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llvm-mirror/lib/Transforms/Scalar/LoopUnrollPass.cpp
Chandler Carruth 79dd28c36c [Unroll] Switch from an eagerly populated SCEV cache to one that is
lazily built.

Also, make it a much more generic SCEV cache, which today exposes only
a reduced GEP model description but could be extended in the future to
do other profitable caching of SCEV information.

llvm-svn: 238124
2015-05-25 01:00:46 +00:00

1016 lines
39 KiB
C++

//===-- 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.h"
#include "llvm/ADT/SetVector.h"
#include "llvm/Analysis/AssumptionCache.h"
#include "llvm/Analysis/CodeMetrics.h"
#include "llvm/Analysis/InstructionSimplify.h"
#include "llvm/Analysis/LoopPass.h"
#include "llvm/Analysis/ScalarEvolution.h"
#include "llvm/Analysis/ScalarEvolutionExpressions.h"
#include "llvm/Analysis/TargetTransformInfo.h"
#include "llvm/IR/DataLayout.h"
#include "llvm/IR/DiagnosticInfo.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/Utils/UnrollLoop.h"
#include <climits>
using namespace llvm;
#define DEBUG_TYPE "loop-unroll"
static cl::opt<unsigned>
UnrollThreshold("unroll-threshold", cl::init(150), cl::Hidden,
cl::desc("The cut-off point for automatic loop unrolling"));
static cl::opt<unsigned> UnrollMaxIterationsCountToAnalyze(
"unroll-max-iteration-count-to-analyze", cl::init(0), 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> UnrollMinPercentOfOptimized(
"unroll-percent-of-optimized-for-complete-unroll", cl::init(20), cl::Hidden,
cl::desc("If complete unrolling could trigger further optimizations, and, "
"by that, remove the given percent of instructions, perform the "
"complete unroll even if it's beyond the threshold"));
static cl::opt<unsigned> UnrollAbsoluteThreshold(
"unroll-absolute-threshold", cl::init(2000), cl::Hidden,
cl::desc("Don't unroll if the unrolled size is bigger than this threshold,"
" even if we can remove big portion of instructions later."));
static cl::opt<unsigned>
UnrollCount("unroll-count", cl::init(0), cl::Hidden,
cl::desc("Use this unroll count for all loops including those with "
"unroll_count pragma values, for testing purposes"));
static cl::opt<bool>
UnrollAllowPartial("unroll-allow-partial", cl::init(false), cl::Hidden,
cl::desc("Allows loops to be partially unrolled until "
"-unroll-threshold loop size is reached."));
static cl::opt<bool>
UnrollRuntime("unroll-runtime", cl::ZeroOrMore, cl::init(false), cl::Hidden,
cl::desc("Unroll loops with run-time trip counts"));
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."));
namespace {
class LoopUnroll : public LoopPass {
public:
static char ID; // Pass ID, replacement for typeid
LoopUnroll(int T = -1, int C = -1, int P = -1, int R = -1) : LoopPass(ID) {
CurrentThreshold = (T == -1) ? UnrollThreshold : unsigned(T);
CurrentAbsoluteThreshold = UnrollAbsoluteThreshold;
CurrentMinPercentOfOptimized = UnrollMinPercentOfOptimized;
CurrentCount = (C == -1) ? UnrollCount : unsigned(C);
CurrentAllowPartial = (P == -1) ? UnrollAllowPartial : (bool)P;
CurrentRuntime = (R == -1) ? UnrollRuntime : (bool)R;
UserThreshold = (T != -1) || (UnrollThreshold.getNumOccurrences() > 0);
UserAbsoluteThreshold = (UnrollAbsoluteThreshold.getNumOccurrences() > 0);
UserPercentOfOptimized =
(UnrollMinPercentOfOptimized.getNumOccurrences() > 0);
UserAllowPartial = (P != -1) ||
(UnrollAllowPartial.getNumOccurrences() > 0);
UserRuntime = (R != -1) || (UnrollRuntime.getNumOccurrences() > 0);
UserCount = (C != -1) || (UnrollCount.getNumOccurrences() > 0);
initializeLoopUnrollPass(*PassRegistry::getPassRegistry());
}
/// 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;
// Threshold to use when optsize is specified (and there is no
// explicit -unroll-threshold).
