//===-- LoopUnroll.cpp - Loop unroller pass -------------------------------===//
//
// The LLVM Compiler Infrastructure
//
// This file is distributed under the University of Illinois Open Source
// License. See LICENSE.TXT for details.
//
//===----------------------------------------------------------------------===//
//
// This pass implements a simple loop unroller. It works best when loops have
// been canonicalized by the -indvars pass, allowing it to determine the trip
// counts of loops easily.
//===----------------------------------------------------------------------===//
#include "llvm/Transforms/Scalar/LoopUnrollPass.h"
#include "llvm/ADT/SetVector.h"
#include "llvm/Analysis/AssumptionCache.h"
#include "llvm/Analysis/CodeMetrics.h"
#include "llvm/Analysis/GlobalsModRef.h"
#include "llvm/Analysis/InstructionSimplify.h"
#include "llvm/Analysis/LoopPass.h"
#include "llvm/Analysis/LoopUnrollAnalyzer.h"
#include "llvm/Analysis/OptimizationDiagnosticInfo.h"
#include "llvm/Analysis/ScalarEvolution.h"
#include "llvm/Analysis/ScalarEvolutionExpressions.h"
#include "llvm/IR/DataLayout.h"
#include "llvm/IR/Dominators.h"
#include "llvm/IR/InstVisitor.h"
#include "llvm/IR/IntrinsicInst.h"
#include "llvm/IR/Metadata.h"
#include "llvm/Support/CommandLine.h"
#include "llvm/Support/Debug.h"
#include "llvm/Support/raw_ostream.h"
#include "llvm/Transforms/Scalar.h"
#include "llvm/Transforms/Scalar/LoopPassManager.h"
#include "llvm/Transforms/Utils/LoopUtils.h"
#include "llvm/Transforms/Utils/UnrollLoop.h"
#include <climits>
#include <utility>
using namespace llvm;
#define DEBUG_TYPE "loop-unroll"
static cl::opt<unsigned>
UnrollThreshold("unroll-threshold", cl::Hidden,
cl::desc("The cost threshold for loop unrolling"));
static cl::opt<unsigned> UnrollPartialThreshold(
"unroll-partial-threshold", cl::Hidden,
cl::desc("The cost threshold for partial loop unrolling"));
static cl::opt<unsigned> UnrollMaxPercentThresholdBoost(
"unroll-max-percent-threshold-boost", cl::init(400), cl::Hidden,
cl::desc("The maximum 'boost' (represented as a percentage >= 100) applied "
"to the threshold when aggressively unrolling a loop due to the "
"dynamic cost savings. If completely unrolling a loop will reduce "
"the total runtime from X to Y, we boost the loop unroll "
"threshold to DefaultThreshold*std::min(MaxPercentThresholdBoost, "
"X/Y). This limit avoids excessive code bloat."));
static cl::opt<unsigned> UnrollMaxIterationsCountToAnalyze(
"unroll-max-iteration-count-to-analyze", cl::init(10), cl::Hidden,
cl::desc("Don't allow loop unrolling to simulate more than this number of"
"iterations when checking full unroll profitability"));
static cl::opt<unsigned> UnrollCount(
"unroll-count", cl::Hidden,
cl::desc("Use this unroll count for all loops including those with "
"unroll_count pragma values, for testing purposes"));
static cl::opt<unsigned> UnrollMaxCount(
"unroll-max-count", cl::Hidden,
cl::desc("Set the max unroll count for partial and runtime unrolling, for"
"testing purposes"));
static cl::opt<unsigned> UnrollFullMaxCount(
"unroll-full-max-count", cl::Hidden,
cl::desc(
"Set the max unroll count for full unrolling, for testing purposes"));
static cl::opt<bool>
UnrollAllowPartial("unroll-allow-partial", cl::Hidden,
cl::desc("Allows loops to be partially unrolled until "
"-unroll-threshold loop size is reached."));
static cl::opt<bool> UnrollAllowRemainder(
"unroll-allow-remainder", cl::Hidden,
cl::desc("Allow generation of a loop remainder (extra iterations) "
"when unrolling a loop."));
static cl::opt<bool>
UnrollRuntime("unroll-runtime", cl::ZeroOrMore, cl::Hidden,
cl::desc("Unroll loops with run-time trip counts"));
static cl::opt<unsigned> UnrollMaxUpperBound(
"unroll-max-upperbound", cl::init(8), cl::Hidden,
cl::desc(
"The max of trip count upper bound that is considered in unrolling"));
static cl::opt<unsigned> PragmaUnrollThreshold(
"pragma-unroll-threshold", cl::init(16 * 1024), cl::Hidden,
cl::desc("Unrolled size limit for loops with an unroll(full) or "
"unroll_count pragma."));
static cl::opt<unsigned> FlatLoopTripCountThreshold(
"flat-loop-tripcount-threshold", cl::init(5), cl::Hidden,
cl::desc("If the runtime tripcount for the loop is lower than the "
"threshold, the loop is considered as flat and will be less "
"aggressively unrolled."));
static cl::opt<bool>
UnrollAllowPeeling("unroll-allow-peeling", cl::init(true), cl::Hidden,
cl::desc("Allows loops to be peeled when the dynamic "
"trip count is known to be low."));
// This option isn't ever intended to be enabled, it serves to allow
// experiments to check the assumptions about when this kind of revisit is
// necessary.
static cl::opt<bool> UnrollRevisitChildLoops(
"unroll-revisit-child-loops", cl::Hidden,
cl::desc("Enqueue and re-visit child loops in the loop PM after unrolling. "
"This shouldn't typically be needed as child loops (or their "
"clones) were already visited."));
/// A magic value for use with the Threshold parameter to indicate
/// that the loop unroll should be performed regardless of how much
/// code expansion would result.
static const unsigned NoThreshold = UINT_MAX;
/// Gather the various unrolling parameters based on the defaults, compiler
/// flags, TTI overrides and user specified parameters.
