380 lines
12 KiB
C++
380 lines
12 KiB
C++
//===- SpillPlacement.cpp - Optimal Spill Code Placement ------------------===//
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//
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// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
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// See https://llvm.org/LICENSE.txt for license information.
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// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
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//
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//===----------------------------------------------------------------------===//
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//
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// This file implements the spill code placement analysis.
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//
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// Each edge bundle corresponds to a node in a Hopfield network. Constraints on
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// basic blocks are weighted by the block frequency and added to become the node
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// bias.
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//
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// Transparent basic blocks have the variable live through, but don't care if it
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// is spilled or in a register. These blocks become connections in the Hopfield
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// network, again weighted by block frequency.
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//
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// The Hopfield network minimizes (possibly locally) its energy function:
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//
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// E = -sum_n V_n * ( B_n + sum_{n, m linked by b} V_m * F_b )
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//
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// The energy function represents the expected spill code execution frequency,
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// or the cost of spilling. This is a Lyapunov function which never increases
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// when a node is updated. It is guaranteed to converge to a local minimum.
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//
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//===----------------------------------------------------------------------===//
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#include "SpillPlacement.h"
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#include "llvm/ADT/BitVector.h"
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#include "llvm/CodeGen/EdgeBundles.h"
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#include "llvm/CodeGen/MachineBasicBlock.h"
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#include "llvm/CodeGen/MachineBlockFrequencyInfo.h"
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#include "llvm/CodeGen/MachineFunction.h"
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#include "llvm/CodeGen/MachineLoopInfo.h"
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#include "llvm/CodeGen/Passes.h"
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#include "llvm/InitializePasses.h"
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#include "llvm/Pass.h"
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#include <algorithm>
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#include <cassert>
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#include <cstdint>
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#include <utility>
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using namespace llvm;
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#define DEBUG_TYPE "spill-code-placement"
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char SpillPlacement::ID = 0;
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char &llvm::SpillPlacementID = SpillPlacement::ID;
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INITIALIZE_PASS_BEGIN(SpillPlacement, DEBUG_TYPE,
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"Spill Code Placement Analysis", true, true)
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INITIALIZE_PASS_DEPENDENCY(EdgeBundles)
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INITIALIZE_PASS_DEPENDENCY(MachineLoopInfo)
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INITIALIZE_PASS_END(SpillPlacement, DEBUG_TYPE,
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"Spill Code Placement Analysis", true, true)
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void SpillPlacement::getAnalysisUsage(AnalysisUsage &AU) const {
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AU.setPreservesAll();
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AU.addRequired<MachineBlockFrequencyInfo>();
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AU.addRequiredTransitive<EdgeBundles>();
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AU.addRequiredTransitive<MachineLoopInfo>();
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MachineFunctionPass::getAnalysisUsage(AU);
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}
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/// Node - Each edge bundle corresponds to a Hopfield node.
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///
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/// The node contains precomputed frequency data that only depends on the CFG,
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/// but Bias and Links are computed each time placeSpills is called.
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///
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/// The node Value is positive when the variable should be in a register. The
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/// value can change when linked nodes change, but convergence is very fast
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/// because all weights are positive.
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struct SpillPlacement::Node {
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/// BiasN - Sum of blocks that prefer a spill.
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BlockFrequency BiasN;
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/// BiasP - Sum of blocks that prefer a register.
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BlockFrequency BiasP;
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/// Value - Output value of this node computed from the Bias and links.
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/// This is always on of the values {-1, 0, 1}. A positive number means the
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/// variable should go in a register through this bundle.
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int Value;
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using LinkVector = SmallVector<std::pair<BlockFrequency, unsigned>, 4>;
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/// Links - (Weight, BundleNo) for all transparent blocks connecting to other
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/// bundles. The weights are all positive block frequencies.
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LinkVector Links;
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/// SumLinkWeights - Cached sum of the weights of all links + ThresHold.
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BlockFrequency SumLinkWeights;
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/// preferReg - Return true when this node prefers to be in a register.
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bool preferReg() const {
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// Undecided nodes (Value==0) go on the stack.
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return Value > 0;
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}
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/// mustSpill - Return True if this node is so biased that it must spill.
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bool mustSpill() const {
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// We must spill if Bias < -sum(weights) or the MustSpill flag was set.
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// BiasN is saturated when MustSpill is set, make sure this still returns
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// true when the RHS saturates. Note that SumLinkWeights includes Threshold.
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return BiasN >= BiasP + SumLinkWeights;
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}
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/// clear - Reset per-query data, but preserve frequencies that only depend on
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/// the CFG.
