1 //=-- ProfilesummaryBuilder.cpp - Profile summary computation ---------------=//
2 //
3 // Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
4 // See https://llvm.org/LICENSE.txt for license information.
5 // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
6 //
7 //===----------------------------------------------------------------------===//
8 //
9 // This file contains support for computing profile summary data.
10 //
11 //===----------------------------------------------------------------------===//
12 
13 #include "llvm/IR/ProfileSummary.h"
14 #include "llvm/ProfileData/InstrProf.h"
15 #include "llvm/ProfileData/ProfileCommon.h"
16 #include "llvm/ProfileData/SampleProf.h"
17 #include "llvm/Support/CommandLine.h"
18 
19 using namespace llvm;
20 
21 namespace llvm {
22 cl::opt<bool> UseContextLessSummary(
23     "profile-summary-contextless", cl::Hidden,
24     cl::desc("Merge context profiles before calculating thresholds."));
25 
26 // The following two parameters determine the threshold for a count to be
27 // considered hot/cold. These two parameters are percentile values (multiplied
28 // by 10000). If the counts are sorted in descending order, the minimum count to
29 // reach ProfileSummaryCutoffHot gives the threshold to determine a hot count.
30 // Similarly, the minimum count to reach ProfileSummaryCutoffCold gives the
31 // threshold for determining cold count (everything <= this threshold is
32 // considered cold).
33 cl::opt<int> ProfileSummaryCutoffHot(
34     "profile-summary-cutoff-hot", cl::Hidden, cl::init(990000),
35     cl::desc("A count is hot if it exceeds the minimum count to"
36              " reach this percentile of total counts."));
37 
38 cl::opt<int> ProfileSummaryCutoffCold(
39     "profile-summary-cutoff-cold", cl::Hidden, cl::init(999999),
40     cl::desc("A count is cold if it is below the minimum count"
41              " to reach this percentile of total counts."));
42 
43 cl::opt<unsigned> ProfileSummaryHugeWorkingSetSizeThreshold(
44     "profile-summary-huge-working-set-size-threshold", cl::Hidden,
45     cl::init(15000),
46     cl::desc("The code working set size is considered huge if the number of"
47              " blocks required to reach the -profile-summary-cutoff-hot"
48              " percentile exceeds this count."));
49 
50 cl::opt<unsigned> ProfileSummaryLargeWorkingSetSizeThreshold(
51     "profile-summary-large-working-set-size-threshold", cl::Hidden,
52     cl::init(12500),
53     cl::desc("The code working set size is considered large if the number of"
54              " blocks required to reach the -profile-summary-cutoff-hot"
55              " percentile exceeds this count."));
56 
57 // The next two options override the counts derived from summary computation and
58 // are useful for debugging purposes.
59 cl::opt<uint64_t> ProfileSummaryHotCount(
60     "profile-summary-hot-count", cl::ReallyHidden,
61     cl::desc("A fixed hot count that overrides the count derived from"
62              " profile-summary-cutoff-hot"));
63 
64 cl::opt<uint64_t> ProfileSummaryColdCount(
65     "profile-summary-cold-count", cl::ReallyHidden,
66     cl::desc("A fixed cold count that overrides the count derived from"
67              " profile-summary-cutoff-cold"));
68 } // namespace llvm
69 
70 // A set of cutoff values. Each value, when divided by ProfileSummary::Scale
71 // (which is 1000000) is a desired percentile of total counts.
72 static const uint32_t DefaultCutoffsData[] = {
73     10000,  /*  1% */
74     100000, /* 10% */
75     200000, 300000, 400000, 500000, 600000, 700000, 800000,
76     900000, 950000, 990000, 999000, 999900, 999990, 999999};
77 const ArrayRef<uint32_t> ProfileSummaryBuilder::DefaultCutoffs =
78     DefaultCutoffsData;
79 
80 const ProfileSummaryEntry &
81 ProfileSummaryBuilder::getEntryForPercentile(const SummaryEntryVector &DS,
82                                              uint64_t Percentile) {
83   auto It = partition_point(DS, [=](const ProfileSummaryEntry &Entry) {
84     return Entry.Cutoff < Percentile;
85   });
86   // The required percentile has to be <= one of the percentiles in the
87   // detailed summary.
88   if (It == DS.end())
89     report_fatal_error("Desired percentile exceeds the maximum cutoff");
90   return *It;
91 }
92 
93 void InstrProfSummaryBuilder::addRecord(const InstrProfRecord &R) {
94   // The first counter is not necessarily an entry count for IR
95   // instrumentation profiles.
96   // Eventually MaxFunctionCount will become obsolete and this can be
97   // removed.
98 
99   if (R.getCountPseudoKind() != InstrProfRecord::NotPseudo)
100     return;
101 
102   addEntryCount(R.Counts[0]);
103   for (size_t I = 1, E = R.Counts.size(); I < E; ++I)
104     addInternalCount(R.Counts[I]);
105 }
106 
107 // To compute the detailed summary, we consider each line containing samples as
108 // equivalent to a block with a count in the instrumented profile.
109 void SampleProfileSummaryBuilder::addRecord(
110     const sampleprof::FunctionSamples &FS, bool isCallsiteSample) {
111   if (!isCallsiteSample) {
112     NumFunctions++;
113     if (FS.getHeadSamples() > MaxFunctionCount)
114       MaxFunctionCount = FS.getHeadSamples();
115   } else if (FS.getContext().hasAttribute(
116                  sampleprof::ContextDuplicatedIntoBase)) {
117     // Do not recount callee samples if they are already merged into their base
118     // profiles. This can happen to CS nested profile.