static TargetTransformInfo::UnrollingPreferences gatherUnrollingPreferences(
Loop *L, const TargetTransformInfo &TTI, int OptLevel,
Optional<unsigned> UserThreshold, Optional<unsigned> UserCount,
Optional<bool> UserAllowPartial, Optional<bool> UserRuntime,
Optional<bool> UserUpperBound) {
TargetTransformInfo::UnrollingPreferences UP;
// Set up the defaults
UP.Threshold = OptLevel > 2 ? 300 : 150;
UP.MaxPercentThresholdBoost = 400;
UP.OptSizeThreshold = 0;
UP.PartialThreshold = 150;
UP.PartialOptSizeThreshold = 0;
UP.Count = 0;
UP.PeelCount = 0;
UP.DefaultUnrollRuntimeCount = 8;
UP.MaxCount = UINT_MAX;
UP.FullUnrollMaxCount = UINT_MAX;
UP.BEInsns = 2;
UP.Partial = false;
UP.Runtime = false;
UP.AllowRemainder = true;
UP.AllowExpensiveTripCount = false;
UP.Force = false;
UP.UpperBound = false;
UP.AllowPeeling = true;
// Override with any target specific settings
TTI.getUnrollingPreferences(L, UP);
// Apply size attributes
if (L->getHeader()->getParent()->optForSize()) {
UP.Threshold = UP.OptSizeThreshold;
UP.PartialThreshold = UP.PartialOptSizeThreshold;
}
// Apply any user values specified by cl::opt
if (UnrollThreshold.getNumOccurrences() > 0)
UP.Threshold = UnrollThreshold;
if (UnrollPartialThreshold.getNumOccurrences() > 0)
UP.PartialThreshold = UnrollPartialThreshold;
if (UnrollMaxPercentThresholdBoost.getNumOccurrences() > 0)
UP.MaxPercentThresholdBoost = UnrollMaxPercentThresholdBoost;
if (UnrollMaxCount.getNumOccurrences() > 0)
UP.MaxCount = UnrollMaxCount;
if (UnrollFullMaxCount.getNumOccurrences() > 0)
UP.FullUnrollMaxCount = UnrollFullMaxCount;
if (UnrollAllowPartial.getNumOccurrences() > 0)
UP.Partial = UnrollAllowPartial;
if (UnrollAllowRemainder.getNumOccurrences() > 0)
UP.AllowRemainder = UnrollAllowRemainder;
if (UnrollRuntime.getNumOccurrences() > 0)
UP.Runtime = UnrollRuntime;
if (UnrollMaxUpperBound == 0)
UP.UpperBound = false;
if (UnrollAllowPeeling.getNumOccurrences() > 0)
UP.AllowPeeling = UnrollAllowPeeling;
// Apply user values provided by argument
if (UserThreshold.hasValue()) {
UP.Threshold = *UserThreshold;
UP.PartialThreshold = *UserThreshold;
}
if (UserCount.hasValue())
UP.Count = *UserCount;
if (UserAllowPartial.hasValue())
UP.Partial = *UserAllowPartial;
if (UserRuntime.hasValue())
UP.Runtime = *UserRuntime;
if (UserUpperBound.hasValue())
UP.UpperBound = *UserUpperBound;
return UP;
}
namespace {
/// A struct to densely store the state of an instruction after unrolling at
/// each iteration.
///
/// This is designed to work like a tuple of <Instruction *, int> for the
/// purposes of hashing and lookup, but to be able to associate two boolean
/// states with each key.
struct UnrolledInstState {
Instruction *I;
int Iteration : 30;
unsigned IsFree : 1;
unsigned IsCounted : 1;
};
/// Hashing and equality testing for a set of the instruction states.
struct UnrolledInstStateKeyInfo {
typedef DenseMapInfo<Instruction *> PtrInfo;
typedef DenseMapInfo<std::pair<Instruction *, int>> PairInfo;
static inline UnrolledInstState getEmptyKey() {
return {PtrInfo::getEmptyKey(), 0, 0, 0};
}
static inline UnrolledInstState getTombstoneKey() {
return {PtrInfo::getTombstoneKey(), 0, 0, 0};
}
static inline unsigned getHashValue(const UnrolledInstState &S) {
return PairInfo::getHashValue({S.I, S.Iteration});
}
static inline bool isEqual(const UnrolledInstState &LHS,
const UnrolledInstState &RHS) {
return PairInfo::isEqual({LHS.I, LHS.Iteration}, {RHS.I, RHS.Iteration});
}
};
}
namespace {
struct EstimatedUnrollCost {
/// \brief The estimated cost after unrolling.
unsigned UnrolledCost;
/// \brief The estimated dynamic cost of executing the instructions in the
/// rolled form.
unsigned RolledDynamicCost;
};
}
/// \brief Figure out if the loop is worth full unrolling.
///
/// Complete loop unrolling can make some loads constant, and we need to know
/// if that would expose any further optimization opportunities. This routine
/// estimates this optimization. It computes cost of unrolled loop
/// (UnrolledCost) and dynamic cost of the original loop (RolledDynamicCost). By
/// dynamic cost we mean that we won't count costs of blocks that are known not
/// to be executed (i.e. if we have a branch in the loop and we know that at the
/// given iteration its condition would be resolved to true, we won't add up the
/// cost of the 'false'-block).
/// \returns Optional value, holding the RolledDynamicCost and UnrolledCost. If
/// the analysis failed (no benefits expected from the unrolling, or the loop is
/// too big to analyze), the returned value is None.
static Optional<EstimatedUnrollCost>
analyzeLoopUnrollCost(const Loop *L, unsigned TripCount, DominatorTree &DT,
ScalarEvolution &SE, const TargetTransformInfo &TTI,
unsigned MaxUnrolledLoopSize) {
// We want to be able to scale offsets by the trip count and add more offsets
// to them without checking for overflows, and we already don't want to
// analyze *massive* trip counts, so we force the max to be reasonably small.
assert(UnrollMaxIterationsCountToAnalyze < (INT_MAX / 2) &&
"The unroll iterations max is too large!");
// Only analyze inner loops. We can't properly estimate cost of nested loops
// and we won't visit inner loops again anyway.
if (!L->empty())
return None;
// Don't simulate loops with a big or unknown tripcount
if (!UnrollMaxIterationsCountToAnalyze || !TripCount ||
TripCount > UnrollMaxIterationsCountToAnalyze)
return None;
SmallSetVector<BasicBlock *, 16> BBWorklist;
SmallSetVector<std::pair<BasicBlock *, BasicBlock *>, 4> ExitWorklist;
DenseMap<Value *, Constant *> SimplifiedValues;
SmallVector<std::pair<Value *, Constant *>, 4> SimplifiedInputValues;
// The estimated cost of the unrolled form of the loop. We try to estimate
// this by simplifying as much as we can while computing the estimate.
unsigned UnrolledCost = 0;
// We also track the estimated dynamic (that is, actually executed) cost in
// the rolled form. This helps identify cases when the savings from unrolling
// aren't just exposing dead control flows, but actual reduced dynamic
// instructions due to the simplifications which we expect to occur after
// unrolling.
unsigned RolledDynamicCost = 0;
// We track the simplification of each instruction in each iteration. We use
// this to recursively merge costs into the unrolled cost on-demand so that
// we don't count the cost of any dead code. This is essentially a map from
// <instruction, int> to <bool, bool>, but stored as a densely packed struct.
