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git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@124798 91177308-0d34-0410-b5e6-96231b3b80d8
356 lines
13 KiB
C++
356 lines
13 KiB
C++
//===-- SpillPlacement.cpp - Optimal Spill Code Placement -----------------===//
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//
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// The LLVM Compiler Infrastructure
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//
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// This file is distributed under the University of Illinois Open Source
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// License. See LICENSE.TXT for details.
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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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#define DEBUG_TYPE "spillplacement"
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#include "SpillPlacement.h"
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#include "llvm/CodeGen/EdgeBundles.h"
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#include "llvm/CodeGen/LiveIntervalAnalysis.h"
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#include "llvm/CodeGen/MachineBasicBlock.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/Support/Debug.h"
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#include "llvm/Support/Format.h"
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using namespace llvm;
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char SpillPlacement::ID = 0;
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INITIALIZE_PASS_BEGIN(SpillPlacement, "spill-code-placement",
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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, "spill-code-placement",
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"Spill Code Placement Analysis", true, true)
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char &llvm::SpillPlacementID = SpillPlacement::ID;
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void SpillPlacement::getAnalysisUsage(AnalysisUsage &AU) const {
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AU.setPreservesAll();
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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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///
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struct SpillPlacement::Node {
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/// Frequency - Total block frequency feeding into[0] or out of[1] the bundle.
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/// Ideally, these two numbers should be identical, but inaccuracies in the
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/// block frequency estimates means that we need to normalize ingoing and
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/// outgoing frequencies separately so they are commensurate.
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float Frequency[2];
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/// Bias - Normalized contributions from non-transparent blocks.
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/// A bundle connected to a MustSpill block has a huge negative bias,
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/// otherwise it is a number in the range [-2;2].
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float Bias;
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/// Value - Output value of this node computed from the Bias and links.
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/// This is always in the range [-1;1]. A positive number means the variable
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/// should go in a register through this bundle.
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float Value;
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typedef SmallVector<std::pair<float, unsigned>, 4> LinkVector;
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/// Links - (Weight, BundleNo) for all transparent blocks connecting to other
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/// bundles. The weights are all positive and add up to at most 2, weights
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/// from ingoing and outgoing nodes separately add up to a most 1. The weight
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/// sum can be less than 2 when the variable is not live into / out of some
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/// connected basic blocks.
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LinkVector Links;
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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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// Actually, we must spill if Bias < sum(weights).
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// It may be worth it to compute the weight sum here?
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return Bias < -2.0f;
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}
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/// Node - Create a blank Node.
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Node() {
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Frequency[0] = Frequency[1] = 0;
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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() {
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Bias = Value = 0;
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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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/// out=0 for an ingoing link, and 1 for an outgoing link.
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void addLink(unsigned b, float w, bool out) {
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// Normalize w relative to all connected blocks from that direction.
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w /= Frequency[out];
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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 from an ingoing[0] or outgoing[1] link.
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void addBias(float w, bool out) {
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// Normalize w relative to all connected blocks from that direction.
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w /= Frequency[out];
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Bias += w;
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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[]) {
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// Compute the weighted sum of inputs.
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float Sum = Bias;
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for (LinkVector::iterator I = Links.begin(), E = Links.end(); I != E; ++I)
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Sum += I->first * nodes[I->second].Value;
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// The weighted sum is going to be in the range [-2;2]. Ideally, we should
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// simply set Value = sign(Sum), but we will add a dead zone around 0 for
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// two reasons:
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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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const float Thres = 1e-4f;
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bool Before = preferReg();
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if (Sum < -Thres)
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Value = -1;
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else if (Sum > Thres)
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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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};
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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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// Compute total ingoing and outgoing block frequencies for all bundles.
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for (MachineFunction::iterator I = mf.begin(), E = mf.end(); I != E; ++I) {
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float Freq = getBlockFrequency(I);
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unsigned Num = I->getNumber();
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nodes[bundles->getBundle(Num, 1)].Frequency[0] += Freq;
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nodes[bundles->getBundle(Num, 0)].Frequency[1] += Freq;
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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 = 0;
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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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if (ActiveNodes->test(n))
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return;
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ActiveNodes->set(n);
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nodes[n].clear();
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}
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/// prepareNodes - 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::
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prepareNodes(const SmallVectorImpl<BlockConstraint> &LiveBlocks) {
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DEBUG(dbgs() << "Building Hopfield network from " << LiveBlocks.size()
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<< " constraint blocks:\n");
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for (SmallVectorImpl<BlockConstraint>::const_iterator I = LiveBlocks.begin(),
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E = LiveBlocks.end(); I != E; ++I) {
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MachineBasicBlock *MBB = MF->getBlockNumbered(I->Number);
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float Freq = getBlockFrequency(MBB);
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DEBUG(dbgs() << " BB#" << I->Number << format(", Freq = %.1f", Freq));
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// Is this a transparent block? Link ingoing and outgoing bundles.