static const unsigned OptSizeUnrollThreshold = 50;
// Default unroll count for loops with run-time trip count if
// -unroll-count is not set
static const unsigned UnrollRuntimeCount = 8;
unsigned CurrentCount;
unsigned CurrentThreshold;
unsigned CurrentAbsoluteThreshold;
unsigned CurrentMinPercentOfOptimized;
bool CurrentAllowPartial;
bool CurrentRuntime;
bool UserCount; // CurrentCount is user-specified.
bool UserThreshold; // CurrentThreshold is user-specified.
bool UserAbsoluteThreshold; // CurrentAbsoluteThreshold is
// user-specified.
bool UserPercentOfOptimized; // CurrentMinPercentOfOptimized is
// user-specified.
bool UserAllowPartial; // CurrentAllowPartial is user-specified.
bool UserRuntime; // CurrentRuntime is user-specified.
bool runOnLoop(Loop *L, LPPassManager &LPM) override;
/// 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<LoopInfoWrapperPass>();
AU.addPreserved<LoopInfoWrapperPass>();
AU.addRequiredID(LoopSimplifyID);
AU.addPreservedID(LoopSimplifyID);
AU.addRequiredID(LCSSAID);
AU.addPreservedID(LCSSAID);
AU.addRequired<ScalarEvolution>();
AU.addPreserved<ScalarEvolution>();
AU.addRequired<TargetTransformInfoWrapperPass>();
// FIXME: Loop unroll requires LCSSA. And LCSSA requires dom info.
// If loop unroll does not preserve dom info then LCSSA pass on next
// loop will receive invalid dom info.
// For now, recreate dom info, if loop is unrolled.
AU.addPreserved<DominatorTreeWrapperPass>();
}
// Fill in the UnrollingPreferences parameter with values from the
// TargetTransformationInfo.
void getUnrollingPreferences(Loop *L, const TargetTransformInfo &TTI,
TargetTransformInfo::UnrollingPreferences &UP) {
UP.Threshold = CurrentThreshold;
UP.AbsoluteThreshold = CurrentAbsoluteThreshold;
UP.MinPercentOfOptimized = CurrentMinPercentOfOptimized;
UP.OptSizeThreshold = OptSizeUnrollThreshold;
UP.PartialThreshold = CurrentThreshold;
UP.PartialOptSizeThreshold = OptSizeUnrollThreshold;
UP.Count = CurrentCount;
UP.MaxCount = UINT_MAX;
UP.Partial = CurrentAllowPartial;
UP.Runtime = CurrentRuntime;
UP.AllowExpensiveTripCount = false;
TTI.getUnrollingPreferences(L, UP);
}
// Select and return an unroll count based on parameters from
// user, unroll preferences, unroll pragmas, or a heuristic.
// SetExplicitly is set to true if the unroll count is is set by
// the user or a pragma rather than selected heuristically.
unsigned
selectUnrollCount(const Loop *L, unsigned TripCount, bool PragmaFullUnroll,
unsigned PragmaCount,
const TargetTransformInfo::UnrollingPreferences &UP,
bool &SetExplicitly);
// Select threshold values used to limit unrolling based on a
// total unrolled size. Parameters Threshold and PartialThreshold
// are set to the maximum unrolled size for fully and partially
// unrolled loops respectively.
void selectThresholds(const Loop *L, bool HasPragma,
const TargetTransformInfo::UnrollingPreferences &UP,
unsigned &Threshold, unsigned &PartialThreshold,
unsigned &AbsoluteThreshold,
unsigned &PercentOfOptimizedForCompleteUnroll) {
// Determine the current unrolling threshold. While this is
// normally set from UnrollThreshold, it is overridden to a
// smaller value if the current function is marked as
// optimize-for-size, and the unroll threshold was not user
// specified.