DenseSet<UnrolledInstState, UnrolledInstStateKeyInfo> InstCostMap;
// A small worklist used to accumulate cost of instructions from each
// observable and reached root in the loop.
SmallVector<Instruction *, 16> CostWorklist;
// PHI-used worklist used between iterations while accumulating cost.
SmallVector<Instruction *, 4> PHIUsedList;
// Helper function to accumulate cost for instructions in the loop.
auto AddCostRecursively = [&](Instruction &RootI, int Iteration) {
assert(Iteration >= 0 && "Cannot have a negative iteration!");
assert(CostWorklist.empty() && "Must start with an empty cost list");
assert(PHIUsedList.empty() && "Must start with an empty phi used list");
CostWorklist.push_back(&RootI);
for (;; --Iteration) {
do {
Instruction *I = CostWorklist.pop_back_val();
// InstCostMap only uses I and Iteration as a key, the other two values
// don't matter here.
auto CostIter = InstCostMap.find({I, Iteration, 0, 0});
if (CostIter == InstCostMap.end())
// If an input to a PHI node comes from a dead path through the loop
// we may have no cost data for it here. What that actually means is
// that it is free.
continue;
auto &Cost = *CostIter;
if (Cost.IsCounted)
// Already counted this instruction.
continue;
// Mark that we are counting the cost of this instruction now.
Cost.IsCounted = true;
// If this is a PHI node in the loop header, just add it to the PHI set.
if (auto *PhiI = dyn_cast<PHINode>(I))
if (PhiI->getParent() == L->getHeader()) {
assert(Cost.IsFree && "Loop PHIs shouldn't be evaluated as they "
"inherently simplify during unrolling.");
if (Iteration == 0)
continue;
// Push the incoming value from the backedge into the PHI used list
// if it is an in-loop instruction. We'll use this to populate the
// cost worklist for the next iteration (as we count backwards).
if (auto *OpI = dyn_cast<Instruction>(
PhiI->getIncomingValueForBlock(L->getLoopLatch())))
if (L->contains(OpI))
PHIUsedList.push_back(OpI);
continue;
}
// First accumulate the cost of this instruction.
if (!Cost.IsFree) {
UnrolledCost += TTI.getUserCost(I);
DEBUG(dbgs() << "Adding cost of instruction (iteration " << Iteration
<< "): ");
DEBUG(I->dump());
}
// We must count the cost of every operand which is not free,
// recursively. If we reach a loop PHI node, simply add it to the set
// to be considered on the next iteration (backwards!).
for (Value *Op : I->operands()) {
// Check whether this operand is free due to being a constant or
// outside the loop.
auto *OpI = dyn_cast<Instruction>(Op);
if (!OpI || !L->contains(OpI))
continue;
// Otherwise accumulate its cost.
CostWorklist.push_back(OpI);
}
} while (!CostWorklist.empty());
if (PHIUsedList.empty())
// We've exhausted the search.
break;
assert(Iteration > 0 &&
"Cannot track PHI-used values past the first iteration!");
CostWorklist.append(PHIUsedList.begin(), PHIUsedList.end());
PHIUsedList.clear();
}
};
// Ensure that we don't violate the loop structure invariants relied on by
// this analysis.
assert(L->isLoopSimplifyForm() && "Must put loop into normal form first.");
assert(L->isLCSSAForm(DT) &&
"Must have loops in LCSSA form to track live-out values.");
DEBUG(dbgs() << "Starting LoopUnroll profitability analysis...\n");
// Simulate execution of each iteration of the loop counting instructions,
// which would be simplified.
// Since the same load will take different values on different iterations,
// we literally have to go through all loop's iterations.
for (unsigned Iteration = 0; Iteration < TripCount; ++Iteration) {
DEBUG(dbgs() << " Analyzing iteration " << Iteration << "\n");
// Prepare for the iteration by collecting any simplified entry or backedge
// inputs.
for (Instruction &I : *L->getHeader()) {
auto *PHI = dyn_cast<PHINode>(&I);
if (!PHI)
break;
// The loop header PHI nodes must have exactly two input: one from the
// loop preheader and one from the loop latch.
assert(
PHI->getNumIncomingValues() == 2 &&
"Must have an incoming value only for the preheader and the latch.");
Value *V = PHI->getIncomingValueForBlock(
Iteration == 0 ? L->getLoopPreheader() : L->getLoopLatch());
Constant *C = dyn_cast<Constant>(V);
if (Iteration != 0 && !C)
C = SimplifiedValues.lookup(V);
if (C)
SimplifiedInputValues.push_back({PHI, C});
}
// Now clear and re-populate the map for the next iteration.
SimplifiedValues.clear();
while (!SimplifiedInputValues.empty())
SimplifiedValues.insert(SimplifiedInputValues.pop_back_val());
UnrolledInstAnalyzer Analyzer(Iteration, SimplifiedValues, SE, L);
BBWorklist.clear();
BBWorklist.insert(L->getHeader());
// Note that we *must not* cache the size, this loop grows the worklist.
for (unsigned Idx = 0; Idx != BBWorklist.size(); ++Idx) {
BasicBlock *BB = BBWorklist[Idx];
// Visit all instructions in the given basic block and try to simplify
// it. We don't change the actual IR, just count optimization
// opportunities.
for (Instruction &I : *BB) {
if (isa<DbgInfoIntrinsic>(I))
continue;
// Track this instruction's expected baseline cost when executing the
// rolled loop form.
RolledDynamicCost += TTI.getUserCost(&I);
// Visit the instruction to analyze its loop cost after unrolling,
// and if the visitor returns true, mark the instruction as free after
// unrolling and continue.
bool IsFree = Analyzer.visit(I);
bool Inserted = InstCostMap.insert({&I, (int)Iteration,
(unsigned)IsFree,
/*IsCounted*/ false}).second;
(void)Inserted;
assert(Inserted && "Cannot have a state for an unvisited instruction!");
if (IsFree)
continue;
// Can't properly model a cost of a call.
