//===-- SpillPlacement.cpp - Optimal Spill Code Placement -----------------===// // // The LLVM Compiler Infrastructure // // This file is distributed under the University of Illinois Open Source // License. See LICENSE.TXT for details. // //===----------------------------------------------------------------------===// // // This file implements the spill code placement analysis. // // Each edge bundle corresponds to a node in a Hopfield network. Constraints on // basic blocks are weighted by the block frequency and added to become the node // bias. // // Transparent basic blocks have the variable live through, but don't care if it // is spilled or in a register. These blocks become connections in the Hopfield // network, again weighted by block frequency. // // The Hopfield network minimizes (possibly locally) its energy function: // // E = -sum_n V_n * ( B_n + sum_{n, m linked by b} V_m * F_b ) // // The energy function represents the expected spill code execution frequency, // or the cost of spilling. This is a Lyapunov function which never increases // when a node is updated. It is guaranteed to converge to a local minimum. // //===----------------------------------------------------------------------===// #include "SpillPlacement.h" #include "llvm/ADT/BitVector.h" #include "llvm/CodeGen/EdgeBundles.h" #include "llvm/CodeGen/MachineBasicBlock.h" #include "llvm/CodeGen/MachineBlockFrequencyInfo.h" #include "llvm/CodeGen/MachineFunction.h" #include "llvm/CodeGen/MachineLoopInfo.h" #include "llvm/CodeGen/Passes.h" #include "llvm/Support/Debug.h" #include "llvm/Support/ManagedStatic.h" using namespace llvm; #define DEBUG_TYPE "spillplacement" char SpillPlacement::ID = 0; INITIALIZE_PASS_BEGIN(SpillPlacement, "spill-code-placement", "Spill Code Placement Analysis", true, true) INITIALIZE_PASS_DEPENDENCY(EdgeBundles) INITIALIZE_PASS_DEPENDENCY(MachineLoopInfo) INITIALIZE_PASS_END(SpillPlacement, "spill-code-placement", "Spill Code Placement Analysis", true, true) char &llvm::SpillPlacementID = SpillPlacement::ID; void SpillPlacement::getAnalysisUsage(AnalysisUsage &AU) const { AU.setPreservesAll(); AU.addRequired<MachineBlockFrequencyInfo>(); AU.addRequiredTransitive<EdgeBundles>(); AU.addRequiredTransitive<MachineLoopInfo>(); MachineFunctionPass::getAnalysisUsage(AU); } /// Node - Each edge bundle corresponds to a Hopfield node. /// /// The node contains precomputed frequency data that only depends on the CFG, /// but Bias and Links are computed each time placeSpills is called. /// /// The node Value is positive when the variable should be in a register. The /// value can change when linked nodes change, but convergence is very fast /// because all weights are positive. /// struct SpillPlacement::Node { /// BiasN - Sum of blocks that prefer a spill. BlockFrequency BiasN; /// BiasP - Sum of blocks that prefer a register. BlockFrequency BiasP; /// Value - Output value of this node computed from the Bias and links. /// This is always on of the values {-1, 0, 1}. A positive number means the /// variable should go in a register through this bundle. int Value; typedef SmallVector<std::pair<BlockFrequency, unsigned>, 4> LinkVector; /// Links - (Weight, BundleNo) for all transparent blocks connecting to other /// bundles. The weights are all positive block frequencies. LinkVector Links; /// SumLinkWeights - Cached sum of the weights of all links + ThresHold. BlockFrequency SumLinkWeights; /// preferReg - Return true when this node prefers to be in a register. bool preferReg() const { // Undecided nodes (Value==0) go on the stack. return Value > 0; } /// mustSpill - Return True if this node is so biased that it must spill. bool mustSpill() const { // We must spill if Bias < -sum(weights) or the MustSpill flag was set. // BiasN is saturated when MustSpill is set, make sure this still returns // true when the RHS saturates. Note that SumLinkWeights includes