Threshold = UserThreshold ? CurrentThreshold : UP.Threshold;
PartialThreshold = UserThreshold ? CurrentThreshold : UP.PartialThreshold;
AbsoluteThreshold = UserAbsoluteThreshold ? CurrentAbsoluteThreshold
: UP.AbsoluteThreshold;
PercentOfOptimizedForCompleteUnroll = UserPercentOfOptimized
? CurrentMinPercentOfOptimized
: UP.MinPercentOfOptimized;
if (!UserThreshold &&
L->getHeader()->getParent()->hasFnAttribute(
Attribute::OptimizeForSize)) {
Threshold = UP.OptSizeThreshold;
PartialThreshold = UP.PartialOptSizeThreshold;
}
if (HasPragma) {
// If the loop has an unrolling pragma, we want to be more
// aggressive with unrolling limits. Set thresholds to at
// least the PragmaTheshold value which is larger than the
// default limits.
if (Threshold != NoThreshold)
Threshold = std::max<unsigned>(Threshold, PragmaUnrollThreshold);
if (PartialThreshold != NoThreshold)
PartialThreshold =
std::max<unsigned>(PartialThreshold, PragmaUnrollThreshold);
}
}
bool canUnrollCompletely(Loop *L, unsigned Threshold,
unsigned AbsoluteThreshold, uint64_t UnrolledSize,
unsigned NumberOfOptimizedInstructions,
unsigned PercentOfOptimizedForCompleteUnroll);
};
}
char LoopUnroll::ID = 0;
INITIALIZE_PASS_BEGIN(LoopUnroll, "loop-unroll", "Unroll loops", false, false)
INITIALIZE_PASS_DEPENDENCY(TargetTransformInfoWrapperPass)
INITIALIZE_PASS_DEPENDENCY(AssumptionCacheTracker)
INITIALIZE_PASS_DEPENDENCY(LoopInfoWrapperPass)
INITIALIZE_PASS_DEPENDENCY(LoopSimplify)
INITIALIZE_PASS_DEPENDENCY(LCSSA)
INITIALIZE_PASS_DEPENDENCY(ScalarEvolution)
INITIALIZE_PASS_END(LoopUnroll, "loop-unroll", "Unroll loops", false, false)
Pass *llvm::createLoopUnrollPass(int Threshold, int Count, int AllowPartial,
int Runtime) {
return new LoopUnroll(Threshold, Count, AllowPartial, Runtime);
}
Pass *llvm::createSimpleLoopUnrollPass() {
return llvm::createLoopUnrollPass(-1, -1, 0, 0);
}
namespace {
/// \brief SCEV expressions visitor used for finding expressions that would
/// become constants if the loop L is unrolled.
struct FindConstantPointers {
/// \brief Shows whether the expression is ConstAddress+Constant or not.
bool IndexIsConstant;
/// \brief Used for filtering out SCEV expressions with two or more AddRec
/// subexpressions.
///
/// Used to filter out complicated SCEV expressions, having several AddRec
/// sub-expressions. We don't handle them, because unrolling one loop
/// would help to replace only one of these inductions with a constant, and
/// consequently, the expression would remain non-constant.
bool HaveSeenAR;
/// \brief If the SCEV expression becomes ConstAddress+Constant, this value
/// holds ConstAddress. Otherwise, it's nullptr.
Value *BaseAddress;
/// \brief The loop, which we try to completely unroll.
const Loop *L;
ScalarEvolution &SE;
FindConstantPointers(const Loop *L, ScalarEvolution &SE)
: IndexIsConstant(true), HaveSeenAR(false), BaseAddress(nullptr),
L(L), SE(SE) {}
/// Examine the given expression S and figure out, if it can be a part of an
/// expression, that could become a constant after the loop is unrolled.
/// The routine sets IndexIsConstant and HaveSeenAR according to the analysis
/// results.
/// \returns true if we need to examine subexpressions, and false otherwise.
bool follow(const SCEV *S) {
if (const SCEVUnknown *SC = dyn_cast<SCEVUnknown>(S)) {
// We've reached the leaf node of SCEV, it's most probably just a
// variable.
// If it's the only one SCEV-subexpression, then it might be a base
// address of an index expression.
// If we've already recorded base address, then just give up on this SCEV
// - it's too complicated.
if (BaseAddress) {
IndexIsConstant = false;
return false;
}
BaseAddress = SC->getValue();
return false;
}
if (isa<SCEVConstant>(S))
return false;
if (const SCEVAddRecExpr *AR = dyn_cast<SCEVAddRecExpr>(S)) {
// If the current SCEV expression is AddRec, and its loop isn't the loop
// we are about to unroll, then we won't get a constant address after
// unrolling, and thus, won't be able to eliminate the load.
if (AR->getLoop() != L) {
IndexIsConstant = false;
return false;
}
// We don't handle multiple AddRecs here, so give up in this case.
if (HaveSeenAR) {
IndexIsConstant = false;
return false;
}
HaveSeenAR = true;
}
// Continue traversal.
return true;
}
bool isDone() const { return !IndexIsConstant; }
};
} // End anonymous namespace.
namespace {
/// \brief A cache of SCEV results used to optimize repeated queries to SCEV on
/// the same set of instructions.