// FIXME: With a proper cost model we should be able to do it.
if(isa<CallInst>(&I))
return None;
// If the instruction might have a side-effect recursively account for
// the cost of it and all the instructions leading up to it.
if (I.mayHaveSideEffects())
AddCostRecursively(I, Iteration);
// If unrolled body turns out to be too big, bail out.
if (UnrolledCost > MaxUnrolledLoopSize) {
DEBUG(dbgs() << " Exceeded threshold.. exiting.\n"
<< " UnrolledCost: " << UnrolledCost
<< ", MaxUnrolledLoopSize: " << MaxUnrolledLoopSize
<< "\n");
return None;
}
}
TerminatorInst *TI = BB->getTerminator();
// Add in the live successors by first checking whether we have terminator
// that may be simplified based on the values simplified by this call.
BasicBlock *KnownSucc = nullptr;
if (BranchInst *BI = dyn_cast<BranchInst>(TI)) {
if (BI->isConditional()) {
if (Constant *SimpleCond =
SimplifiedValues.lookup(BI->getCondition())) {
// Just take the first successor if condition is undef
if (isa<UndefValue>(SimpleCond))
KnownSucc = BI->getSuccessor(0);
else if (ConstantInt *SimpleCondVal =
dyn_cast<ConstantInt>(SimpleCond))
KnownSucc = BI->getSuccessor(SimpleCondVal->isZero() ? 1 : 0);
}
}
} else if (SwitchInst *SI = dyn_cast<SwitchInst>(TI)) {
if (Constant *SimpleCond =
SimplifiedValues.lookup(SI->getCondition())) {
// Just take the first successor if condition is undef
if (isa<UndefValue>(SimpleCond))
KnownSucc = SI->getSuccessor(0);
else if (ConstantInt *SimpleCondVal =
dyn_cast<ConstantInt>(SimpleCond))
KnownSucc = SI->findCaseValue(SimpleCondVal)->getCaseSuccessor();
}
}
if (KnownSucc) {
if (L->contains(KnownSucc))
BBWorklist.insert(KnownSucc);
else
ExitWorklist.insert({BB, KnownSucc});
continue;
}
// Add BB's successors to the worklist.
for (BasicBlock *Succ : successors(BB))
if (L->contains(Succ))
BBWorklist.insert(Succ);
else
ExitWorklist.insert({BB, Succ});
AddCostRecursively(*TI, Iteration);
}
// If we found no optimization opportunities on the first iteration, we
// won't find them on later ones too.
if (UnrolledCost == RolledDynamicCost) {
DEBUG(dbgs() << " No opportunities found.. exiting.\n"
<< " UnrolledCost: " << UnrolledCost << "\n");
return None;
}
}
while (!ExitWorklist.empty()) {
BasicBlock *ExitingBB, *ExitBB;
std::tie(ExitingBB, ExitBB) = ExitWorklist.pop_back_val();
for (Instruction &I : *ExitBB) {
auto *PN = dyn_cast<PHINode>(&I);
if (!PN)
break;
Value *Op = PN->getIncomingValueForBlock(ExitingBB);
if (auto *OpI = dyn_cast<Instruction>(Op))
if (L->contains(OpI))
AddCostRecursively(*OpI, TripCount - 1);
}
}
DEBUG(dbgs() << "Analysis finished:\n"
<< "UnrolledCost: " << UnrolledCost << ", "
<< "RolledDynamicCost: " << RolledDynamicCost << "\n");
return {{UnrolledCost, RolledDynamicCost}};
}
/// ApproximateLoopSize - Approximate the size of the loop.
static unsigned ApproximateLoopSize(const Loop *L, unsigned &NumCalls,
bool &NotDuplicatable, bool &Convergent,
const TargetTransformInfo &TTI,
AssumptionCache *AC, unsigned BEInsns) {
SmallPtrSet<const Value *, 32> EphValues;
CodeMetrics::collectEphemeralValues(L, AC, EphValues);
CodeMetrics Metrics;
for (BasicBlock *BB : L->blocks())
Metrics.analyzeBasicBlock(BB, TTI, EphValues);
NumCalls = Metrics.NumInlineCandidates;
NotDuplicatable = Metrics.notDuplicatable;
Convergent = Metrics.convergent;
unsigned LoopSize = Metrics.NumInsts;
// Don't allow an estimate of size zero. This would allows unrolling of loops
// with huge iteration counts, which is a compile time problem even if it's
// not a problem for code quality. Also, the code using this size may assume
// that each loop has at least three instructions (likely a conditional
// branch, a comparison feeding that branch, and some kind of loop increment
// feeding that comparison instruction).
LoopSize = std::max(LoopSize, BEInsns + 1);
return LoopSize;
}
// Returns the loop hint metadata node with the given name (for example,
// "llvm.loop.unroll.count"). If no such metadata node exists, then nullptr is
// returned.
static MDNode *GetUnrollMetadataForLoop(const Loop *L, StringRef Name) {
if (MDNode *LoopID = L->getLoopID())
return GetUnrollMetadata(LoopID, Name);
return nullptr;
}
// Returns true if the loop has an unroll(full) pragma.
static bool HasUnrollFullPragma(const Loop *L) {
return GetUnrollMetadataForLoop(L, "llvm.loop.unroll.full");
}
// Returns true if the loop has an unroll(enable) pragma. This metadata is used
// for both "#pragma unroll" and "#pragma clang loop unroll(enable)" directives.
static bool HasUnrollEnablePragma(const Loop *L) {
return GetUnrollMetadataForLoop(L, "llvm.loop.unroll.enable");
}
// Returns true if the loop has an unroll(disable) pragma.
static bool HasUnrollDisablePragma(const Loop *L) {
return GetUnrollMetadataForLoop(L, "llvm.loop.unroll.disable");
}
// Returns true if the loop has an runtime unroll(disable) pragma.
static bool HasRuntimeUnrollDisablePragma(const Loop *L) {
return GetUnrollMetadataForLoop(L, "llvm.loop.unroll.runtime.disable");
}
// If loop has an unroll_count pragma return the (necessarily
// positive) value from the pragma. Otherwise return 0.
static unsigned UnrollCountPragmaValue(const Loop *L) {
MDNode *MD = GetUnrollMetadataForLoop(L, "llvm.loop.unroll.count");
if (MD) {
assert(MD->getNumOperands() == 2 &&
"Unroll count hint metadata should have two operands.");
unsigned Count =
mdconst::extract<ConstantInt>(MD->getOperand(1))->getZExtValue();
assert(Count >= 1 && "Unroll count must be positive.");
return Count;
}
return 0;
}
// Remove existing unroll metadata and add unroll disable metadata to
// indicate the loop has already been unrolled. This prevents a loop
// from being unrolled more than is directed by a pragma if the loop
// unrolling pass is run more than once (which it generally is).
static void SetLoopAlreadyUnrolled(Loop *L) {
MDNode *LoopID = L->getLoopID();
// First remove any existing loop unrolling metadata.
