//===-- 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 #include using namespace llvm; #define DEBUG_TYPE "loop-unroll" static cl::opt UnrollThreshold("unroll-threshold", cl::Hidden, cl::desc("The baseline cost threshold for loop unrolling")); static cl::opt 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 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 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 UnrollMaxCount( "unroll-max-count", cl::Hidden, cl::desc("Set the max unroll count for partial and runtime unrolling, for" "testing purposes")); static cl::opt UnrollFullMaxCount( "unroll-full-max-count", cl::Hidden, cl::desc( "Set the max unroll count for full unrolling, for testing purposes")); static cl::opt UnrollAllowPartial("unroll-allow-partial", cl::Hidden, cl::desc("Allows loops to be partially unrolled until " "-unroll-threshold loop size is reached.")); static cl::opt UnrollAllowRemainder( "unroll-allow-remainder", cl::Hidden, cl::desc("Allow generation of a loop remainder (extra iterations) " "when unrolling a loop.")); static cl::opt UnrollRuntime("unroll-runtime", cl::ZeroOrMore, cl::Hidden, cl::desc("Unroll loops with run-time trip counts")); static cl::opt 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 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 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 UnrollAllowPeeling("unroll-allow-peeling", cl::Hidden, cl::desc("Allows loops to be peeled when the dynamic " "trip count is known to be low.")); /// 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, Optional UserThreshold, Optional UserCount, Optional UserAllowPartial, Optional UserRuntime, Optional UserUpperBound) { TargetTransformInfo::UnrollingPreferences UP; // Set up the defaults UP.Threshold = 150; UP.MaxPercentThresholdBoost = 400; UP.OptSizeThreshold = 0; UP.PartialThreshold = UP.Threshold; 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 = false; // 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; UP.PartialThreshold = UnrollThreshold; } 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 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 PtrInfo; typedef DenseMapInfo> 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 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 BBWorklist; SmallSetVector, 4> ExitWorklist; DenseMap SimplifiedValues; SmallVector, 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 // to , but stored as a densely packed struct. DenseSet InstCostMap; // A small worklist used to accumulate cost of instructions from each // observable and reached root in the loop. SmallVector CostWorklist; // PHI-used worklist used between iterations while accumulating cost. SmallVector 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(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( 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(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(&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(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(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(&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(TI)) { if (BI->isConditional()) { if (Constant *SimpleCond = SimplifiedValues.lookup(BI->getCondition())) { // Just take the first successor if condition is undef if (isa(SimpleCond)) KnownSucc = BI->getSuccessor(0); else if (ConstantInt *SimpleCondVal = dyn_cast(SimpleCond)) KnownSucc = BI->getSuccessor(SimpleCondVal->isZero() ? 1 : 0); } } } else if (SwitchInst *SI = dyn_cast(TI)) { if (Constant *SimpleCond = SimplifiedValues.lookup(SI->getCondition())) { // Just take the first successor if condition is undef if (isa(SimpleCond)) KnownSucc = SI->getSuccessor(0); else if (ConstantInt *SimpleCondVal = dyn_cast(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(&I); if (!PN) break; Value *Op = PN->getIncomingValueForBlock(ExitingBB); if (auto *OpI = dyn_cast(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 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(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 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(LoopID->getOperand(i)); if (MD) { const MDString *S = dyn_cast(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 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(UP.Threshold, PragmaUnrollThreshold); UP.PartialThreshold = std::max(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 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; } } } } // 4rd 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."); // 5th priority is loop peeling computePeelCount(L, LoopSize, UP); if (UP.PeelCount) { UP.Runtime = false; UP.Count = 1; return ExplicitUnroll; } // 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, Optional ProvidedCount, Optional ProvidedThreshold, Optional ProvidedAllowPartial, Optional ProvidedRuntime, Optional 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, 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(Optional Threshold = None, Optional Count = None, Optional AllowPartial = None, Optional Runtime = None, Optional UpperBound = None) : LoopPass(ID), ProvidedCount(std::move(Count)), ProvidedThreshold(Threshold), ProvidedAllowPartial(AllowPartial), ProvidedRuntime(Runtime), ProvidedUpperBound(UpperBound) { initializeLoopUnrollPass(*PassRegistry::getPassRegistry()); } Optional ProvidedCount; Optional ProvidedThreshold; Optional ProvidedAllowPartial; Optional ProvidedRuntime; Optional ProvidedUpperBound; bool runOnLoop(Loop *L, LPPassManager &) override { if (skipLoop(L)) return false; Function &F = *L->getHeader()->getParent(); auto &DT = getAnalysis().getDomTree(); LoopInfo *LI = &getAnalysis().getLoopInfo(); ScalarEvolution *SE = &getAnalysis().getSE(); const TargetTransformInfo &TTI = getAnalysis().getTTI(F); auto &AC = getAnalysis().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, 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(); AU.addRequired(); // 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 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(Threshold == -1 ? None : Optional(Threshold), Count == -1 ? None : Optional(Count), AllowPartial == -1 ? None : Optional(AllowPartial), Runtime == -1 ? None : Optional(Runtime), UpperBound == -1 ? None : Optional(UpperBound)); } Pass *llvm::createSimpleLoopUnrollPass() { return llvm::createLoopUnrollPass(-1, -1, 0, 0, 0); } PreservedAnalyses LoopUnrollPass::run(Loop &L, LoopAnalysisManager &AM, LoopStandardAnalysisResults &AR, LPMUpdater &) { const auto &FAM = AM.getResult(L, AR).getManager(); Function *F = L.getHeader()->getParent(); auto *ORE = FAM.getCachedResult(*F); // FIXME: This should probably be optional rather than required. if (!ORE) report_fatal_error("LoopUnrollPass: OptimizationRemarkEmitterAnalysis not " "cached at a higher level"); bool Changed = tryToUnrollLoop(&L, AR.DT, &AR.LI, &AR.SE, AR.TTI, AR.AC, *ORE, /*PreserveLCSSA*/ true, ProvidedCount, ProvidedThreshold, ProvidedAllowPartial, ProvidedRuntime, ProvidedUpperBound); if (!Changed) return PreservedAnalyses::all(); return getLoopPassPreservedAnalyses(); }