//===- LoopUnroll.cpp - Loop unroller pass --------------------------------===// // // Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions. // See https://llvm.org/LICENSE.txt for license information. // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception // //===----------------------------------------------------------------------===// // // 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/DenseMap.h" #include "llvm/ADT/DenseMapInfo.h" #include "llvm/ADT/DenseSet.h" #include "llvm/ADT/None.h" #include "llvm/ADT/Optional.h" #include "llvm/ADT/STLExtras.h" #include "llvm/ADT/SetVector.h" #include "llvm/ADT/SmallPtrSet.h" #include "llvm/ADT/SmallVector.h" #include "llvm/ADT/StringRef.h" #include "llvm/Analysis/AssumptionCache.h" #include "llvm/Analysis/BlockFrequencyInfo.h" #include "llvm/Analysis/CodeMetrics.h" #include "llvm/Analysis/LazyBlockFrequencyInfo.h" #include "llvm/Analysis/LoopAnalysisManager.h" #include "llvm/Analysis/LoopInfo.h" #include "llvm/Analysis/LoopPass.h" #include "llvm/Analysis/LoopUnrollAnalyzer.h" #include "llvm/Analysis/OptimizationRemarkEmitter.h" #include "llvm/Analysis/ProfileSummaryInfo.h" #include "llvm/Analysis/ScalarEvolution.h" #include "llvm/Analysis/TargetTransformInfo.h" #include "llvm/IR/BasicBlock.h" #include "llvm/IR/CFG.h" #include "llvm/IR/Constant.h" #include "llvm/IR/Constants.h" #include "llvm/IR/DiagnosticInfo.h" #include "llvm/IR/Dominators.h" #include "llvm/IR/Function.h" #include "llvm/IR/Instruction.h" #include "llvm/IR/Instructions.h" #include "llvm/IR/IntrinsicInst.h" #include "llvm/IR/Metadata.h" #include "llvm/IR/PassManager.h" #include "llvm/InitializePasses.h" #include "llvm/Pass.h" #include "llvm/Support/Casting.h" #include "llvm/Support/CommandLine.h" #include "llvm/Support/Debug.h" #include "llvm/Support/ErrorHandling.h" #include "llvm/Support/raw_ostream.h" #include "llvm/Transforms/Scalar.h" #include "llvm/Transforms/Scalar/LoopPassManager.h" #include "llvm/Transforms/Utils.h" #include "llvm/Transforms/Utils/LoopPeel.h" #include "llvm/Transforms/Utils/LoopSimplify.h" #include "llvm/Transforms/Utils/LoopUtils.h" #include "llvm/Transforms/Utils/SizeOpts.h" #include "llvm/Transforms/Utils/UnrollLoop.h" #include #include #include #include #include #include #include using namespace llvm; #define DEBUG_TYPE "loop-unroll" cl::opt llvm::ForgetSCEVInLoopUnroll( "forget-scev-loop-unroll", cl::init(false), cl::Hidden, cl::desc("Forget everything in SCEV when doing LoopUnroll, instead of just" " the current top-most loop. This is sometimes preferred to reduce" " compile time.")); static cl::opt UnrollThreshold("unroll-threshold", cl::Hidden, cl::desc("The cost threshold for loop unrolling")); static cl::opt UnrollOptSizeThreshold( "unroll-optsize-threshold", cl::init(0), cl::Hidden, cl::desc("The cost threshold for loop unrolling when optimizing for " "size")); static cl::opt UnrollPartialThreshold( "unroll-partial-threshold", cl::Hidden, cl::desc("The cost threshold for partial 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 UnrollUnrollRemainder( "unroll-remainder", cl::Hidden, cl::desc("Allow the loop remainder to be unrolled.")); // 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 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.")); static cl::opt UnrollThresholdAggressive( "unroll-threshold-aggressive", cl::init(300), cl::Hidden, cl::desc("Threshold (max size of unrolled loop) to use in aggressive (O3) " "optimizations")); static cl::opt UnrollThresholdDefault("unroll-threshold-default", cl::init(150), cl::Hidden, cl::desc("Default threshold (max size of unrolled " "loop), used in all but O3 optimizations")); /// 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 = std::numeric_limits::max(); /// Gather the various unrolling parameters based on the defaults, compiler /// flags, TTI overrides and user specified parameters. TargetTransformInfo::UnrollingPreferences llvm::gatherUnrollingPreferences( Loop *L, ScalarEvolution &SE, const TargetTransformInfo &TTI, BlockFrequencyInfo *BFI, ProfileSummaryInfo *PSI, OptimizationRemarkEmitter &ORE, int OptLevel, Optional UserThreshold, Optional UserCount, Optional UserAllowPartial, Optional UserRuntime, Optional UserUpperBound, Optional UserFullUnrollMaxCount) { TargetTransformInfo::UnrollingPreferences UP; // Set up the defaults UP.Threshold = OptLevel > 2 ? UnrollThresholdAggressive : UnrollThresholdDefault; UP.MaxPercentThresholdBoost = 400; UP.OptSizeThreshold = UnrollOptSizeThreshold; UP.PartialThreshold = 150; UP.PartialOptSizeThreshold = UnrollOptSizeThreshold; UP.Count = 0; UP.DefaultUnrollRuntimeCount = 8; UP.MaxCount = std::numeric_limits::max(); UP.FullUnrollMaxCount = std::numeric_limits::max(); UP.BEInsns = 2; UP.Partial = false; UP.Runtime = false; UP.AllowRemainder = true; UP.UnrollRemainder = false; UP.AllowExpensiveTripCount = false; UP.Force = false; UP.UpperBound = false; UP.UnrollAndJam = false; UP.UnrollAndJamInnerLoopThreshold = 60; UP.MaxIterationsCountToAnalyze = UnrollMaxIterationsCountToAnalyze; // Override with any target specific settings TTI.getUnrollingPreferences(L, SE, UP, &ORE); // Apply size attributes bool OptForSize = L->getHeader()->getParent()->hasOptSize() || // Let unroll hints / pragmas take precedence over PGSO. (hasUnrollTransformation(L) != TM_ForcedByUser && llvm::shouldOptimizeForSize(L->getHeader(), PSI, BFI, PGSOQueryType::IRPass)); if (OptForSize) { UP.Threshold = UP.OptSizeThreshold; UP.PartialThreshold = UP.PartialOptSizeThreshold; UP.MaxPercentThresholdBoost = 100; } // 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 (UnrollUnrollRemainder.getNumOccurrences() > 0) UP.UnrollRemainder = UnrollUnrollRemainder; if (UnrollMaxIterationsCountToAnalyze.getNumOccurrences() > 0) UP.MaxIterationsCountToAnalyze = UnrollMaxIterationsCountToAnalyze; // 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; if (UserFullUnrollMaxCount.hasValue()) UP.FullUnrollMaxCount = *UserFullUnrollMaxCount; 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 { using PtrInfo = DenseMapInfo; using PairInfo = DenseMapInfo>; 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}); } }; struct EstimatedUnrollCost { /// The estimated cost after unrolling. unsigned UnrolledCost; /// The estimated dynamic cost of executing the instructions in the /// rolled form. unsigned RolledDynamicCost; }; struct PragmaInfo { PragmaInfo(bool UUC, bool PFU, unsigned PC, bool PEU) : UserUnrollCount(UUC), PragmaFullUnroll(PFU), PragmaCount(PC), PragmaEnableUnroll(PEU) {} const bool UserUnrollCount; const bool PragmaFullUnroll; const unsigned PragmaCount; const bool PragmaEnableUnroll; }; } // end anonymous namespace /// 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 SmallPtrSetImpl &EphValues, const TargetTransformInfo &TTI, unsigned MaxUnrolledLoopSize, unsigned MaxIterationsCountToAnalyze) { // 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(MaxIterationsCountToAnalyze < (unsigned)(std::numeric_limits::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->isInnermost()) return None; // Don't simulate loops with a big or unknown tripcount if (!TripCount || TripCount > MaxIterationsCountToAnalyze) 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. InstructionCost 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. InstructionCost 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); TargetTransformInfo::TargetCostKind CostKind = RootI.getFunction()->hasMinSize() ? TargetTransformInfo::TCK_CodeSize : TargetTransformInfo::TCK_SizeAndLatency; 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, CostKind); LLVM_DEBUG(dbgs() << "Adding cost of instruction (iteration " << Iteration << "): "); LLVM_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."); LLVM_DEBUG(dbgs() << "Starting LoopUnroll profitability analysis...\n"); TargetTransformInfo::TargetCostKind CostKind = L->getHeader()->getParent()->hasMinSize() ? TargetTransformInfo::TCK_CodeSize : TargetTransformInfo::TCK_SizeAndLatency; // 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) { LLVM_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()); if (Iteration != 0 && SimplifiedValues.count(V)) V = SimplifiedValues.lookup(V); SimplifiedInputValues.push_back({PHI, V}); } // 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) { // These won't get into the final code - don't even try calculating the // cost for them. if (isa(I) || EphValues.count(&I)) continue; // Track this instruction's expected baseline cost when executing the // rolled loop form. RolledDynamicCost += TTI.getUserCost(&I, CostKind); // 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 (auto *CI = dyn_cast(&I)) { const Function *Callee = CI->getCalledFunction(); if (!Callee || TTI.isLoweredToCall(Callee)) { LLVM_DEBUG(dbgs() << "Can't analyze cost of loop with call\n"); 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) { LLVM_DEBUG(dbgs() << " Exceeded threshold.. exiting.