SmallVector<Metadata *, 4> MDs;
// Reserve first location for self reference to the LoopID metadata node.
MDs.push_back(nullptr);
if (LoopID) {
for (unsigned i = 1, ie = LoopID->getNumOperands(); i < ie; ++i) {
bool IsUnrollMetadata = false;
MDNode *MD = dyn_cast<MDNode>(LoopID->getOperand(i));
if (MD) {
const MDString *S = dyn_cast<MDString>(MD->getOperand(0));
IsUnrollMetadata = S && S->getString().startswith("llvm.loop.unroll.");
}
if (!IsUnrollMetadata)
MDs.push_back(LoopID->getOperand(i));
}
}
// Add unroll(disable) metadata to disable future unrolling.
LLVMContext &Context = L->getHeader()->getContext();
SmallVector<Metadata *, 1> DisableOperands;
DisableOperands.push_back(MDString::get(Context, "llvm.loop.unroll.disable"));
MDNode *DisableNode = MDNode::get(Context, DisableOperands);
MDs.push_back(DisableNode);
MDNode *NewLoopID = MDNode::get(Context, MDs);
// Set operand 0 to refer to the loop id itself.
NewLoopID->replaceOperandWith(0, NewLoopID);
L->setLoopID(NewLoopID);
}
// Computes the boosting factor for complete unrolling.
// If fully unrolling the loop would save a lot of RolledDynamicCost, it would
// be beneficial to fully unroll the loop even if unrolledcost is large. We
// use (RolledDynamicCost / UnrolledCost) to model the unroll benefits to adjust
// the unroll threshold.
static unsigned getFullUnrollBoostingFactor(const EstimatedUnrollCost &Cost,
unsigned MaxPercentThresholdBoost) {
if (Cost.RolledDynamicCost >= UINT_MAX / 100)
return 100;
else if (Cost.UnrolledCost != 0)
// The boosting factor is RolledDynamicCost / UnrolledCost
return std::min(100 * Cost.RolledDynamicCost / Cost.UnrolledCost,
MaxPercentThresholdBoost);
else
return MaxPercentThresholdBoost;
}
// Returns loop size estimation for unrolled loop.
static uint64_t getUnrolledLoopSize(
unsigned LoopSize,
TargetTransformInfo::UnrollingPreferences &UP) {
assert(LoopSize >= UP.BEInsns && "LoopSize should not be less than BEInsns!");
return (uint64_t)(LoopSize - UP.BEInsns) * UP.Count + UP.BEInsns;
}
// Returns true if unroll count was set explicitly.
// Calculates unroll count and writes it to UP.Count.
static bool computeUnrollCount(
Loop *L, const TargetTransformInfo &TTI, DominatorTree &DT, LoopInfo *LI,
ScalarEvolution *SE, OptimizationRemarkEmitter *ORE, unsigned &TripCount,
unsigned MaxTripCount, unsigned &TripMultiple, unsigned LoopSize,
TargetTransformInfo::UnrollingPreferences &UP, bool &UseUpperBound) {
// Check for explicit Count.
// 1st priority is unroll count set by "unroll-count" option.
bool UserUnrollCount = UnrollCount.getNumOccurrences() > 0;
if (UserUnrollCount) {
UP.Count = UnrollCount;
UP.AllowExpensiveTripCount = true;
UP.Force = true;
if (UP.AllowRemainder && getUnrolledLoopSize(LoopSize, UP) < UP.Threshold)
return true;
}
// 2nd priority is unroll count set by pragma.
unsigned PragmaCount = UnrollCountPragmaValue(L);
if (PragmaCount > 0) {
UP.Count = PragmaCount;
UP.Runtime = true;
UP.AllowExpensiveTripCount = true;
UP.Force = true;
if (UP.AllowRemainder &&
getUnrolledLoopSize(LoopSize, UP) < PragmaUnrollThreshold)
return true;
}
bool PragmaFullUnroll = HasUnrollFullPragma(L);
if (PragmaFullUnroll && TripCount != 0) {
UP.Count = TripCount;
if (getUnrolledLoopSize(LoopSize, UP) < PragmaUnrollThreshold)
return false;
}
bool PragmaEnableUnroll = HasUnrollEnablePragma(L);
bool ExplicitUnroll = PragmaCount > 0 || PragmaFullUnroll ||
PragmaEnableUnroll || UserUnrollCount;
if (ExplicitUnroll && TripCount != 0) {
// If the loop has an unrolling pragma, we want to be more aggressive with
// unrolling limits. Set thresholds to at least the PragmaThreshold value
// which is larger than the default limits.
UP.Threshold = std::max<unsigned>(UP.Threshold, PragmaUnrollThreshold);
UP.PartialThreshold =
std::max<unsigned>(UP.PartialThreshold, PragmaUnrollThreshold);
}
// 3rd priority is full unroll count.
// Full unroll makes sense only when TripCount or its upper bound could be
// statically calculated.
// Also we need to check if we exceed FullUnrollMaxCount.
// If using the upper bound to unroll, TripMultiple should be set to 1 because
// we do not know when loop may exit.
// MaxTripCount and ExactTripCount cannot both be non zero since we only
// compute the former when the latter is zero.
unsigned ExactTripCount = TripCount;
assert((ExactTripCount == 0 || MaxTripCount == 0) &&
"ExtractTripCound and MaxTripCount cannot both be non zero.");
unsigned FullUnrollTripCount = ExactTripCount ? ExactTripCount : MaxTripCount;
UP.Count = FullUnrollTripCount;
if (FullUnrollTripCount && FullUnrollTripCount <= UP.FullUnrollMaxCount) {
// When computing the unrolled size, note that BEInsns are not replicated
// like the rest of the loop body.
if (getUnrolledLoopSize(LoopSize, UP) < UP.Threshold) {
UseUpperBound = (MaxTripCount == FullUnrollTripCount);
TripCount = FullUnrollTripCount;
TripMultiple = UP.UpperBound ? 1 : TripMultiple;
return ExplicitUnroll;
} else {
// The loop isn't that small, but we still can fully unroll it if that
// helps to remove a significant number of instructions.