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void clear(const BlockFrequency &Threshold) {
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BiasN = BiasP = Value = 0;
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SumLinkWeights = Threshold;
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Links.clear();
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}
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/// addLink - Add a link to bundle b with weight w.
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void addLink(unsigned b, BlockFrequency w) {
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// Update cached sum.
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SumLinkWeights += w;
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// There can be multiple links to the same bundle, add them up.
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for (LinkVector::iterator I = Links.begin(), E = Links.end(); I != E; ++I)
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if (I->second == b) {
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I->first += w;
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return;
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}
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// This must be the first link to b.
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Links.push_back(std::make_pair(w, b));
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}
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/// addBias - Bias this node.
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void addBias(BlockFrequency freq, BorderConstraint direction) {
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switch (direction) {
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default:
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break;
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case PrefReg:
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BiasP += freq;
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break;
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case PrefSpill:
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BiasN += freq;
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break;
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case MustSpill:
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BiasN = BlockFrequency::getMaxFrequency();
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break;
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}
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}
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/// update - Recompute Value from Bias and Links. Return true when node
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/// preference changes.
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bool update(const Node nodes[], const BlockFrequency &Threshold) {
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// Compute the weighted sum of inputs.
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BlockFrequency SumN = BiasN;
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BlockFrequency SumP = BiasP;
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for (LinkVector::iterator I = Links.begin(), E = Links.end(); I != E; ++I) {
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if (nodes[I->second].Value == -1)
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SumN += I->first;
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else if (nodes[I->second].Value == 1)
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SumP += I->first;
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}
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// Each weighted sum is going to be less than the total frequency of the
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// bundle. Ideally, we should simply set Value = sign(SumP - SumN), but we
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// will add a dead zone around 0 for two reasons:
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//
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// 1. It avoids arbitrary bias when all links are 0 as is possible during
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// initial iterations.
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// 2. It helps tame rounding errors when the links nominally sum to 0.
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//
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bool Before = preferReg();
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if (SumN >= SumP + Threshold)
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Value = -1;
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else if (SumP >= SumN + Threshold)
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Value = 1;
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else
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Value = 0;
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return Before != preferReg();
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}
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void getDissentingNeighbors(SparseSet<unsigned> &List,
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const Node nodes[]) const {
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for (const auto &Elt : Links) {
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unsigned n = Elt.second;
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// Neighbors that already have the same value are not going to
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// change because of this node changing.
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if (Value != nodes[n].Value)
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List.insert(n);
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}
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}
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};
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bool SpillPlacement::runOnMachineFunction(MachineFunction &mf) {
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MF = &mf;
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bundles = &getAnalysis<EdgeBundles>();
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loops = &getAnalysis<MachineLoopInfo>();
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assert(!nodes && "Leaking node array");
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nodes = new Node[bundles->getNumBundles()];
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TodoList.clear();
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TodoList.setUniverse(bundles->getNumBundles());
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// Compute total ingoing and outgoing block frequencies for all bundles.
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BlockFrequencies.resize(mf.getNumBlockIDs());
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MBFI = &getAnalysis<MachineBlockFrequencyInfo>();
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setThreshold(MBFI->getEntryFreq());
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for (auto &I : mf) {
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unsigned Num = I.getNumber();
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BlockFrequencies[Num] = MBFI->getBlockFreq(&I);
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}
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// We never change the function.
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return false;
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}
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void SpillPlacement::releaseMemory() {
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delete[] nodes;
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nodes = nullptr;
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TodoList.clear();
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}
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/// activate - mark node n as active if it wasn't already.
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void SpillPlacement::activate(unsigned n) {
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TodoList.insert(n);
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if (ActiveNodes->test(n))
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return;
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ActiveNodes->set(n);
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nodes[n].clear(Threshold);
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// Very large bundles usually come from big switches, indirect branches,
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// landing pads, or loops with many 'continue' statements. It is difficult to
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// allocate registers when so many different blocks are involved.
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//
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// Give a small negative bias to large bundles such that a substantial
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// fraction of the connected blocks need to be interested before we consider
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// expanding the region through the bundle. This helps compile time by
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// limiting the number of blocks visited and the number of links in the
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// Hopfield network.
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if (bundles->getBlocks(n).size() > 100) {
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nodes[n].BiasP = 0;
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nodes[n].BiasN = (MBFI->getEntryFreq() / 16);
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}
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}
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/// Set the threshold for a given entry frequency.
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///
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/// Set the threshold relative to \c Entry. Since the threshold is used as a
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/// bound on the open interval (-Threshold;Threshold), 1 is the minimum
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/// threshold.
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void SpillPlacement::setThreshold(const BlockFrequency &Entry) {
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// Apparently 2 is a good threshold when Entry==2^14, but we need to scale
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// it. Divide by 2^13, rounding as appropriate.