///
/// The primary cost this saves is the cost of checking the validity of a SCEV
/// every time it is looked up. However, in some cases we can provide a reduced
/// and especially useful model for an instruction based upon SCEV that is
/// non-trivial to compute but more useful to clients.
class SCEVCache {
public:
/// \brief Struct to represent a GEP whose start and step are known fixed
/// offsets from a base address due to SCEV's analysis.
struct GEPDescriptor {
Value *BaseAddr = nullptr;
unsigned Start = 0;
unsigned Step = 0;
};
Optional<GEPDescriptor> getGEPDescriptor(GetElementPtrInst *GEP);
SCEVCache(const Loop &L, ScalarEvolution &SE) : L(L), SE(SE) {}
private:
const Loop &L;
ScalarEvolution &SE;
SmallDenseMap<GetElementPtrInst *, GEPDescriptor> GEPDescriptors;
};
} // End anonymous namespace.
/// \brief Get a simplified descriptor for a GEP instruction.
///
/// Where possible, this produces a simplified descriptor for a GEP instruction
/// using SCEV analysis of the containing loop. If this isn't possible, it
/// returns an empty optional.
///
/// The model is a base address, an initial offset, and a per-iteration step.
/// This fits very common patterns of GEPs inside loops and is something we can
/// use to simulate the behavior of a particular iteration of a loop.
///
/// This is a cached interface. The first call may do non-trivial work to
/// compute the result, but all subsequent calls will return a fast answer
/// based on a cached result. This includes caching negative results.
Optional<SCEVCache::GEPDescriptor>
SCEVCache::getGEPDescriptor(GetElementPtrInst *GEP) {
decltype(GEPDescriptors)::iterator It;
bool Inserted;
std::tie(It, Inserted) = GEPDescriptors.insert({GEP, {}});
if (!Inserted) {
if (!It->second.BaseAddr)
return None;
return It->second;
}
// We've inserted a new record into the cache, so compute the GEP descriptor
// if possible.
Value *V = cast<Value>(GEP);
if (!SE.isSCEVable(V->getType()))
return None;
const SCEV *S = SE.getSCEV(V);
// FIXME: It'd be nice if the worklist and set used by the
// SCEVTraversal could be re-used between loop iterations, but the
// interface doesn't support that. There is no way to clear the visited
// sets between uses.
FindConstantPointers Visitor(&L, SE);
SCEVTraversal<FindConstantPointers> T(Visitor);
// Try to find (BaseAddress+Step+Offset) tuple.
// If succeeded, save it to the cache - it might help in folding
// loads.
T.visitAll(S);
if (!Visitor.IndexIsConstant || !Visitor.BaseAddress)
return None;
const SCEV *BaseAddrSE = SE.getSCEV(Visitor.BaseAddress);
if (BaseAddrSE->getType() != S->getType())
return None;
const SCEV *OffSE = SE.getMinusSCEV(S, BaseAddrSE);
const SCEVAddRecExpr *AR = dyn_cast<SCEVAddRecExpr>(OffSE);
if (!AR)
return None;
const SCEVConstant *StepSE =
dyn_cast<SCEVConstant>(AR->getStepRecurrence(SE));
const SCEVConstant *StartSE = dyn_cast<SCEVConstant>(AR->getStart());
if (!StepSE || !StartSE)
return None;
// Check and skip caching if doing so would require lots of bits to
// avoid overflow.
APInt Start = StartSE->getValue()->getValue();
APInt Step = StepSE->getValue()->getValue();
if (Start.getActiveBits() > 32 || Step.getActiveBits() > 32)
return None;
// We found a cacheable SCEV model for the GEP.
It->second.BaseAddr = Visitor.BaseAddress;
It->second.Start = Start.getLimitedValue();
It->second.Step = Step.getLimitedValue();
return It->second;
}
namespace {
// This class is used to get an estimate of the optimization effects that we
// could get from complete loop unrolling. It comes from the fact that some
// loads might be replaced with concrete constant values and that could trigger
// a chain of instruction simplifications.