// To check that, run additional analysis on the loop.
if (Optional<EstimatedUnrollCost> Cost = analyzeLoopUnrollCost(
L, FullUnrollTripCount, DT, *SE, TTI,
UP.Threshold * UP.MaxPercentThresholdBoost / 100)) {
unsigned Boost =
getFullUnrollBoostingFactor(*Cost, UP.MaxPercentThresholdBoost);
if (Cost->UnrolledCost < UP.Threshold * Boost / 100) {
UseUpperBound = (MaxTripCount == FullUnrollTripCount);
TripCount = FullUnrollTripCount;
TripMultiple = UP.UpperBound ? 1 : TripMultiple;
return ExplicitUnroll;
}
}
}
}
// 4th priority is loop peeling
computePeelCount(L, LoopSize, UP, TripCount);
if (UP.PeelCount) {
UP.Runtime = false;
UP.Count = 1;
return ExplicitUnroll;
}
// 5th priority is partial unrolling.
// Try partial unroll only when TripCount could be staticaly calculated.
if (TripCount) {
UP.Partial |= ExplicitUnroll;
if (!UP.Partial) {
DEBUG(dbgs() << " will not try to unroll partially because "
<< "-unroll-allow-partial not given\n");
UP.Count = 0;
return false;
}
if (UP.Count == 0)
UP.Count = TripCount;
if (UP.PartialThreshold != NoThreshold) {
// Reduce unroll count to be modulo of TripCount for partial unrolling.
if (getUnrolledLoopSize(LoopSize, UP) > UP.PartialThreshold)
UP.Count =
(std::max(UP.PartialThreshold, UP.BEInsns + 1) - UP.BEInsns) /
(LoopSize - UP.BEInsns);
if (UP.Count > UP.MaxCount)
UP.Count = UP.MaxCount;
while (UP.Count != 0 && TripCount % UP.Count != 0)
UP.Count--;
if (UP.AllowRemainder && UP.Count <= 1) {
// If there is no Count that is modulo of TripCount, set Count to
// largest power-of-two factor that satisfies the threshold limit.
// As we'll create fixup loop, do the type of unrolling only if
// remainder loop is allowed.
UP.Count = UP.DefaultUnrollRuntimeCount;
while (UP.Count != 0 &&
getUnrolledLoopSize(LoopSize, UP) > UP.PartialThreshold)
UP.Count >>= 1;
}
if (UP.Count < 2) {
if (PragmaEnableUnroll)
ORE->emit(
OptimizationRemarkMissed(DEBUG_TYPE, "UnrollAsDirectedTooLarge",
L->getStartLoc(), L->getHeader())
<< "Unable to unroll loop as directed by unroll(enable) pragma "
"because unrolled size is too large.");
UP.Count = 0;
}
} else {
UP.Count = TripCount;
}
if ((PragmaFullUnroll || PragmaEnableUnroll) && TripCount &&
UP.Count != TripCount)
ORE->emit(
OptimizationRemarkMissed(DEBUG_TYPE, "FullUnrollAsDirectedTooLarge",
L->getStartLoc(), L->getHeader())
<< "Unable to fully unroll loop as directed by unroll pragma because "
"unrolled size is too large.");
return ExplicitUnroll;
}
assert(TripCount == 0 &&
"All cases when TripCount is constant should be covered here.");
if (PragmaFullUnroll)
ORE->emit(
OptimizationRemarkMissed(DEBUG_TYPE,
"CantFullUnrollAsDirectedRuntimeTripCount",
L->getStartLoc(), L->getHeader())
<< "Unable to fully unroll loop as directed by unroll(full) pragma "
"because loop has a runtime trip count.");
// 6th priority is runtime unrolling.
// Don't unroll a runtime trip count loop when it is disabled.
if (HasRuntimeUnrollDisablePragma(L)) {
UP.Count = 0;
return false;
}
// Check if the runtime trip count is too small when profile is available.
if (L->getHeader()->getParent()->getEntryCount()) {
if (auto ProfileTripCount = getLoopEstimatedTripCount(L)) {
if (*ProfileTripCount < FlatLoopTripCountThreshold)
return false;
else
UP.AllowExpensiveTripCount = true;
}
}
// Reduce count based on the type of unrolling and the threshold values.
UP.Runtime |= PragmaEnableUnroll || PragmaCount > 0 || UserUnrollCount;
if (!UP.Runtime) {
DEBUG(dbgs() << " will not try to unroll loop with runtime trip count "
<< "-unroll-runtime not given\n");
UP.Count = 0;
return false;
}
if (UP.Count == 0)
UP.Count = UP.DefaultUnrollRuntimeCount;
// Reduce unroll count to be the largest power-of-two factor of
// the original count which satisfies the threshold limit.
while (UP.Count != 0 &&
getUnrolledLoopSize(LoopSize, UP) > UP.PartialThreshold)
UP.Count >>= 1;
#ifndef NDEBUG
unsigned OrigCount = UP.Count;
#endif
if (!UP.AllowRemainder && UP.Count != 0 && (TripMultiple % UP.Count) != 0) {
while (UP.Count != 0 && TripMultiple % UP.Count != 0)
UP.Count >>= 1;
DEBUG(dbgs() << "Remainder loop is restricted (that could architecture "
"specific or because the loop contains a convergent "
"instruction), so unroll count must divide the trip "
"multiple, "
<< TripMultiple << ". Reducing unroll count from "
<< OrigCount << " to " << UP.Count << ".\n");
using namespace ore;
if (PragmaCount > 0 && !UP.AllowRemainder)
ORE->emit(
OptimizationRemarkMissed(DEBUG_TYPE,
"DifferentUnrollCountFromDirected",
L->getStartLoc(), L->getHeader())
<< "Unable to unroll loop the number of times directed by "
"unroll_count pragma because remainder loop is restricted "
"(that could architecture specific or because the loop "
"contains a convergent instruction) and so must have an unroll "
"count that divides the loop trip multiple of "
<< NV("TripMultiple", TripMultiple) << ". Unrolling instead "
<< NV("UnrollCount", UP.Count) << " time(s).");
}
if (UP.Count > UP.MaxCount)
UP.Count = UP.MaxCount;
DEBUG(dbgs() << " partially unrolling with count: " << UP.Count << "\n");
if (UP.Count < 2)
UP.Count = 0;
return ExplicitUnroll;
}
static bool tryToUnrollLoop(Loop *L, DominatorTree &DT, LoopInfo *LI,
ScalarEvolution *SE, const TargetTransformInfo &TTI,
AssumptionCache &AC, OptimizationRemarkEmitter &ORE,
bool PreserveLCSSA, int OptLevel,
Optional<unsigned> ProvidedCount,
Optional<unsigned> ProvidedThreshold,
Optional<bool> ProvidedAllowPartial,
Optional<bool> ProvidedRuntime,
Optional<bool> ProvidedUpperBound) {
DEBUG(dbgs() << "Loop Unroll: F[" << L->getHeader()->getParent()->getName()
<< "] Loop %" << L->getHeader()->getName() << "\n");
if (HasUnrollDisablePragma(L))
return false;
if (!L->isLoopSimplifyForm()) {
DEBUG(
dbgs() << " Not unrolling loop which is not in loop-simplify form.\n");
return false;
}
unsigned NumInlineCandidates;
bool NotDuplicatable;
bool Convergent;
TargetTransformInfo::UnrollingPreferences UP = gatherUnrollingPreferences(
L, TTI, OptLevel, ProvidedThreshold, ProvidedCount, ProvidedAllowPartial,
ProvidedRuntime, ProvidedUpperBound);
// Exit early if unrolling is disabled.