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if (I->Entry == DontCare && I->Exit == DontCare) {
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unsigned ib = bundles->getBundle(I->Number, 0);
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unsigned ob = bundles->getBundle(I->Number, 1);
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DEBUG(dbgs() << ", transparent EB#" << ib << " -> EB#" << ob << '\n');
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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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nodes[ib].addLink(ob, Freq, 1);
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nodes[ob].addLink(ib, Freq, 0);
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continue;
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}
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// This block is not transparent, but it can still add bias.
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const float Bias[] = {
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0, // DontCare,
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1, // PrefReg,
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-1, // PrefSpill
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-HUGE_VALF // MustSpill
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};
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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, 0);
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activate(ib);
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nodes[ib].addBias(Freq * Bias[I->Entry], 1);
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DEBUG(dbgs() << format(", entry EB#%u %+.1f", ib, Freq * Bias[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, 1);
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activate(ob);
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nodes[ob].addBias(Freq * Bias[I->Exit], 0);
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DEBUG(dbgs() << format(", exit EB#%u %+.1f", ob, Freq * Bias[I->Exit]));
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}
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DEBUG(dbgs() << '\n');
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}
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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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/// @param Linked - Numbers of linked nodes that need updating.
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void SpillPlacement::iterate(const SmallVectorImpl<unsigned> &Linked) {
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DEBUG(dbgs() << "Iterating over " << Linked.size() << " linked nodes:\n");
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if (Linked.empty())
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return;
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// Run up to 10 iterations. The edge bundle numbering is closely related to
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// basic block numbering, so there is a strong tendency towards chains of
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// linked nodes with sequential numbers. By scanning the linked nodes
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// backwards and forwards, we make it very likely that a single node can
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// affect the entire network in a single iteration. That means very fast
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// convergence, usually in a single iteration.
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for (unsigned iteration = 0; iteration != 10; ++iteration) {
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// Scan backwards, skipping the last node which was just updated.
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bool Changed = false;
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for (SmallVectorImpl<unsigned>::const_reverse_iterator I =
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llvm::next(Linked.rbegin()), E = Linked.rend(); I != E; ++I) {
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unsigned n = *I;
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bool C = nodes[n].update(nodes);
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Changed |= C;
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DEBUG(dbgs() << " \\EB#" << n << format(" = %+2.0f", nodes[n].Value)
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<< (C ? " *\n" : "\n"));
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}
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if (!Changed)
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return;
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// Scan forwards, skipping the first node which was just updated.
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Changed = false;
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for (SmallVectorImpl<unsigned>::const_iterator I =
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llvm::next(Linked.begin()), E = Linked.end(); I != E; ++I) {
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unsigned n = *I;
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bool C = nodes[n].update(nodes);
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Changed |= C;
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DEBUG(dbgs() << " /EB#" << n << format(" = %+2.0f", nodes[n].Value)
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<< (C ? " *\n" : "\n"));
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}
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if (!Changed)
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return;
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}
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}
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bool
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SpillPlacement::placeSpills(const SmallVectorImpl<BlockConstraint> &LiveBlocks,
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BitVector &RegBundles) {
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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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// Compute active nodes, links and biases.
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prepareNodes(LiveBlocks);
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// Update all active nodes, and find the ones that are actually linked to
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// something so their value may change when iterating.
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DEBUG(dbgs() << "Network has " << RegBundles.count() << " active nodes:\n");
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SmallVector<unsigned, 8> Linked;
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for (int n = RegBundles.find_first(); n>=0; n = RegBundles.find_next(n)) {
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nodes[n].update(nodes);
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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].Links.empty() && !nodes[n].mustSpill())
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Linked.push_back(n);
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DEBUG({
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dbgs() << " EB#" << n << format(" = %+2.0f", nodes[n].Value)
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<< format(", Bias %+.2f", nodes[n].Bias)
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<< format(", Freq %.1f/%.1f", nodes[n].Frequency[0],
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nodes[n].Frequency[1]);
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for (unsigned i = 0, e = nodes[n].Links.size(); i != e; ++i)
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dbgs() << format(", %.2f -> EB#%u", nodes[n].Links[i].first,
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nodes[n].Links[i].second);
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dbgs() << '\n';
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});
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}
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// Iterate the network to convergence.
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iterate(Linked);
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// Write preferences back to RegBundles.
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bool Perfect = true;
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for (int n = RegBundles.find_first(); n>=0; n = RegBundles.find_next(n))
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if (!nodes[n].preferReg()) {
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RegBundles.reset(n);
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Perfect = false;
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}
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return Perfect;
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}
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/// getBlockFrequency - Return our best estimate of the block frequency which is
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/// the expected number of block executions per function invocation.
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float SpillPlacement::getBlockFrequency(const MachineBasicBlock *MBB) {
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// Use the unnormalized spill weight for real block frequencies.
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return LiveIntervals::getSpillWeight(true, false, loops->getLoopDepth(MBB));
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}
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