//
// E.g. we might have:
// int a[] = {0, 1, 0};
// v = 0;
// for (i = 0; i < 3; i ++)
// v += b[i]*a[i];
// If we completely unroll the loop, we would get:
// v = b[0]*a[0] + b[1]*a[1] + b[2]*a[2]
// Which then will be simplified to:
// v = b[0]* 0 + b[1]* 1 + b[2]* 0
// And finally:
// v = b[1]
class UnrolledInstAnalyzer : private InstVisitor<UnrolledInstAnalyzer, bool> {
typedef InstVisitor<UnrolledInstAnalyzer, bool> Base;
friend class InstVisitor<UnrolledInstAnalyzer, bool>;
public:
UnrolledInstAnalyzer(unsigned Iteration,
DenseMap<Value *, Constant *> &SimplifiedValues,
SCEVCache &SC)
: Iteration(Iteration), SimplifiedValues(SimplifiedValues), SC(SC) {}
// Allow access to the initial visit method.
using Base::visit;
private:
/// \brief Number of currently simulated iteration.
///
/// If an expression is ConstAddress+Constant, then the Constant is
/// Start + Iteration*Step, where Start and Step could be obtained from
/// SCEVGEPCache.
unsigned Iteration;
// While we walk the loop instructions, we we build up and maintain a mapping
// of simplified values specific to this iteration. The idea is to propagate
// any special information we have about loads that can be replaced with
// constants after complete unrolling, and account for likely simplifications
// post-unrolling.
DenseMap<Value *, Constant *> &SimplifiedValues;
// We use a cache to wrap all our SCEV queries.
SCEVCache &SC;
/// Base case for the instruction visitor.
bool visitInstruction(Instruction &I) { return false; };
/// TODO: Add visitors for other instruction types, e.g. ZExt, SExt.
/// Try to simplify binary operator I.
///
/// TODO: Probaly it's worth to hoist the code for estimating the
/// simplifications effects to a separate class, since we have a very similar
/// code in InlineCost already.
bool visitBinaryOperator(BinaryOperator &I) {
Value *LHS = I.getOperand(0), *RHS = I.getOperand(1);
if (!isa<Constant>(LHS))
if (Constant *SimpleLHS = SimplifiedValues.lookup(LHS))
LHS = SimpleLHS;
if (!isa<Constant>(RHS))
if (Constant *SimpleRHS = SimplifiedValues.lookup(RHS))
RHS = SimpleRHS;
Value *SimpleV = nullptr;
const DataLayout &DL = I.getModule()->getDataLayout();
if (auto FI = dyn_cast<FPMathOperator>(&I))
SimpleV =
SimplifyFPBinOp(I.getOpcode(), LHS, RHS, FI->getFastMathFlags(), DL);
else
SimpleV = SimplifyBinOp(I.getOpcode(), LHS, RHS, DL);
if (Constant *C = dyn_cast_or_null<Constant>(SimpleV))
SimplifiedValues[&I] = C;
return SimpleV;
}
/// Try to fold load I.
bool visitLoad(LoadInst &I) {
Value *AddrOp = I.getPointerOperand();
if (!isa<Constant>(AddrOp))
if (Constant *SimplifiedAddrOp = SimplifiedValues.lookup(AddrOp))
AddrOp = SimplifiedAddrOp;
auto *GEP = dyn_cast<GetElementPtrInst>(AddrOp);
if (!GEP)
return false;
auto OptionalGEPDesc = SC.getGEPDescriptor(GEP);
if (!OptionalGEPDesc)
return false;
auto GV = dyn_cast<GlobalVariable>(OptionalGEPDesc->BaseAddr);
// We're only interested in loads that can be completely folded to a
// constant.
if (!GV || !GV->hasInitializer())
return false;
ConstantDataSequential *CDS =
dyn_cast<ConstantDataSequential>(GV->getInitializer());
if (!CDS)
return false;
// This calculation should never overflow because we bound Iteration quite
// low and both the start and step are 32-bit integers. We use signed
// integers so that UBSan will catch if a bug sneaks into the code.
int ElemSize = CDS->getElementType()->getPrimitiveSizeInBits() / 8U;
int64_t Index = ((int64_t)OptionalGEPDesc->Start +
(int64_t)OptionalGEPDesc->Step * (int64_t)Iteration) /
ElemSize;
if (Index >= CDS->getNumElements()) {
// FIXME: For now we conservatively ignore out of bound accesses, but
// we're allowed to perform the optimization in this case.