Threshold. return BiasN >= BiasP + SumLinkWeights; } /// clear - Reset per-query data, but preserve frequencies that only depend on // the CFG. void clear(const BlockFrequency &Threshold) { BiasN = BiasP = Value = 0; SumLinkWeights = Threshold; Links.clear(); } /// addLink - Add a link to bundle b with weight w. void addLink(unsigned b, BlockFrequency w) { // Update cached sum. SumLinkWeights += w; // There can be multiple links to the same bundle, add them up. for (LinkVector::iterator I = Links.begin(), E = Links.end(); I != E; ++I) if (I->second == b) { I->first += w; return; } // This must be the first link to b. Links.push_back(std::make_pair(w, b)); } /// addBias - Bias this node. void addBias(BlockFrequency freq, BorderConstraint direction) { switch (direction) { default: break; case PrefReg: BiasP += freq; break; case PrefSpill: BiasN += freq; break; case MustSpill: BiasN = BlockFrequency::getMaxFrequency(); break; } } /// update - Recompute Value from Bias and Links. Return true when node /// preference changes. bool update(const Node nodes[], const BlockFrequency &Threshold) { // Compute the weighted sum of inputs. BlockFrequency SumN = BiasN; BlockFrequency SumP = BiasP; for (LinkVector::iterator I = Links.begin(), E = Links.end(); I != E; ++I) { if (nodes[I->second].Value == -1) SumN += I->first; else if (nodes[I->second].Value == 1) SumP += I->first; } // Each weighted sum is going to be less than the total frequency of the // bundle. Ideally, we should simply set Value = sign(SumP - SumN), but we // will add a dead zone around 0 for two reasons: // // 1. It avoids arbitrary bias when all links are 0 as is possible during // initial iterations. // 2. It helps tame rounding errors when the links nominally sum to 0. // bool Before = preferReg(); if (SumN >= SumP + Threshold) Value = -1; else if (SumP >= SumN + Threshold) Value = 1; else Value = 0; return Before != preferReg(); } void getDissentingNeighbors(SparseSet<unsigned> &List, const Node nodes[]) const { for (const auto &Elt : Links) { unsigned n = Elt.second; // Neighbors that already have the same value are not going to // change because of this node changing. if (Value != nodes[n].Value) List.insert(n); } } }; bool SpillPlacement::runOnMachineFunction(MachineFunction &mf) { MF = &mf; bundles = &getAnalysis<EdgeBundles>(); loops = &getAnalysis<MachineLoopInfo>(); assert(!nodes && "Leaking node array"); nodes = new Node[bundles->getNumBundles()]; TodoList.clear(); TodoList.setUniverse(bundles->getNumBundles()); // Compute total ingoing and outgoing block frequencies for all bundles. BlockFrequencies.resize(mf.getNumBlockIDs()); MBFI = &getAnalysis<MachineBlockFrequencyInfo>(); setThreshold(MBFI->getEntryFreq()); for (auto &I : mf) { unsigned Num = I.getNumber(); BlockFrequencies[Num] = MBFI->getBlockFreq(&I); } // We never change the function. return false; } void SpillPlacement::releaseMemory() { delete[] nodes; nodes = nullptr; TodoList.clear(); } /// activate - mark node n as active if it wasn't already. void SpillPlacement::activate(unsigned n) { TodoList.insert(n); if (ActiveNodes->test(n)) return; ActiveNodes->set(n); nodes[n].clear(Threshold); // Very large bundles usually come from big switches, indirect branches, // landing pads, or loops with many 'continue' statements. It is difficult to // allocate registers when so many different blocks are involved. // // Give a small negative bias to large bundles such that a substantial // fraction of the connected blocks need to be interested before we consider // expanding the region through the bundle. This helps compile time by // limiting the number of blocks visited and the number of links in the // Hopfield network. if (bundles->getBlocks(n).size() > 100) { nodes[n].BiasP = 0; nodes[n].BiasN = (MBFI->getEntryFreq() / 16); } } /// \brief Set the threshold for a given entry frequency. /// /// Set the threshold relative to \c Entry. Since