\n" << " UnrolledCost: " << UnrolledCost << ", MaxUnrolledLoopSize: " << MaxUnrolledLoopSize << "\n"); return None; } } Instruction *TI = BB->getTerminator(); auto getSimplifiedConstant = [&](Value *V) -> Constant * { if (SimplifiedValues.count(V)) V = SimplifiedValues.lookup(V); return dyn_cast(V); }; // 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 (auto *SimpleCond = getSimplifiedConstant(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 (auto *SimpleCond = getSimplifiedConstant(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) { LLVM_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); } } assert(UnrolledCost.isValid() && RolledDynamicCost.isValid() && "All instructions must have a valid cost, whether the " "loop is rolled or unrolled."); LLVM_DEBUG(dbgs() << "Analysis finished:\n" << "UnrolledCost: " << UnrolledCost << ", " << "RolledDynamicCost: " << RolledDynamicCost << "\n"); return {{unsigned(*UnrolledCost.getValue()), unsigned(*RolledDynamicCost.getValue())}}; } /// ApproximateLoopSize - Approximate the size of the loop. unsigned llvm::ApproximateLoopSize( const Loop *L, unsigned &NumCalls, bool &NotDuplicatable, bool &Convergent, const TargetTransformInfo &TTI, const SmallPtrSetImpl &EphValues, unsigned BEInsns) { 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 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; } // 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 >= std::numeric_limits::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; } // Produce an estimate of the unrolled cost of the specified loop. This // is used to a) produce a cost estimate for partial unrolling and b) to // cheaply estimate cost for full unrolling when we don't want to symbolically // evaluate all iterations. class UnrollCostEstimator { const unsigned LoopSize; public: UnrollCostEstimator(Loop &L, unsigned LoopSize) : LoopSize(LoopSize) {} // Returns loop size estimation for unrolled loop, given the unrolling // configuration specified by UP. uint64_t getUnrolledLoopSize(const TargetTransformInfo::UnrollingPreferences &UP, const unsigned CountOverwrite = 0) const { assert(LoopSize >= UP.BEInsns && "LoopSize should not be less than BEInsns!"); if (CountOverwrite) return static_cast(LoopSize - UP.BEInsns) * CountOverwrite + UP.BEInsns; else return static_cast(LoopSize - UP.BEInsns) * UP.Count + UP.BEInsns; } }; static Optional shouldPragmaUnroll(Loop *L, const PragmaInfo &PInfo, const unsigned TripMultiple, const unsigned TripCount, const UnrollCostEstimator UCE, const TargetTransformInfo::UnrollingPreferences &UP) { // Using unroll pragma // 1st priority is unroll count set by "unroll-count" option. if (PInfo.UserUnrollCount) { if (UP.AllowRemainder && UCE.getUnrolledLoopSize(UP, (unsigned)UnrollCount) < UP.Threshold) return (unsigned)UnrollCount; } // 2nd priority is unroll count set by pragma. if (PInfo.PragmaCount > 0) { if ((UP.AllowRemainder || (TripMultiple % PInfo.PragmaCount == 0)) && UCE.getUnrolledLoopSize(UP, PInfo.PragmaCount) < PragmaUnrollThreshold) return PInfo.PragmaCount; } if (PInfo.PragmaFullUnroll && TripCount != 0) { if (UCE.getUnrolledLoopSize(UP, TripCount) < PragmaUnrollThreshold) return TripCount; } // if didn't return until here, should continue to other priorties return None; } static Optional shouldFullUnroll( Loop *L, const TargetTransformInfo &TTI, DominatorTree &DT, ScalarEvolution &SE, const SmallPtrSetImpl &EphValues, const unsigned FullUnrollTripCount, const UnrollCostEstimator UCE, const TargetTransformInfo::UnrollingPreferences &UP) { assert(FullUnrollTripCount && "should be non-zero!"); if (FullUnrollTripCount > UP.FullUnrollMaxCount) return None; // When computing the unrolled size, note that BEInsns are not replicated // like the rest of the loop body. if (UCE.getUnrolledLoopSize(UP) < UP.Threshold) return FullUnrollTripCount; // 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, EphValues, TTI, UP.Threshold * UP.MaxPercentThresholdBoost / 100, UP.MaxIterationsCountToAnalyze)) { unsigned Boost = getFullUnrollBoostingFactor(*Cost, UP.MaxPercentThresholdBoost); if (Cost->UnrolledCost < UP.Threshold * Boost / 100) return FullUnrollTripCount; } return None; } static Optional shouldPartialUnroll(const unsigned LoopSize, const unsigned TripCount, const UnrollCostEstimator UCE, const TargetTransformInfo::UnrollingPreferences &UP) { if (!TripCount) return None; if (!UP.Partial) { LLVM_DEBUG(dbgs() << " will not try to unroll partially because " << "-unroll-allow-partial