return false;
}
Constant *CV = CDS->getElementAsConstant(Index);
assert(CV && "Constant expected.");
SimplifiedValues[&I] = CV;
return true;
}
};
} // namespace
namespace {
struct EstimatedUnrollCost {
/// \brief Count the number of optimized instructions.
unsigned NumberOfOptimizedInstructions;
/// \brief Count the total number of instructions.
unsigned UnrolledLoopSize;
};
}
/// \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 assigns computed number of instructions,
/// that potentially might be optimized away, to
/// NumberOfOptimizedInstructions, and total number of instructions to
/// UnrolledLoopSize (not counting blocks that won't be reached, if we were
/// able to compute the condition).
/// \returns false if we can't analyze the loop, or if we discovered that
/// unrolling won't give anything. Otherwise, returns true.
Optional<EstimatedUnrollCost>
analyzeLoopUnrollCost(const Loop *L, unsigned TripCount, 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!");
// Don't simulate loops with a big or unknown tripcount
if (!UnrollMaxIterationsCountToAnalyze || !TripCount ||
TripCount > UnrollMaxIterationsCountToAnalyze)
return None;
SmallSetVector<BasicBlock *, 16> BBWorklist;
DenseMap<Value *, Constant *> SimplifiedValues;
// Use a cache to access SCEV expressions so that we don't pay the cost on
// each iteration. This cache is lazily self-populating.
SCEVCache SC(*L, SE);
unsigned NumberOfOptimizedInstructions = 0;
unsigned UnrolledLoopSize = 0;
// 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) {
SimplifiedValues.clear();
UnrolledInstAnalyzer Analyzer(Iteration, SimplifiedValues, SC);
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) {
UnrolledLoopSize += TTI.getUserCost(&I);
// Visit the instruction to analyze its loop cost after unrolling,
// and if the visitor returns true, then we can optimize this
// instruction away.
if (Analyzer.visit(I))
NumberOfOptimizedInstructions += TTI.getUserCost(&I);
// If unrolled body turns out to be too big, bail out.
if (UnrolledLoopSize - NumberOfOptimizedInstructions >
MaxUnrolledLoopSize)
return None;
}
// Add BB's successors to the worklist.
for (BasicBlock *Succ : successors(BB))
if (L->contains(Succ))
BBWorklist.insert(Succ);
}
// If we found no optimization opportunities on the first iteration, we
// won't find them on later ones too.
if (!NumberOfOptimizedInstructions)
return None;
}
return {{NumberOfOptimizedInstructions, UnrolledLoopSize}};
}
/// ApproximateLoopSize - Approximate the size of the loop.
static unsigned ApproximateLoopSize(const Loop *L, unsigned &NumCalls,
bool &NotDuplicatable,
const TargetTransformInfo &TTI,
AssumptionCache *AC) {
SmallPtrSet<const Value *, 32> EphValues;
CodeMetrics::collectEphemeralValues(L, AC, EphValues);
CodeMetrics Metrics;
for (Loop::block_iterator I = L->block_begin(), E = L->block_end();
I != E; ++I)
Metrics.analyzeBasicBlock(*I, TTI, EphValues);
NumCalls = Metrics.NumInlineCandidates;
NotDuplicatable = Metrics.notDuplicatable;
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, 3u);
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(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();
if (!LoopID) return;
// 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);
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);
}
bool LoopUnroll::canUnrollCompletely(
Loop *L, unsigned Threshold, unsigned AbsoluteThreshold,
uint64_t UnrolledSize, unsigned NumberOfOptimizedInstructions,
unsigned PercentOfOptimizedForCompleteUnroll) {
if (Threshold == NoThreshold) {
DEBUG(dbgs() << " Can fully unroll, because no threshold is set.\n");
return true;
}
if (UnrolledSize <= Threshold) {
DEBUG(dbgs() << " Can fully unroll, because unrolled size: "
<< UnrolledSize << "<" << Threshold << "\n");
return true;