the threshold is used as a /// bound on the open interval (-Threshold;Threshold), 1 is the minimum /// threshold. void SpillPlacement::setThreshold(const BlockFrequency &Entry) { // Apparently 2 is a good threshold when Entry==2^14, but we need to scale // it. Divide by 2^13, rounding as appropriate. uint64_t Freq = Entry.getFrequency(); uint64_t Scaled = (Freq >> 13) + bool(Freq & (1 << 12)); Threshold = std::max(UINT64_C(1), Scaled); } /// addConstraints - Compute node biases and weights from a set of constraints. /// Set a bit in NodeMask for each active node. void SpillPlacement::addConstraints(ArrayRef<BlockConstraint> LiveBlocks) { for (ArrayRef<BlockConstraint>::iterator I = LiveBlocks.begin(), E = LiveBlocks.end(); I != E; ++I) { BlockFrequency Freq = BlockFrequencies[I->Number]; // Live-in to block? if (I->Entry != DontCare) { unsigned ib = bundles->getBundle(I->Number, 0); activate(ib); nodes[ib].addBias(Freq, I->Entry); } // Live-out from block? if (I->Exit != DontCare) { unsigned ob = bundles->getBundle(I->Number, 1); activate(ob); nodes[ob].addBias(Freq, I->Exit); } } } /// addPrefSpill - Same as addConstraints(PrefSpill) void SpillPlacement::addPrefSpill(ArrayRef<unsigned> Blocks, bool Strong) { for (ArrayRef<unsigned>::iterator I = Blocks.begin(), E = Blocks.end(); I != E; ++I) { BlockFrequency Freq = BlockFrequencies[*I]; if (Strong) Freq += Freq; unsigned ib = bundles->getBundle(*I, 0); unsigned ob = bundles->getBundle(*I, 1); activate(ib); activate(ob); nodes[ib].addBias(Freq, PrefSpill); nodes[ob].addBias(Freq, PrefSpill); } } void SpillPlacement::addLinks(ArrayRef<unsigned> Links) { for (ArrayRef<unsigned>::iterator I = Links.begin(), E = Links.end(); I != E; ++I) { unsigned Number = *I; unsigned ib = bundles->getBundle(Number, 0); unsigned ob = bundles->getBundle(Number, 1); // Ignore self-loops. if (ib == ob) continue; activate(ib); activate(ob); BlockFrequency Freq = BlockFrequencies[Number]; nodes[ib].addLink(ob, Freq); nodes[ob].addLink(ib, Freq); } } bool SpillPlacement::scanActiveBundles() { RecentPositive.clear(); for (int n = ActiveNodes->find_first(); n>=0; n = ActiveNodes->find_next(n)) { update(n); // A node that must spill, or a node without any links is not going to // change its value ever again, so exclude it from iterations. if (nodes[n].mustSpill()) continue; if (nodes[n].preferReg()) RecentPositive.push_back(n); } return !RecentPositive.empty(); } bool SpillPlacement::update(unsigned n) { if (!nodes[n].update(nodes, Threshold)) return false; nodes[n].getDissentingNeighbors(TodoList, nodes); return true; } /// iterate - Repeatedly update the Hopfield nodes until stability or the /// maximum number of iterations is reached. void SpillPlacement::iterate() { // We do not need to push those node in the todolist. // They are already been proceeded as part of the previous iteration. RecentPositive.clear(); // Since the last iteration, the todolist have been augmented by calls // to addConstraints, addLinks, and co. // Update the network energy starting at this new frontier. // The call to ::update will add the nodes that changed into the todolist. unsigned Limit = bundles->getNumBundles() * 10; while(Limit-- > 0 && !TodoList.empty()) { unsigned n = TodoList.pop_back_val(); if (!update(n)) continue; if (nodes[n].preferReg()) RecentPositive.push_back(n); } } void SpillPlacement::prepare(BitVector &RegBundles) { RecentPositive.clear(); TodoList.clear(); // Reuse RegBundles as our ActiveNodes vector. ActiveNodes = &RegBundles; ActiveNodes->clear(); ActiveNodes->resize(bundles->getNumBundles()); } bool SpillPlacement::finish() { assert(ActiveNodes && "Call prepare() first"); // Write preferences back to ActiveNodes. bool Perfect = true; for (int n = ActiveNodes->find_first(); n>=0; n = ActiveNodes->find_next(n)) if (!nodes[n].preferReg()) { ActiveNodes->reset(n); Perfect = false; } ActiveNodes = nullptr; return Perfect; }