperands[0], I->getType());
break;
case Instruction::FPToSI:
NewV = IRB.CreateSExtOrTrunc(NewOperands[0], I->getType());
break;
case Instruction::FCmp: {
CmpInst::Predicate P = mapFCmpPred(cast<CmpInst>(I)->getPredicate());
assert(P != CmpInst::BAD_ICMP_PREDICATE && "Unhandled predicate!");
NewV = IRB.CreateICmp(P, NewOperands[0], NewOperands[1], I->getName());
break;
}
case Instruction::UIToFP:
NewV = IRB.CreateZExtOrTrunc(NewOperands[0], ToTy);
break;
case Instruction::SIToFP:
NewV = IRB.CreateSExtOrTrunc(NewOperands[0], ToTy);
break;
case Instruction::FAdd:
case Instruction::FSub:
case Instruction::FMul:
NewV = IRB.CreateBinOp(mapBinOpcode(I->getOpcode()),
NewOperands[0], NewOperands[1],
I->getName());
break;
}
// If we're a root instruction, RAUW.
if (Roots.count(I))
I->replaceAllUsesWith(NewV);
ConvertedInsts[I] = NewV;
return NewV;
}
// Perform dead code elimination on the instructions we just modified.
void Float2Int::cleanup() {
for (auto &I : make_range(ConvertedInsts.rbegin(), ConvertedInsts.rend()))
I.first->eraseFromParent();
}
bool Float2Int::runOnFunction(Function &F) {
if (skipOptnoneFunction(F))
return false;
DEBUG(dbgs() << "F2I: Looking at function " << F.getName() << "\n");
// Clear out all state.
ECs = EquivalenceClasses<Instruction*>();
SeenInsts.clear();
ConvertedInsts.clear();
Roots.clear();
Ctx = &F.getParent()->getContext();
findRoots(F, Roots);
walkBackwards(Roots);
walkForwards();
bool Modified = validateAndTransform();
if (Modified)
cleanup();
return Modified;
}
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FunctionPass *llvm::createFloat2IntPass() { return new Float2Int(); }