Merge branch 'ismaelJimenez-complexity'

This commit is contained in:
Dominic Hamon 2016-05-24 13:15:55 -07:00
commit a86545874a
16 changed files with 573 additions and 22 deletions

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@ -16,6 +16,7 @@ Eugene Zhuk <eugene.zhuk@gmail.com>
Evgeny Safronov <division494@gmail.com>
Felix Homann <linuxaudio@showlabor.de>
Google Inc.
Ismael Jimenez Martinez <ismael.jimenez.martinez@gmail.com>
JianXiong Zhou <zhoujianxiong2@gmail.com>
Jussi Knuuttila <jussi.knuuttila@gmail.com>
Kaito Udagawa <umireon@gmail.com>

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@ -32,6 +32,7 @@ Eric Fiselier <eric@efcs.ca>
Eugene Zhuk <eugene.zhuk@gmail.com>
Evgeny Safronov <division494@gmail.com>
Felix Homann <linuxaudio@showlabor.de>
Ismael Jimenez Martinez <ismael.jimenez.martinez@gmail.com>
JianXiong Zhou <zhoujianxiong2@gmail.com>
Jussi Knuuttila <jussi.knuuttila@gmail.com>
Kaito Udagawa <umireon@gmail.com>

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@ -61,6 +61,13 @@ the specified range and will generate a benchmark for each such argument.
BENCHMARK(BM_memcpy)->Range(8, 8<<10);
```
By default the arguments in the range are generated in multiples of eight and the command above selects [ 8, 64, 512, 4k, 8k ]. In the following code the range multiplier is changed to multiples of two.
```c++
BENCHMARK(BM_memcpy)->RangeMultiplier(2)->Range(8, 8<<10);
```
Now arguments generated are [ 8, 16, 32, 64, 128, 256, 512, 1024, 2k, 4k, 8k ].
You might have a benchmark that depends on two inputs. For example, the
following code defines a family of benchmarks for measuring the speed of set
insertion.
@ -109,6 +116,27 @@ static void CustomArguments(benchmark::internal::Benchmark* b) {
BENCHMARK(BM_SetInsert)->Apply(CustomArguments);
```
### Calculate asymptotic complexity (Big O)
Asymptotic complexity might be calculated for a family of benchmarks. The following code will calculate the coefficient for the high-order term in the running time and the normalized root-mean square error of string comparison.
```c++
static void BM_StringCompare(benchmark::State& state) {
std::string s1(state.range_x(), '-');
std::string s2(state.range_x(), '-');
while (state.KeepRunning())
benchmark::DoNotOptimize(s1.compare(s2));
}
BENCHMARK(BM_StringCompare)
->RangeMultiplier(2)->Range(1<<10, 1<<18)->Complexity(benchmark::oN);
```
As shown in the following invocation, asymptotic complexity might also be calculated automatically.
```c++
BENCHMARK(BM_StringCompare)
->RangeMultiplier(2)->Range(1<<10, 1<<18)->Complexity(benchmark::oAuto);
```
### Templated benchmarks
Templated benchmarks work the same way: This example produces and consumes
messages of size `sizeof(v)` `range_x` times. It also outputs throughput in the

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@ -154,6 +154,7 @@ BENCHMARK(BM_test)->Unit(benchmark::kMillisecond);
#include <stdint.h>
#include "macros.h"
#include "complexity.h"
namespace benchmark {
class BenchmarkReporter;
@ -321,6 +322,19 @@ public:
return bytes_processed_;
}
// If this routine is called with complexity_n > 0 and complexity report is requested for the
// family benchmark, then current benchmark will be part of the computation and complexity_n will
// represent the length of N.
BENCHMARK_ALWAYS_INLINE
void SetComplexityN(size_t complexity_n) {
complexity_n_ = complexity_n;
}
BENCHMARK_ALWAYS_INLINE
size_t complexity_length_n() {
return complexity_n_;
}
// If this routine is called with items > 0, then an items/s
// label is printed on the benchmark report line for the currently
// executing benchmark. It is typically called at the end of a processing
@ -393,6 +407,8 @@ private:
size_t bytes_processed_;
size_t items_processed_;
size_t complexity_n_;
public:
// Index of the executing thread. Values from [0, threads).
const int thread_index;
@ -477,6 +493,10 @@ public:
// or MB/second values.
Benchmark* UseManualTime();
// Set the asymptotic computational complexity for the benchmark. If called
// the asymptotic computational complexity will be shown on the output.
Benchmark* Complexity(BigO complexity);
// Support for running multiple copies of the same benchmark concurrently
// in multiple threads. This may be useful when measuring the scaling
// of some piece of code.

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@ -0,0 +1,42 @@
#ifndef COMPLEXITY_H_
#define COMPLEXITY_H_
#include <string>
namespace benchmark {
// BigO is passed to a benchmark in order to specify the asymptotic computational
// complexity for the benchmark. In case oAuto is selected, complexity will be
// calculated automatically to the best fit.
enum BigO {
oNone,
o1,
oN,
oNSquared,
oNCubed,
oLogN,
oNLogN,
oAuto
};
inline std::string GetBigO(BigO complexity) {
switch (complexity) {
case oN:
return "* N";
case oNSquared:
return "* N**2";
case oNCubed:
return "* N**3";
case oLogN:
return "* lgN";
case oNLogN:
return "* NlgN";
case o1:
return "* 1";
default:
return "";
}
}
} // end namespace benchmark
#endif // COMPLEXITY_H_