not given\n"); return 0; } unsigned count = UP.Count; if (count == 0) count = TripCount; if (UP.PartialThreshold != NoThreshold) { // Reduce unroll count to be modulo of TripCount for partial unrolling. if (UCE.getUnrolledLoopSize(UP, count) > UP.PartialThreshold) count = (std::max(UP.PartialThreshold, UP.BEInsns + 1) - UP.BEInsns) / (LoopSize - UP.BEInsns); if (count > UP.MaxCount) count = UP.MaxCount; while (count != 0 && TripCount % count != 0) count--; if (UP.AllowRemainder && 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. count = UP.DefaultUnrollRuntimeCount; while (count != 0 && UCE.getUnrolledLoopSize(UP, count) > UP.PartialThreshold) count >>= 1; } if (count < 2) { count = 0; } } else { count = TripCount; } if (count > UP.MaxCount) count = UP.MaxCount; LLVM_DEBUG(dbgs() << " partially unrolling with count: " << count << "\n"); return count; } // Returns true if unroll count was set explicitly. // Calculates unroll count and writes it to UP.Count. // Unless IgnoreUser is true, will also use metadata and command-line options // that are specific to to the LoopUnroll pass (which, for instance, are // irrelevant for the LoopUnrollAndJam pass). // FIXME: This function is used by LoopUnroll and LoopUnrollAndJam, but consumes // many LoopUnroll-specific options. The shared functionality should be // refactored into it own function. bool llvm::computeUnrollCount( Loop *L, const TargetTransformInfo &TTI, DominatorTree &DT, LoopInfo *LI, ScalarEvolution &SE, const SmallPtrSetImpl &EphValues, OptimizationRemarkEmitter *ORE, unsigned TripCount, unsigned MaxTripCount, bool MaxOrZero, unsigned TripMultiple, unsigned LoopSize, TargetTransformInfo::UnrollingPreferences &UP, TargetTransformInfo::PeelingPreferences &PP, bool &UseUpperBound) { UnrollCostEstimator UCE(*L, LoopSize); const bool UserUnrollCount = UnrollCount.getNumOccurrences() > 0; const bool PragmaFullUnroll = hasUnrollFullPragma(L); const unsigned PragmaCount = unrollCountPragmaValue(L); const bool PragmaEnableUnroll = hasUnrollEnablePragma(L); const bool ExplicitUnroll = PragmaCount > 0 || PragmaFullUnroll || PragmaEnableUnroll || UserUnrollCount; PragmaInfo PInfo(UserUnrollCount, PragmaFullUnroll, PragmaCount, PragmaEnableUnroll); // Use an explicit peel count that has been specified for testing. In this // case it's not permitted to also specify an explicit unroll count. if (PP.PeelCount) { if (UnrollCount.getNumOccurrences() > 0) { report_fatal_error("Cannot specify both explicit peel count and " "explicit unroll count"); } UP.Count = 1; UP.Runtime = false; return true; } // Check for explicit Count. // 1st priority is unroll count set by "unroll-count" option. // 2nd priority is unroll count set by pragma. if (auto UnrollFactor = shouldPragmaUnroll(L, PInfo, TripMultiple, TripCount, UCE, UP)) { UP.Count = *UnrollFactor; if (UserUnrollCount || (PragmaCount > 0)) { UP.AllowExpensiveTripCount = true; UP.Force = true; } UP.Runtime |= (PragmaCount > 0); return ExplicitUnroll; } else { 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 PragmaUnrollThreshold // 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 exact full unrolling. This will eliminate all copies // of some exit test. UP.Count = 0; if (TripCount) { UP.Count = TripCount; if (auto UnrollFactor = shouldFullUnroll(L, TTI, DT, SE, EphValues, TripCount, UCE, UP)) { UP.Count = *UnrollFactor; UseUpperBound = false; return ExplicitUnroll; } } // 4th priority is bounded unrolling. // 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 // constrained branch predictor resources so is controlled by an option.) // In addition we only unroll small upper bounds. // Note that the cost of bounded unrolling is always strictly greater than // cost of exact full unrolling. As such, if we have an exact count and // found it unprofitable, we'll never chose to bounded unroll. if (!TripCount && MaxTripCount && (UP.UpperBound || MaxOrZero) && MaxTripCount <= UnrollMaxUpperBound) { UP.Count = MaxTripCount; if (auto UnrollFactor = shouldFullUnroll(L, TTI, DT, SE, EphValues, MaxTripCount, UCE, UP)) { UP.Count = *UnrollFactor; UseUpperBound = true; return ExplicitUnroll; } } // 5th priority is loop peeling. computePeelCount(L, LoopSize, PP, TripCount, DT, SE, UP.Threshold); if (PP.PeelCount) { UP.Runtime = false; UP.Count = 1; return ExplicitUnroll; } // Before starting partial unrolling, set up.partial to true, // if user explicitly asked for unrolling if (TripCount) UP.Partial |= ExplicitUnroll; // 6th priority is partial unrolling. // Try partial unroll only when TripCount could be statically calculated. if (auto UnrollFactor = shouldPartialUnroll(LoopSize, TripCount, UCE, UP)) { UP.Count = *UnrollFactor; if ((PragmaFullUnroll || PragmaEnableUnroll) && TripCount && UP.Count != TripCount) ORE->emit([&]() { return OptimizationRemarkMissed(DEBUG_TYPE, "FullUnrollAsDirectedTooLarge", L->getStartLoc(), L->getHeader()) << "Unable to fully unroll loop as directed by unroll pragma " "because " "unrolled size is too large."; }); if (UP.PartialThreshold != NoThreshold) { if (UP.Count == 0) { if (PragmaEnableUnroll) ORE->emit([&]() { return OptimizationRemarkMissed(DEBUG_TYPE, "UnrollAsDirectedTooLarge", L->getStartLoc(), L->getHeader()) << "Unable to unroll loop as directed by unroll(enable) " "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([&]() { return 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."; }); // 7th priority is runtime unrolling. // Don't unroll a runtime trip count loop when it is disabled. if (hasRuntimeUnrollDisablePragma(L)) { UP.Count = 0; return false; } // Don't unroll a small upper bound loop unless user or TTI asked to do so. if (MaxTripCount && !UP.Force && MaxTripCount < UnrollMaxUpperBound) { UP.Count = 0; return false; } // Check if the runtime trip count is too small when profile is available. if (L->getHeader()->getParent()->hasProfileData()) { if (auto ProfileTripCount = getLoopEstimatedTripCount(L)) { if (*ProfileTripCount < FlatLoopTripCountThreshold) return false; else UP.AllowExpensiveTripCount = true; } } UP.Runtime |= PragmaEnableUnroll || PragmaCount > 0 || UserUnrollCount; if (!UP.Runtime) { LLVM_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 && UCE.getUnrolledLoopSize(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; LLVM_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 (unrollCountPragmaValue(L) > 0 && !UP.AllowRemainder) ORE->emit([&]() { return 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; if (MaxTripCount && UP.Count > MaxTripCount) UP.Count = MaxTripCount; LLVM_DEBUG(dbgs() << " runtime unrolling with count: " << UP.Count << "\n"); if (UP.Count < 2) UP.Count = 0; return ExplicitUnroll; } static LoopUnrollResult tryToUnrollLoop( Loop *L, DominatorTree &DT, LoopInfo *LI, ScalarEvolution &SE, const TargetTransformInfo &TTI, AssumptionCache &AC, OptimizationRemarkEmitter &ORE, BlockFrequencyInfo *BFI, ProfileSummaryInfo *PSI, bool PreserveLCSSA, int OptLevel, bool OnlyWhenForced, bool ForgetAllSCEV, Optional ProvidedCount, Optional ProvidedThreshold, Optional ProvidedAllowPartial, Optional ProvidedRuntime, Optional ProvidedUpperBound, Optional ProvidedAllowPeeling, Optional ProvidedAllowProfileBasedPeeling, Optional ProvidedFullUnrollMaxCount) { LLVM_DEBUG(dbgs() << "Loop Unroll: F[" << L->getHeader()->getParent()->getName() << "] Loop %" << L->getHeader()->getName() << "\n"); TransformationMode TM = hasUnrollTransformation(L); if (TM & TM_Disable) return LoopUnrollResult::Unmodified; // If this loop isn't forced to be unrolled, avoid unrolling it when the // parent loop has an explicit unroll-and-jam pragma. This is to prevent // automatic unrolling from interfering with the user requested // transformation. Loop *ParentL = L->getParentLoop(); if (ParentL != nullptr && hasUnrollAndJamTransformation(ParentL) == TM_ForcedByUser && hasUnrollTransformation(L) != TM_ForcedByUser) { LLVM_DEBUG(dbgs() << "Not unrolling loop since parent loop has" << " llvm.loop.unroll_and_jam.\n"); return LoopUnrollResult::Unmodified; } // If this loop isn't forced to be unrolled, avoid unrolling it when the // loop has an explicit unroll-and-jam pragma. This is to prevent automatic // unrolling from interfering with the user requested transformation. if (hasUnrollAndJamTransformation(L) == TM_ForcedByUser && hasUnrollTransformation(L) != TM_ForcedByUser) { LLVM_DEBUG( dbgs() << " Not unrolling loop since it has llvm.loop.unroll_and_jam.\n"); return LoopUnrollResult::Unmodified; } if (!L->isLoopSimplifyForm()) { LLVM_DEBUG( dbgs() << " Not unrolling loop which is not in loop-simplify form.\n"); return LoopUnrollResult::Unmodified; } // When automatic unrolling is disabled, do not unroll unless overridden for // this loop. if (OnlyWhenForced && !