}
assert(UnrolledSize && "UnrolledSize can't be 0 at this point.");
unsigned PercentOfOptimizedInstructions =
(uint64_t)NumberOfOptimizedInstructions * 100ull / UnrolledSize;
if (UnrolledSize <= AbsoluteThreshold &&
PercentOfOptimizedInstructions >= PercentOfOptimizedForCompleteUnroll) {
DEBUG(dbgs() << " Can fully unroll, because unrolling will help removing "
<< PercentOfOptimizedInstructions
<< "% instructions (threshold: "
<< PercentOfOptimizedForCompleteUnroll << "%)\n");
DEBUG(dbgs() << " Unrolled size (" << UnrolledSize
<< ") is less than the threshold (" << AbsoluteThreshold
<< ").\n");
return true;
}
DEBUG(dbgs() << " Too large to fully unroll:\n");
DEBUG(dbgs() << " Unrolled size: " << UnrolledSize << "\n");
DEBUG(dbgs() << " Estimated number of optimized instructions: "
<< NumberOfOptimizedInstructions << "\n");
DEBUG(dbgs() << " Absolute threshold: " << AbsoluteThreshold << "\n");
DEBUG(dbgs() << " Minimum percent of removed instructions: "
<< PercentOfOptimizedForCompleteUnroll << "\n");
DEBUG(dbgs() << " Threshold for small loops: " << Threshold << "\n");
return false;
}
unsigned LoopUnroll::selectUnrollCount(
const Loop *L, unsigned TripCount, bool PragmaFullUnroll,
unsigned PragmaCount, const TargetTransformInfo::UnrollingPreferences &UP,
bool &SetExplicitly) {
SetExplicitly = true;
// User-specified count (either as a command-line option or
// constructor parameter) has highest precedence.
unsigned Count = UserCount ? CurrentCount : 0;
// If there is no user-specified count, unroll pragmas have the next
// highest precendence.
if (Count == 0) {
if (PragmaCount) {
Count = PragmaCount;
} else if (PragmaFullUnroll) {
Count = TripCount;
}
}
if (Count == 0)
Count = UP.Count;
if (Count == 0) {
SetExplicitly = false;
if (TripCount == 0)
// Runtime trip count.
Count = UnrollRuntimeCount;
else
// Conservative heuristic: if we know the trip count, see if we can
// completely unroll (subject to the threshold, checked below); otherwise
// try to find greatest modulo of the trip count which is still under
// threshold value.
Count = TripCount;
}
if (TripCount && Count > TripCount)
return TripCount;
return Count;
}
bool LoopUnroll::runOnLoop(Loop *L, LPPassManager &LPM) {
if (skipOptnoneFunction(L))
return false;
Function &F = *L->getHeader()->getParent();
LoopInfo *LI = &getAnalysis<LoopInfoWrapperPass>().getLoopInfo();
ScalarEvolution *SE = &getAnalysis<ScalarEvolution>();
const TargetTransformInfo &TTI =
getAnalysis<TargetTransformInfoWrapperPass>().getTTI(F);
auto &AC = getAnalysis<AssumptionCacheTracker>().getAssumptionCache(F);
BasicBlock *Header = L->getHeader();
DEBUG(dbgs() << "Loop Unroll: F[" << Header->getParent()->getName()
<< "] Loop %" << Header->getName() << "\n");
if (HasUnrollDisablePragma(L)) {
return false;
}
bool PragmaFullUnroll = HasUnrollFullPragma(L);
unsigned PragmaCount = UnrollCountPragmaValue(L);
bool HasPragma = PragmaFullUnroll || PragmaCount > 0;
TargetTransformInfo::UnrollingPreferences UP;
getUnrollingPreferences(L, TTI, UP);
// Find trip count and trip multiple if count is not available
unsigned TripCount = 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);
}
// Select an initial unroll count. This may be reduced later based
// on size thresholds.
bool CountSetExplicitly;
unsigned Count = selectUnrollCount(L, TripCount, PragmaFullUnroll,
PragmaCount, UP, CountSetExplicitly);
unsigned NumInlineCandidates;
bool notDuplicatable;
unsigned LoopSize =
ApproximateLoopSize(L, NumInlineCandidates, notDuplicatable, TTI, &AC);
DEBUG(dbgs() << " Loop Size = " << LoopSize << "\n");
// When computing the unrolled size, note that the conditional branch on the
// backedge and the comparison feeding it are not replicated like the rest of
// the loop body (which is why 2 is subtracted).