if (UP.Threshold == 0 && (!UP.Partial || UP.PartialThreshold == 0))
return false;
unsigned LoopSize = ApproximateLoopSize(
L, NumInlineCandidates, NotDuplicatable, Convergent, TTI, &AC, UP.BEInsns);
DEBUG(dbgs() << " Loop Size = " << LoopSize << "\n");
if (NotDuplicatable) {
DEBUG(dbgs() << " Not unrolling loop which contains non-duplicatable"
<< " instructions.\n");
return false;
}
if (NumInlineCandidates != 0) {
DEBUG(dbgs() << " Not unrolling loop with inlinable calls.\n");
return false;
}
// Find trip count and trip multiple if count is not available
unsigned TripCount = 0;
unsigned MaxTripCount = 0;
unsigned TripMultiple = 1;
// If there are multiple exiting blocks but one of them is the latch, use the
// latch for the trip count estimation. Otherwise insist on a single exiting
// block for the trip count estimation.
BasicBlock *ExitingBlock = L->getLoopLatch();
if (!ExitingBlock || !L->isLoopExiting(ExitingBlock))
ExitingBlock = L->getExitingBlock();
if (ExitingBlock) {
TripCount = SE->getSmallConstantTripCount(L, ExitingBlock);
TripMultiple = SE->getSmallConstantTripMultiple(L, ExitingBlock);
}
// If the loop contains a convergent operation, the prelude we'd add
// to do the first few instructions before we hit the unrolled loop
// is unsafe -- it adds a control-flow dependency to the convergent
// operation. Therefore restrict remainder loop (try unrollig without).
//
// TODO: This is quite conservative. In practice, convergent_op()
// is likely to be called unconditionally in the loop. In this
// case, the program would be ill-formed (on most architectures)
// unless n were the same on all threads in a thread group.
// Assuming n is the same on all threads, any kind of unrolling is
// safe. But currently llvm's notion of convergence isn't powerful
// enough to express this.
if (Convergent)
UP.AllowRemainder = false;
// Try to find the trip count upper bound if we cannot find the exact trip
// count.
bool MaxOrZero = false;
if (!TripCount) {
MaxTripCount = SE->getSmallConstantMaxTripCount(L);
MaxOrZero = SE->isBackedgeTakenCountMaxOrZero(L);
// We can unroll by the upper bound amount if it's generally allowed or if
// we know that the loop is executed either the upper bound or zero times.
// (MaxOrZero unrolling keeps only the first loop test, so the number of
// loop tests remains the same compared to the non-unrolled version, whereas
// the generic upper bound unrolling keeps all but the last loop test so the
// number of loop tests goes up which may end up being worse on targets with
// constriained branch predictor resources so is controlled by an option.)
// In addition we only unroll small upper bounds.
if (!(UP.UpperBound || MaxOrZero) || MaxTripCount > UnrollMaxUpperBound) {
MaxTripCount = 0;
}
}
// computeUnrollCount() decides whether it is beneficial to use upper bound to
// fully unroll the loop.
bool UseUpperBound = false;
bool IsCountSetExplicitly =
computeUnrollCount(L, TTI, DT, LI, SE, &ORE, TripCount, MaxTripCount,
TripMultiple, LoopSize, UP, UseUpperBound);
if (!UP.Count)
return false;
// Unroll factor (Count) must be less or equal to TripCount.
if (TripCount && UP.Count > TripCount)
UP.Count = TripCount;
// Unroll the loop.
if (!UnrollLoop(L, UP.Count, TripCount, UP.Force, UP.Runtime,
UP.AllowExpensiveTripCount, UseUpperBound, MaxOrZero,
TripMultiple, UP.PeelCount, LI, SE, &DT, &AC, &ORE,
PreserveLCSSA))
return false;
// If loop has an unroll count pragma or unrolled by explicitly set count
// mark loop as unrolled to prevent unrolling beyond that requested.
// If the loop was peeled, we already "used up" the profile information
// we had, so we don't want to unroll or peel again.
if (IsCountSetExplicitly || UP.PeelCount)
SetLoopAlreadyUnrolled(L);
return true;
}
namespace {
class LoopUnroll : public LoopPass {
public:
static char ID; // Pass ID, replacement for typeid
LoopUnroll(int OptLevel = 2, Optional<unsigned> Threshold = None,
Optional<unsigned> Count = None,
Optional<bool> AllowPartial = None, Optional<bool> Runtime = None,
Optional<bool> UpperBound = None)
: LoopPass(ID), OptLevel(OptLevel), ProvidedCount(std::move(Count)),
ProvidedThreshold(Threshold), ProvidedAllowPartial(AllowPartial),
ProvidedRuntime(Runtime), ProvidedUpperBound(UpperBound) {
initializeLoopUnrollPass(*PassRegistry::getPassRegistry());
}
int OptLevel;
Optional<unsigned> ProvidedCount;
Optional<unsigned> ProvidedThreshold;
Optional<bool> ProvidedAllowPartial;
Optional<bool> ProvidedRuntime;
Optional<bool> ProvidedUpperBound;
bool runOnLoop(Loop *L, LPPassManager &) override {
if (skipLoop(L))
return false;
Function &F = *L->getHeader()->getParent();
auto &DT = getAnalysis<DominatorTreeWrapperPass>().getDomTree();
LoopInfo *LI = &getAnalysis<LoopInfoWrapperPass>().getLoopInfo();
ScalarEvolution *SE = &getAnalysis<ScalarEvolutionWrapperPass>().getSE();
const TargetTransformInfo &TTI =
getAnalysis<TargetTransformInfoWrapperPass>().getTTI(F);
auto &AC = getAnalysis<AssumptionCacheTracker>().getAssumptionCache(F);
// For the old PM, we can't use OptimizationRemarkEmitter as an analysis
// pass. Function analyses need to be preserved across loop transformations
// but ORE cannot be preserved (see comment before the pass definition).