(TM & TM_Enable)) return LoopUnrollResult::Unmodified; bool OptForSize = L->getHeader()->getParent()->hasOptSize(); unsigned NumInlineCandidates; bool NotDuplicatable; bool Convergent; TargetTransformInfo::UnrollingPreferences UP = gatherUnrollingPreferences( L, SE, TTI, BFI, PSI, ORE, OptLevel, ProvidedThreshold, ProvidedCount, ProvidedAllowPartial, ProvidedRuntime, ProvidedUpperBound, ProvidedFullUnrollMaxCount); TargetTransformInfo::PeelingPreferences PP = gatherPeelingPreferences( L, SE, TTI, ProvidedAllowPeeling, ProvidedAllowProfileBasedPeeling, true); // Exit early if unrolling is disabled. For OptForSize, we pick the loop size // as threshold later on. if (UP.Threshold == 0 && (!UP.Partial || UP.PartialThreshold == 0) && !OptForSize) return LoopUnrollResult::Unmodified; SmallPtrSet EphValues; CodeMetrics::collectEphemeralValues(L, &AC, EphValues); unsigned LoopSize = ApproximateLoopSize(L, NumInlineCandidates, NotDuplicatable, Convergent, TTI, EphValues, UP.BEInsns); LLVM_DEBUG(dbgs() << " Loop Size = " << LoopSize << "\n"); if (NotDuplicatable) { LLVM_DEBUG(dbgs() << " Not unrolling loop which contains non-duplicatable" << " instructions.\n"); return LoopUnrollResult::Unmodified; } // When optimizing for size, use LoopSize + 1 as threshold (we use < Threshold // later), to (fully) unroll loops, if it does not increase code size. if (OptForSize) UP.Threshold = std::max(UP.Threshold, LoopSize + 1); if (NumInlineCandidates != 0) { LLVM_DEBUG(dbgs() << " Not unrolling loop with inlinable calls.\n"); return LoopUnrollResult::Unmodified; } // Find the smallest exact trip count for any exit. This is an upper bound // on the loop trip count, but an exit at an earlier iteration is still // possible. An unroll by the smallest exact trip count guarantees that all // brnaches relating to at least one exit can be eliminated. This is unlike // the max trip count, which only guarantees that the backedge can be broken. unsigned TripCount = 0; unsigned TripMultiple = 1; SmallVector ExitingBlocks; L->getExitingBlocks(ExitingBlocks); for (BasicBlock *ExitingBlock : ExitingBlocks) if (unsigned TC = SE.getSmallConstantTripCount(L, ExitingBlock)) if (!TripCount || TC < TripCount) TripCount = TripMultiple = TC; if (!TripCount) { // If no exact trip count is known, determine the trip multiple of either // the loop latch or the single exiting block. // TODO: Relax for multiple exits. BasicBlock *ExitingBlock = L->getLoopLatch(); if (!ExitingBlock || !L->isLoopExiting(ExitingBlock)) ExitingBlock = L->getExitingBlock(); if (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 unrolling 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. unsigned MaxTripCount = 0; bool MaxOrZero = false; if (!TripCount) { MaxTripCount = SE.getSmallConstantMaxTripCount(L); MaxOrZero = SE.isBackedgeTakenCountMaxOrZero(L); } // 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, EphValues, &ORE, TripCount, MaxTripCount, MaxOrZero, TripMultiple, LoopSize, UP, PP, UseUpperBound); if (!UP.Count) return LoopUnrollResult::Unmodified; if (PP.PeelCount) { assert(UP.Count == 1 && "Cannot perform peel and unroll in the same step"); LLVM_DEBUG(dbgs() << "PEELING loop %" << L->getHeader()->getName() << " with iteration count " << PP.PeelCount << "!\n"); ORE.emit([&]() { return OptimizationRemark(DEBUG_TYPE, "Peeled", L->getStartLoc(), L->getHeader()) << " peeled loop by " << ore::NV("PeelCount", PP.PeelCount) << " iterations"; }); if (peelLoop(L, PP.PeelCount, LI, &SE, DT, &AC, PreserveLCSSA)) { simplifyLoopAfterUnroll(L, true, LI, &SE, &DT, &AC, &TTI); // 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 (PP.PeelProfiledIterations) L->setLoopAlreadyUnrolled(); return LoopUnrollResult::PartiallyUnrolled; } return LoopUnrollResult::Unmodified; } // At this point, UP.Runtime indicates that run-time unrolling is allowed. // However, we only want to actually perform it if we don't know the trip // count and the unroll count doesn't divide the known trip multiple. // TODO: This decision should probably be pushed up into // computeUnrollCount(). UP.Runtime &= TripCount == 0 && TripMultiple % UP.Count != 0; // Save loop properties before it is transformed. MDNode *OrigLoopID = L->getLoopID(); // Unroll the loop. Loop *RemainderLoop = nullptr; LoopUnrollResult UnrollResult = UnrollLoop( L, {UP.Count, UP.Force, UP.Runtime, UP.AllowExpensiveTripCount, UP.UnrollRemainder, ForgetAllSCEV}, LI, &SE, &DT, &AC, &TTI, &ORE, PreserveLCSSA, &RemainderLoop); if (UnrollResult == LoopUnrollResult::Unmodified) return LoopUnrollResult::Unmodified; if (RemainderLoop) { Optional RemainderLoopID = makeFollowupLoopID(OrigLoopID, {LLVMLoopUnrollFollowupAll, LLVMLoopUnrollFollowupRemainder}); if (RemainderLoopID.hasValue()) RemainderLoop->setLoopID(RemainderLoopID.getValue()); } if (UnrollResult != LoopUnrollResult::FullyUnrolled) { Optional NewLoopID = makeFollowupLoopID(OrigLoopID, {LLVMLoopUnrollFollowupAll, LLVMLoopUnrollFollowupUnrolled}); if (NewLoopID.hasValue()) { L->setLoopID(NewLoopID.getValue()); // Do not setLoopAlreadyUnrolled if loop attributes have been specified // explicitly. return UnrollResult; } } // If loop has an unroll count pragma or unrolled by explicitly set count // mark loop as unrolled to prevent unrolling beyond that requested. if (UnrollResult != LoopUnrollResult::FullyUnrolled && IsCountSetExplicitly) L->setLoopAlreadyUnrolled(); return UnrollResult; } namespace { class LoopUnroll : public LoopPass { public: static char ID; // Pass ID, replacement for typeid int OptLevel; /// If false, use a cost model to determine whether unrolling of a loop is /// profitable. If true, only loops that explicitly request unrolling via /// metadata are considered. All other loops are skipped. bool OnlyWhenForced; /// If false, when SCEV is invalidated, only forget everything in the /// top-most loop (call forgetTopMostLoop), of the loop being processed. /// Otherwise, forgetAllLoops and rebuild when needed next. bool ForgetAllSCEV; Optional ProvidedCount; Optional ProvidedThreshold; Optional ProvidedAllowPartial; Optional ProvidedRuntime; Optional ProvidedUpperBound; Optional ProvidedAllowPeeling; Optional ProvidedAllowProfileBasedPeeling; Optional ProvidedFullUnrollMaxCount; LoopUnroll(int OptLevel = 2, bool OnlyWhenForced = false, bool ForgetAllSCEV = false, Optional Threshold = None, Optional Count = None, Optional AllowPartial = None, Optional Runtime = None, Optional UpperBound = None, Optional AllowPeeling = None, Optional AllowProfileBasedPeeling = None, Optional ProvidedFullUnrollMaxCount = None) : LoopPass(ID), OptLevel(OptLevel), OnlyWhenForced(OnlyWhenForced), ForgetAllSCEV(ForgetAllSCEV), ProvidedCount(std::move(Count)), ProvidedThreshold(Threshold), ProvidedAllowPartial(AllowPartial), ProvidedRuntime(Runtime), ProvidedUpperBound(UpperBound), ProvidedAllowPeeling(AllowPeeling), ProvidedAllowProfileBasedPeeling(AllowProfileBasedPeeling), ProvidedFullUnrollMaxCount(ProvidedFullUnrollMaxCount) { initializeLoopUnrollPass(*PassRegistry::getPassRegistry()); } bool runOnLoop(Loop *L, LPPassManager &LPM) 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); LoopUnrollResult Result = tryToUnrollLoop( L, DT, LI, SE, TTI, AC, ORE, nullptr, nullptr, PreserveLCSSA, OptLevel, OnlyWhenForced, ForgetAllSCEV, ProvidedCount, ProvidedThreshold, ProvidedAllowPartial, ProvidedRuntime, ProvidedUpperBound, ProvidedAllowPeeling, ProvidedAllowProfileBasedPeeling, ProvidedFullUnrollMaxCount); if (Result == LoopUnrollResult::FullyUnrolled) LPM.markLoopAsDeleted(*L); return Result != LoopUnrollResult::Unmodified; } /// 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); } }; } // end anonymous namespace 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, bool OnlyWhenForced, bool ForgetAllSCEV, int Threshold, int Count, int AllowPartial, int Runtime, int UpperBound, int AllowPeeling) { // 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, OnlyWhenForced, ForgetAllSCEV, 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), AllowPeeling == -1 ? None : Optional(AllowPeeling)); } Pass *llvm::createSimpleLoopUnrollPass(int OptLevel, bool OnlyWhenForced, bool ForgetAllSCEV) { return createLoopUnrollPass(OptLevel, OnlyWhenForced, ForgetAllSCEV, -1, -1, 0, 0, 0, 1); } PreservedAnalyses LoopFullUnrollPass::run(Loop &L, LoopAnalysisManager &AM, LoopStandardAnalysisResults &AR, LPMUpdater &Updater) { // For the new 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(L.getHeader()->getParent()); // Keep track of the previous loop structure so we can identify new loops // created by unrolling. Loop *ParentL = L.getParentLoop(); SmallPtrSet OldLoops; if (ParentL) OldLoops.insert(ParentL->begin(), ParentL->end()); else OldLoops.insert(AR.LI.begin(), AR.LI.end()); std::string LoopName = std::string(L.getName()); bool Changed = tryToUnrollLoop(&L, AR.DT, &AR.LI, AR.SE, AR.TTI, AR.AC, ORE, /*BFI*/ nullptr, /*PSI*/ nullptr, /*PreserveLCSSA*/ true, OptLevel, OnlyWhenForced, ForgetSCEV, /*Count*/ None, /*Threshold*/ None, /*AllowPartial*/ false, /*Runtime*/ false, /*UpperBound*/ false, /*AllowPeeling*/ true, /*AllowProfileBasedPeeling*/ false, /*FullUnrollMaxCount*/ None) != LoopUnrollResult::Unmodified; 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: // - 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. // // When a new loop appears as a sibling loop after 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 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.contains(SibLoop); }); Updater.addSiblingLoops(SibLoops); if (!IsCurrentLoopValid) { Updater.markLoopAsDeleted(L, LoopName); } else { // We can only walk child loops if the current loop remained valid. if (UnrollRevisitChildLoops) { // Walk *all* of the child loops. SmallVector ChildLoops(L.begin(), L.end()); Updater.addChildLoops(ChildLoops); } } return getLoopPassPreservedAnalyses(); } PreservedAnalyses LoopUnrollPass::run(Function &F, FunctionAnalysisManager &AM) { auto &SE = AM.getResult(F); auto &LI = AM.getResult(F); auto &TTI = AM.getResult(F); auto &DT = AM.getResult(F); auto &AC = AM.getResult(F); auto &ORE = AM.getResult(F); LoopAnalysisManager *LAM = nullptr; if (auto *LAMProxy = AM.getCachedResult(F)) LAM = &LAMProxy->getManager(); auto &MAMProxy = AM.getResult(F); ProfileSummaryInfo *PSI = MAMProxy.getCachedResult(*F.getParent()); auto *BFI = (PSI && PSI->hasProfileSummary()) ? &AM.getResult(F) : nullptr; bool Changed = false; // The unroller requires loops to be in simplified form, and also needs LCSSA. // Since simplification may add new inner loops, it has to run before the // legality and profitability checks. This means running the loop unroller // will simplify all loops, regardless of whether anything end up being // unrolled. for (auto &L : LI) { Changed |= simplifyLoop(L, &DT, &LI, &SE, &AC, nullptr, false /* PreserveLCSSA */); Changed |= formLCSSARecursively(*L, DT, &LI, &SE); } // Add the loop nests in the reverse order of LoopInfo. See method // declaration. SmallPriorityWorklist Worklist; appendLoopsToWorklist(LI, Worklist); while (!Worklist.empty()) { // Because the LoopInfo stores the loops in RPO, we walk the worklist // from back to front so that we work forward across the CFG, which // for unrolling is only needed to get optimization remarks emitted in // a forward order. Loop &L = *Worklist.pop_back_val(); #ifndef NDEBUG Loop *ParentL = L.getParentLoop(); #endif // Check if the profile summary indicates that the profiled application // has a huge working set size, in which case we disable peeling to avoid // bloating it further. Optional LocalAllowPeeling = UnrollOpts.AllowPeeling; if (PSI && PSI->hasHugeWorkingSetSize()) LocalAllowPeeling = false; std::string LoopName = std::string(L.getName()); // The API here is quite complex to call and we allow to select some // flavors of unrolling during construction time (by setting UnrollOpts). LoopUnrollResult Result = tryToUnrollLoop( &L, DT, &LI, SE, TTI, AC, ORE, BFI, PSI, /*PreserveLCSSA*/ true, UnrollOpts.OptLevel, UnrollOpts.OnlyWhenForced, UnrollOpts.ForgetSCEV, /*Count*/ None, /*Threshold*/ None, UnrollOpts.AllowPartial, UnrollOpts.AllowRuntime, UnrollOpts.AllowUpperBound, LocalAllowPeeling, UnrollOpts.AllowProfileBasedPeeling, UnrollOpts.FullUnrollMaxCount); Changed |= Result != LoopUnrollResult::Unmodified; // The parent must not be damaged by unrolling! #ifndef NDEBUG if (Result != LoopUnrollResult::Unmodified && ParentL) ParentL->verifyLoop(); #endif // Clear any cached analysis results for L if we removed it completely. if (LAM && Result == LoopUnrollResult::FullyUnrolled) LAM->clear(L, LoopName); } if (!Changed) return PreservedAnalyses::all(); return getLoopPassPreservedAnalyses(); } void LoopUnrollPass::printPipeline( raw_ostream &OS, function_ref MapClassName2PassName) { static_cast *>(this)->printPipeline( OS, MapClassName2PassName); OS << "<"; if (UnrollOpts.AllowPartial != None) OS << (UnrollOpts.AllowPartial.getValue() ? "" : "no-") << "partial;"; if (UnrollOpts.AllowPeeling != None) OS << (UnrollOpts.AllowPeeling.getValue() ? "" : "no-") << "peeling;"; if (UnrollOpts.AllowRuntime != None) OS << (UnrollOpts.AllowRuntime.getValue() ? "" : "no-") << "runtime;"; if (UnrollOpts.AllowUpperBound != None) OS << (UnrollOpts.AllowUpperBound.getValue() ? "" : "no-") << "upperbound;"; if (UnrollOpts.AllowProfileBasedPeeling != None) OS << (UnrollOpts.AllowProfileBasedPeeling.getValue() ? "" : "no-") << "profile-peeling;"; if (UnrollOpts.FullUnrollMaxCount != None) OS << "full-unroll-max=" << UnrollOpts.FullUnrollMaxCount << ";"; OS << "O" << UnrollOpts.OptLevel; OS << ">"; }