uint64_t UnrolledSize = (uint64_t)(LoopSize-2) * Count + 2;
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;
}
unsigned Threshold, PartialThreshold;
unsigned AbsoluteThreshold, PercentOfOptimizedForCompleteUnroll;
selectThresholds(L, HasPragma, UP, Threshold, PartialThreshold,
AbsoluteThreshold, PercentOfOptimizedForCompleteUnroll);
// Given Count, TripCount and thresholds determine the type of
// unrolling which is to be performed.
enum { Full = 0, Partial = 1, Runtime = 2 };
int Unrolling;
if (TripCount && Count == TripCount) {
Unrolling = Partial;
// If the loop is really small, we don't need to run an expensive analysis.
if (canUnrollCompletely(
L, Threshold, AbsoluteThreshold,
UnrolledSize, 0, 100)) {
Unrolling = Full;
} 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, TripCount, *SE, TTI, AbsoluteThreshold))
if (canUnrollCompletely(L, Threshold, AbsoluteThreshold,
Cost->UnrolledLoopSize,
Cost->NumberOfOptimizedInstructions,
PercentOfOptimizedForCompleteUnroll)) {
Unrolling = Full;
}
}
} else if (TripCount && Count < TripCount) {
Unrolling = Partial;
} else {
Unrolling = Runtime;
}
// Reduce count based on the type of unrolling and the threshold values.
unsigned OriginalCount = Count;
bool AllowRuntime = UserRuntime ? CurrentRuntime : UP.Runtime;
if (HasRuntimeUnrollDisablePragma(L)) {
AllowRuntime = false;
}
if (Unrolling == Partial) {
bool AllowPartial = UserAllowPartial ? CurrentAllowPartial : UP.Partial;
if (!AllowPartial && !CountSetExplicitly) {
DEBUG(dbgs() << " will not try to unroll partially because "
<< "-unroll-allow-partial not given\n");
return false;
}
if (PartialThreshold != NoThreshold && UnrolledSize > PartialThreshold) {
// Reduce unroll count to be modulo of TripCount for partial unrolling.
Count = (std::max(PartialThreshold, 3u)-2) / (LoopSize-2);
while (Count != 0 && TripCount % Count != 0)
Count--;
}
} else if (Unrolling == Runtime) {
if (!AllowRuntime && !CountSetExplicitly) {
DEBUG(dbgs() << " will not try to unroll loop with runtime trip count "
<< "-unroll-runtime not given\n");
return false;
}
// Reduce unroll count to be the largest power-of-two factor of
// the original count which satisfies the threshold limit.
while (Count != 0 && UnrolledSize > PartialThreshold) {
Count >>= 1;
UnrolledSize = (LoopSize-2) * Count + 2;
}
if (Count > UP.MaxCount)
Count = UP.MaxCount;
DEBUG(dbgs() << " partially unrolling with count: " << Count << "\n");
}
if (HasPragma) {
if (PragmaCount != 0)
// If loop has an unroll count pragma mark loop as unrolled to prevent
// unrolling beyond that requested by the pragma.
SetLoopAlreadyUnrolled(L);
// Emit optimization remarks if we are unable to unroll the loop
// as directed by a pragma.
DebugLoc LoopLoc = L->getStartLoc();
Function *F = Header->getParent();
LLVMContext &Ctx = F->getContext();
if (PragmaFullUnroll && PragmaCount == 0) {
if (TripCount && Count != TripCount) {
emitOptimizationRemarkMissed(
Ctx, DEBUG_TYPE, *F, LoopLoc,
"Unable to fully unroll loop as directed by unroll(full) pragma "
"because unrolled size is too large.");
} else if (!TripCount) {
emitOptimizationRemarkMissed(
Ctx, DEBUG_TYPE, *F, LoopLoc,
"Unable to fully unroll loop as directed by unroll(full) pragma "
"because loop has a runtime trip count.");
}
} else if (PragmaCount > 0 && Count != OriginalCount) {
emitOptimizationRemarkMissed(
Ctx, DEBUG_TYPE, *F, LoopLoc,
"Unable to unroll loop the number of times directed by "
"unroll_count pragma because unrolled size is too large.");
}
}
if (Unrolling != Full && Count < 2) {
// Partial unrolling by 1 is a nop. For full unrolling, a factor
// of 1 makes sense because loop control can be eliminated.
return false;
}
// Unroll the loop.
if (!UnrollLoop(L, Count, TripCount, AllowRuntime, UP.AllowExpensiveTripCount,
TripMultiple, LI, this, &LPM, &AC))
return false;
return true;
}