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uint64_t Freq = Entry.getFrequency();
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uint64_t Scaled = (Freq >> 13) + bool(Freq & (1 << 12));
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Threshold = std::max(UINT64_C(1), Scaled);
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}
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/// addConstraints - Compute node biases and weights from a set of constraints.
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/// Set a bit in NodeMask for each active node.
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void SpillPlacement::addConstraints(ArrayRef<BlockConstraint> LiveBlocks) {
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for (ArrayRef<BlockConstraint>::iterator I = LiveBlocks.begin(),
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E = LiveBlocks.end(); I != E; ++I) {
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BlockFrequency Freq = BlockFrequencies[I->Number];
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// Live-in to block?
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if (I->Entry != DontCare) {
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unsigned ib = bundles->getBundle(I->Number, false);
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activate(ib);
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nodes[ib].addBias(Freq, I->Entry);
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}
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// Live-out from block?
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if (I->Exit != DontCare) {
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unsigned ob = bundles->getBundle(I->Number, true);
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activate(ob);
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nodes[ob].addBias(Freq, I->Exit);
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}
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}
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}
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/// addPrefSpill - Same as addConstraints(PrefSpill)
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void SpillPlacement::addPrefSpill(ArrayRef<unsigned> Blocks, bool Strong) {
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for (ArrayRef<unsigned>::iterator I = Blocks.begin(), E = Blocks.end();
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I != E; ++I) {
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BlockFrequency Freq = BlockFrequencies[*I];
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if (Strong)
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Freq += Freq;
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unsigned ib = bundles->getBundle(*I, false);
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unsigned ob = bundles->getBundle(*I, true);
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activate(ib);
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activate(ob);
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nodes[ib].addBias(Freq, PrefSpill);
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nodes[ob].addBias(Freq, PrefSpill);
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}
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}
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void SpillPlacement::addLinks(ArrayRef<unsigned> Links) {
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for (ArrayRef<unsigned>::iterator I = Links.begin(), E = Links.end(); I != E;
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++I) {
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unsigned Number = *I;
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unsigned ib = bundles->getBundle(Number, false);
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unsigned ob = bundles->getBundle(Number, true);
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// Ignore self-loops.
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if (ib == ob)
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continue;
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activate(ib);
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activate(ob);
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BlockFrequency Freq = BlockFrequencies[Number];
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nodes[ib].addLink(ob, Freq);
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nodes[ob].addLink(ib, Freq);
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}
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}
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bool SpillPlacement::scanActiveBundles() {
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RecentPositive.clear();
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for (unsigned n : ActiveNodes->set_bits()) {
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update(n);
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// A node that must spill, or a node without any links is not going to
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// change its value ever again, so exclude it from iterations.
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if (nodes[n].mustSpill())
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continue;
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if (nodes[n].preferReg())
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RecentPositive.push_back(n);
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}
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return !RecentPositive.empty();
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}
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bool SpillPlacement::update(unsigned n) {
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if (!nodes[n].update(nodes, Threshold))
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return false;
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nodes[n].getDissentingNeighbors(TodoList, nodes);
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return true;
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}
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/// iterate - Repeatedly update the Hopfield nodes until stability or the
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/// maximum number of iterations is reached.
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void SpillPlacement::iterate() {
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// We do not need to push those node in the todolist.
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// They are already been proceeded as part of the previous iteration.
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RecentPositive.clear();
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// Since the last iteration, the todolist have been augmented by calls
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// to addConstraints, addLinks, and co.
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// Update the network energy starting at this new frontier.
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// The call to ::update will add the nodes that changed into the todolist.
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unsigned Limit = bundles->getNumBundles() * 10;
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while(Limit-- > 0 && !TodoList.empty()) {
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unsigned n = TodoList.pop_back_val();
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if (!update(n))
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continue;
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if (nodes[n].preferReg())
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RecentPositive.push_back(n);
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}
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}
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void SpillPlacement::prepare(BitVector &RegBundles) {
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RecentPositive.clear();
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TodoList.clear();
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// Reuse RegBundles as our ActiveNodes vector.
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ActiveNodes = &RegBundles;
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ActiveNodes->clear();
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ActiveNodes->resize(bundles->getNumBundles());
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}
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bool
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SpillPlacement::finish() {
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assert(ActiveNodes && "Call prepare() first");
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// Write preferences back to ActiveNodes.
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bool Perfect = true;
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for (unsigned n : ActiveNodes->set_bits())
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if (!nodes[n].preferReg()) {
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ActiveNodes->reset(n);
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Perfect = false;
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}
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ActiveNodes = nullptr;
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return Perfect;
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}
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