1//===- MachineBranchProbabilityInfo.cpp - Machine Branch Probability Info -===//
2//
3//                     The LLVM Compiler Infrastructure
4//
5// This file is distributed under the University of Illinois Open Source
6// License. See LICENSE.TXT for details.
7//
8//===----------------------------------------------------------------------===//
9//
10// This analysis uses probability info stored in Machine Basic Blocks.
11//
12//===----------------------------------------------------------------------===//
13
14#include "llvm/Instructions.h"
15#include "llvm/CodeGen/MachineBranchProbabilityInfo.h"
16#include "llvm/CodeGen/MachineBasicBlock.h"
17#include "llvm/Support/Debug.h"
18#include "llvm/Support/raw_ostream.h"
19
20using namespace llvm;
21
22INITIALIZE_PASS_BEGIN(MachineBranchProbabilityInfo, "machine-branch-prob",
23                      "Machine Branch Probability Analysis", false, true)
24INITIALIZE_PASS_END(MachineBranchProbabilityInfo, "machine-branch-prob",
25                    "Machine Branch Probability Analysis", false, true)
26
27char MachineBranchProbabilityInfo::ID = 0;
28
29void MachineBranchProbabilityInfo::anchor() { }
30
31uint32_t MachineBranchProbabilityInfo::
32getSumForBlock(const MachineBasicBlock *MBB, uint32_t &Scale) const {
33  // First we compute the sum with 64-bits of precision, ensuring that cannot
34  // overflow by bounding the number of weights considered. Hopefully no one
35  // actually needs 2^32 successors.
36  assert(MBB->succ_size() < UINT32_MAX);
37  uint64_t Sum = 0;
38  Scale = 1;
39  for (MachineBasicBlock::const_succ_iterator I = MBB->succ_begin(),
40       E = MBB->succ_end(); I != E; ++I) {
41    uint32_t Weight = getEdgeWeight(MBB, I);
42    Sum += Weight;
43  }
44
45  // If the computed sum fits in 32-bits, we're done.
46  if (Sum <= UINT32_MAX)
47    return Sum;
48
49  // Otherwise, compute the scale necessary to cause the weights to fit, and
50  // re-sum with that scale applied.
51  assert((Sum / UINT32_MAX) < UINT32_MAX);
52  Scale = (Sum / UINT32_MAX) + 1;
53  Sum = 0;
54  for (MachineBasicBlock::const_succ_iterator I = MBB->succ_begin(),
55       E = MBB->succ_end(); I != E; ++I) {
56    uint32_t Weight = getEdgeWeight(MBB, I);
57    Sum += Weight / Scale;
58  }
59  assert(Sum <= UINT32_MAX);
60  return Sum;
61}
62
63uint32_t MachineBranchProbabilityInfo::
64getEdgeWeight(const MachineBasicBlock *Src,
65              MachineBasicBlock::const_succ_iterator Dst) const {
66  uint32_t Weight = Src->getSuccWeight(Dst);
67  if (!Weight)
68    return DEFAULT_WEIGHT;
69  return Weight;
70}
71
72uint32_t MachineBranchProbabilityInfo::
73getEdgeWeight(const MachineBasicBlock *Src,
74              const MachineBasicBlock *Dst) const {
75  // This is a linear search. Try to use the const_succ_iterator version when
76  // possible.
77  return getEdgeWeight(Src, std::find(Src->succ_begin(), Src->succ_end(), Dst));
78}
79
80bool MachineBranchProbabilityInfo::isEdgeHot(MachineBasicBlock *Src,
81                                             MachineBasicBlock *Dst) const {
82  // Hot probability is at least 4/5 = 80%
83  // FIXME: Compare against a static "hot" BranchProbability.
84  return getEdgeProbability(Src, Dst) > BranchProbability(4, 5);
85}
86
87MachineBasicBlock *
88MachineBranchProbabilityInfo::getHotSucc(MachineBasicBlock *MBB) const {
89  uint32_t MaxWeight = 0;
90  MachineBasicBlock *MaxSucc = 0;
91  for (MachineBasicBlock::const_succ_iterator I = MBB->succ_begin(),
92       E = MBB->succ_end(); I != E; ++I) {
93    uint32_t Weight = getEdgeWeight(MBB, I);
94    if (Weight > MaxWeight) {
95      MaxWeight = Weight;
96      MaxSucc = *I;
97    }
98  }
99
100  if (getEdgeProbability(MBB, MaxSucc) >= BranchProbability(4, 5))
101    return MaxSucc;
102
103  return 0;
104}
105
106BranchProbability
107MachineBranchProbabilityInfo::getEdgeProbability(MachineBasicBlock *Src,
108                                                 MachineBasicBlock *Dst) const {
109  uint32_t Scale = 1;
110  uint32_t D = getSumForBlock(Src, Scale);
111  uint32_t N = getEdgeWeight(Src, Dst) / Scale;
112
113  return BranchProbability(N, D);
114}
115
116raw_ostream &MachineBranchProbabilityInfo::
117printEdgeProbability(raw_ostream &OS, MachineBasicBlock *Src,
118                     MachineBasicBlock *Dst) const {
119
120  const BranchProbability Prob = getEdgeProbability(Src, Dst);
121  OS << "edge MBB#" << Src->getNumber() << " -> MBB#" << Dst->getNumber()
122     << " probability is "  << Prob
123     << (isEdgeHot(Src, Dst) ? " [HOT edge]\n" : "\n");
124
125  return OS;
126}
127