119     return;
120   }
121 
122   for (const auto &I : FS.getBodySamples()) {
123     uint64_t Count = I.second.getSamples();
124       addCount(Count);
125   }
126   for (const auto &I : FS.getCallsiteSamples())
127     for (const auto &CS : I.second)
128       addRecord(CS.second, true);
129 }
130 
131 // The argument to this method is a vector of cutoff percentages and the return
132 // value is a vector of (Cutoff, MinCount, NumCounts) triplets.
133 void ProfileSummaryBuilder::computeDetailedSummary() {
134   if (DetailedSummaryCutoffs.empty())
135     return;
136   llvm::sort(DetailedSummaryCutoffs);
137   auto Iter = CountFrequencies.begin();
138   const auto End = CountFrequencies.end();
139 
140   uint32_t CountsSeen = 0;
141   uint64_t CurrSum = 0, Count = 0;
142 
143   for (const uint32_t Cutoff : DetailedSummaryCutoffs) {
144     assert(Cutoff <= 999999);
145     APInt Temp(128, TotalCount);
146     APInt N(128, Cutoff);
147     APInt D(128, ProfileSummary::Scale);
148     Temp *= N;
149     Temp = Temp.sdiv(D);
150     uint64_t DesiredCount = Temp.getZExtValue();
151     assert(DesiredCount <= TotalCount);
152     while (CurrSum < DesiredCount && Iter != End) {
153       Count = Iter->first;
154       uint32_t Freq = Iter->second;
155       CurrSum += (Count * Freq);
156       CountsSeen += Freq;
157       Iter++;
158     }
159     assert(CurrSum >= DesiredCount);
160     ProfileSummaryEntry PSE = {Cutoff, Count, CountsSeen};
161     DetailedSummary.push_back(PSE);
162   }
163 }
164 
165 uint64_t
166 ProfileSummaryBuilder::getHotCountThreshold(const SummaryEntryVector &DS) {
167   auto &HotEntry =
168       ProfileSummaryBuilder::getEntryForPercentile(DS, ProfileSummaryCutoffHot);
169   uint64_t HotCountThreshold = HotEntry.MinCount;
170   if (ProfileSummaryHotCount.getNumOccurrences() > 0)
171     HotCountThreshold = ProfileSummaryHotCount;
172   return HotCountThreshold;
173 }
174 
175 uint64_t
176 ProfileSummaryBuilder::getColdCountThreshold(const SummaryEntryVector &DS) {
177   auto &ColdEntry = ProfileSummaryBuilder::getEntryForPercentile(
178       DS, ProfileSummaryCutoffCold);
179   uint64_t ColdCountThreshold = ColdEntry.MinCount;
180   if (ProfileSummaryColdCount.getNumOccurrences() > 0)
181     ColdCountThreshold = ProfileSummaryColdCount;
182   return ColdCountThreshold;
183 }
184 
185 std::unique_ptr<ProfileSummary> SampleProfileSummaryBuilder::getSummary() {
186   computeDetailedSummary();
187   return std::make_unique<ProfileSummary>(
188       ProfileSummary::PSK_Sample, DetailedSummary, TotalCount, MaxCount, 0,
189       MaxFunctionCount, NumCounts, NumFunctions);
190 }
191 
192 std::unique_ptr<ProfileSummary>
193 SampleProfileSummaryBuilder::computeSummaryForProfiles(
194     const SampleProfileMap &Profiles) {
195   assert(NumFunctions == 0 &&
196          "This can only be called on an empty summary builder");
197   sampleprof::SampleProfileMap ContextLessProfiles;
198   const sampleprof::SampleProfileMap *ProfilesToUse = &Profiles;
199   // For CSSPGO, context-sensitive profile effectively split a function profile
200   // into many copies each representing the CFG profile of a particular calling
201   // context. That makes the count distribution looks more flat as we now have
202   // more function profiles each with lower counts, which in turn leads to lower
203   // hot thresholds. To compensate for that, by default we merge context
204   // profiles before computing profile summary.
205   if (UseContextLessSummary || (sampleprof::FunctionSamples::ProfileIsCS &&
206                                 !UseContextLessSummary.getNumOccurrences())) {
207     ProfileConverter::flattenProfile(Profiles, ContextLessProfiles, true);
208     ProfilesToUse = &ContextLessProfiles;
209   }
210 
211   for (const auto &I : *ProfilesToUse) {
212     const sampleprof::FunctionSamples &Profile = I.second;
213     addRecord(Profile);
214   }
215 
216   return getSummary();
217 }
218 
219 std::unique_ptr<ProfileSummary> InstrProfSummaryBuilder::getSummary() {
220   computeDetailedSummary();
221   return std::make_unique<ProfileSummary>(
222       ProfileSummary::PSK_Instr, DetailedSummary, TotalCount, MaxCount,
223       MaxInternalBlockCount, MaxFunctionCount, NumCounts, NumFunctions);
224 }
225 
226 void InstrProfSummaryBuilder::addEntryCount(uint64_t Count) {
227   assert(Count <= getInstrMaxCountValue() &&
228          "Count value should be less than the max count value.");
229   NumFunctions++;
230   addCount(Count);
231   if (Count > MaxFunctionCount)
232     MaxFunctionCount = Count;
233 }
234 
235 void InstrProfSummaryBuilder::addInternalCount(uint64_t Count) {
236   assert(Count <= getInstrMaxCountValue() &&
237          "Count value should be less than the max count value.");
238   addCount(Count);
239   if (Count > MaxInternalBlockCount)
240     MaxInternalBlockCount = Count;
241 }
242