OptimizationRemarkEmitter ORE(&F);
bool PreserveLCSSA = mustPreserveAnalysisID(LCSSAID);
return tryToUnrollLoop(L, DT, LI, SE, TTI, AC, ORE, PreserveLCSSA, OptLevel,
ProvidedCount, ProvidedThreshold,
ProvidedAllowPartial, ProvidedRuntime,
ProvidedUpperBound);
}
/// This transformation requires natural loop information & requires that
/// loop preheaders be inserted into the CFG...
///
void getAnalysisUsage(AnalysisUsage &AU) const override {
AU.addRequired<AssumptionCacheTracker>();
AU.addRequired<TargetTransformInfoWrapperPass>();
// FIXME: Loop passes are required to preserve domtree, and for now we just
// recreate dom info if anything gets unrolled.
getLoopAnalysisUsage(AU);
}
};
}
char LoopUnroll::ID = 0;
INITIALIZE_PASS_BEGIN(LoopUnroll, "loop-unroll", "Unroll loops", false, false)
INITIALIZE_PASS_DEPENDENCY(AssumptionCacheTracker)
INITIALIZE_PASS_DEPENDENCY(LoopPass)
INITIALIZE_PASS_DEPENDENCY(TargetTransformInfoWrapperPass)
INITIALIZE_PASS_END(LoopUnroll, "loop-unroll", "Unroll loops", false, false)
Pass *llvm::createLoopUnrollPass(int OptLevel, int Threshold, int Count,
int AllowPartial, int Runtime,
int UpperBound) {
// TODO: It would make more sense for this function to take the optionals
// directly, but that's dangerous since it would silently break out of tree
// callers.
return new LoopUnroll(
OptLevel, Threshold == -1 ? None : Optional<unsigned>(Threshold),
Count == -1 ? None : Optional<unsigned>(Count),
AllowPartial == -1 ? None : Optional<bool>(AllowPartial),
Runtime == -1 ? None : Optional<bool>(Runtime),
UpperBound == -1 ? None : Optional<bool>(UpperBound));
}
Pass *llvm::createSimpleLoopUnrollPass(int OptLevel) {
return llvm::createLoopUnrollPass(OptLevel, -1, -1, 0, 0, 0);
}
PreservedAnalyses LoopUnrollPass::run(Loop &L, LoopAnalysisManager &AM,
LoopStandardAnalysisResults &AR,
LPMUpdater &Updater) {
const auto &FAM =
AM.getResult<FunctionAnalysisManagerLoopProxy>(L, AR).getManager();
Function *F = L.getHeader()->getParent();
auto *ORE = FAM.getCachedResult<OptimizationRemarkEmitterAnalysis>(*F);
// FIXME: This should probably be optional rather than required.
if (!ORE)
report_fatal_error("LoopUnrollPass: OptimizationRemarkEmitterAnalysis not "
"cached at a higher level");
// Keep track of the previous loop structure so we can identify new loops
// created by unrolling.
Loop *ParentL = L.getParentLoop();
SmallPtrSet<Loop *, 4> OldLoops;
if (ParentL)
OldLoops.insert(ParentL->begin(), ParentL->end());
else
OldLoops.insert(AR.LI.begin(), AR.LI.end());
// The API here is quite complex to call, but there are only two interesting
// states we support: partial and full (or "simple") unrolling. However, to
// enable these things we actually pass "None" in for the optional to avoid
// providing an explicit choice.
Optional<bool> AllowPartialParam, RuntimeParam, UpperBoundParam;
if (!AllowPartialUnrolling)
AllowPartialParam = RuntimeParam = UpperBoundParam = false;
bool Changed = tryToUnrollLoop(
&L, AR.DT, &AR.LI, &AR.SE, AR.TTI, AR.AC, *ORE,
/*PreserveLCSSA*/ true, OptLevel, /*Count*/ None,
/*Threshold*/ None, AllowPartialParam, RuntimeParam, UpperBoundParam);
if (!Changed)
return PreservedAnalyses::all();
// The parent must not be damaged by unrolling!
#ifndef NDEBUG
if (ParentL)
ParentL->verifyLoop();
#endif
// Unrolling can do several things to introduce new loops into a loop nest:
// - Partial unrolling clones child loops within the current loop. If it
// uses a remainder, then it can also create any number of sibling loops.
// - Full unrolling clones child loops within the current loop but then
// removes the current loop making all of the children appear to be new
// sibling loops.
// - Loop peeling can directly introduce new sibling loops by peeling one
// iteration.
//
// When a new loop appears as a sibling loop, either from peeling an
// iteration or fully unrolling, its nesting structure has fundamentally
// changed and we want to revisit it to reflect that.
//
// When unrolling has removed the current loop, we need to tell the
// infrastructure that it is gone.
//
// Finally, we support a debugging/testing mode where we revisit child loops
// as well. These are not expected to require further optimizations as either
// they or the loop they were cloned from have been directly visited already.
// But the debugging mode allows us to check this assumption.
bool IsCurrentLoopValid = false;
SmallVector<Loop *, 4> SibLoops;
if (ParentL)
SibLoops.append(ParentL->begin(), ParentL->end());
else
SibLoops.append(AR.LI.begin(), AR.LI.end());
erase_if(SibLoops, [&](Loop *SibLoop) {
if (SibLoop == &L) {
IsCurrentLoopValid = true;
return true;
}
// Otherwise erase the loop from the list if it was in the old loops.
return OldLoops.count(SibLoop) != 0;
});
Updater.addSiblingLoops(SibLoops);
if (!IsCurrentLoopValid) {
Updater.markLoopAsDeleted(L);
} else {
// We can only walk child loops if the current loop remained valid.
if (UnrollRevisitChildLoops) {
// Walk *all* of the child loops. This is a highly speculative mode
// anyways so look for any simplifications that arose from partial
// unrolling or peeling off of iterations.
SmallVector<Loop *, 4> ChildLoops(L.begin(), L.end());
Updater.addChildLoops(ChildLoops);
}
}
return getLoopPassPreservedAnalyses();
}