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@ -48,7 +48,11 @@ class BenchmarkReporter {
cpu_accumulated_time(0),
bytes_per_second(0),
items_per_second(0),
max_heapbytes_used(0) {}
max_heapbytes_used(0),
complexity(oNone),
complexity_n(0),
report_big_o(false),
report_rms(false) {}
std::string benchmark_name;
std::string report_label; // Empty if not set by benchmark.
@ -63,6 +67,14 @@ class BenchmarkReporter {
// This is set to 0.0 if memory tracing is not enabled.
double max_heapbytes_used;
// Keep track of arguments to compute asymptotic complexity
BigO complexity;
int complexity_n;
// Inform print function whether the current run is a complexity report
bool report_big_o;
bool report_rms;
};
// Called once for every suite of benchmarks run.
@ -78,6 +90,12 @@ class BenchmarkReporter {
// Note that all the grouped benchmark runs should refer to the same
// benchmark, thus have the same name.
virtual void ReportRuns(const std::vector<Run>& report) = 0;
// Called once at the last benchmark in a family of benchmarks, gives information
// about asymptotic complexity and RMS.
// Note that all the benchmark runs in a range should refer to the same benchmark,
// thus have the same name.
virtual void ReportComplexity(const std::vector<Run>& complexity_reports) = 0;
// Called once and only once after ever group of benchmarks is run and
// reported.
@ -85,7 +103,8 @@ class BenchmarkReporter {
virtual ~BenchmarkReporter();
protected:
static void ComputeStats(std::vector<Run> const& reports, Run* mean, Run* stddev);
static void ComputeStats(const std::vector<Run> & reports, Run* mean, Run* stddev);
static void ComputeBigO(const std::vector<Run> & reports, Run* bigO, Run* rms);
static TimeUnitMultiplier GetTimeUnitAndMultiplier(TimeUnit unit);
};
@ -95,6 +114,7 @@ class ConsoleReporter : public BenchmarkReporter {
public:
virtual bool ReportContext(const Context& context);
virtual void ReportRuns(const std::vector<Run>& reports);
virtual void ReportComplexity(const std::vector<Run>& complexity_reports);
protected:
virtual void PrintRunData(const Run& report);
@ -107,6 +127,7 @@ public:
JSONReporter() : first_report_(true) {}
virtual bool ReportContext(const Context& context);
virtual void ReportRuns(const std::vector<Run>& reports);
virtual void ReportComplexity(const std::vector<Run>& complexity_reports);
virtual void Finalize();
private:
@ -119,6 +140,7 @@ class CSVReporter : public BenchmarkReporter {
public:
virtual bool ReportContext(const Context& context);
virtual void ReportRuns(const std::vector<Run>& reports);
virtual void ReportComplexity(const std::vector<Run>& complexity_reports);
private:
void PrintRunData(const Run& report);

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@ -5,7 +5,7 @@ include_directories(${PROJECT_SOURCE_DIR}/src)
set(SOURCE_FILES "benchmark.cc" "colorprint.cc" "commandlineflags.cc"
"console_reporter.cc" "csv_reporter.cc" "json_reporter.cc"
"log.cc" "reporter.cc" "sleep.cc" "string_util.cc"
"sysinfo.cc" "walltime.cc")
"sysinfo.cc" "walltime.cc" "minimal_leastsq.cc")
# Determine the correct regular expression engine to use
if(HAVE_STD_REGEX)
set(RE_FILES "re_std.cc")

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@ -116,9 +116,10 @@ std::string* GetReportLabel() {
//static benchmark::MallocCounter *benchmark_mc;
struct ThreadStats {
ThreadStats() : bytes_processed(0), items_processed(0) {}
ThreadStats() : bytes_processed(0), items_processed(0), complexity_n(0) {}
int64_t bytes_processed;
int64_t items_processed;
int complexity_n;
};
// Timer management class
@ -290,6 +291,8 @@ struct Benchmark::Instance {
int range_multiplier;
bool use_real_time;
bool use_manual_time;
BigO complexity;
bool last_benchmark_instance;
double min_time;
int threads; // Number of concurrent threads to use
bool multithreaded; // Is benchmark multi-threaded?
@ -331,6 +334,7 @@ public:
void MinTime(double n);
void UseRealTime();
void UseManualTime();
void Complexity(BigO complexity);
void Threads(int t);
void ThreadRange(int min_threads, int max_threads);
void ThreadPerCpu();
@ -349,6 +353,7 @@ private:
double min_time_;
bool use_real_time_;
bool use_manual_time_;
BigO complexity_;
std::vector<int> thread_counts_;
BenchmarkImp& operator=(BenchmarkImp const&);
@ -411,6 +416,7 @@ bool BenchmarkFamilies::FindBenchmarks(
instance.min_time = family->min_time_;
instance.use_real_time = family->use_real_time_;
instance.use_manual_time = family->use_manual_time_;
instance.complexity = family->complexity_;
instance.threads = num_threads;
instance.multithreaded = !(family->thread_counts_.empty());
@ -436,6 +442,7 @@ bool BenchmarkFamilies::FindBenchmarks(
}
if (re.Match(instance.name)) {
instance.last_benchmark_instance = (args == family->args_.back());
benchmarks->push_back(instance);
}
}
@ -447,7 +454,8 @@ bool BenchmarkFamilies::FindBenchmarks(
BenchmarkImp::BenchmarkImp(const char* name)
: name_(name), arg_count_(-1), time_unit_(kNanosecond),
range_multiplier_(kRangeMultiplier), min_time_(0.0),
use_real_time_(false), use_manual_time_(false) {
use_real_time_(false), use_manual_time_(false),
complexity_(oNone) {
}
BenchmarkImp::~BenchmarkImp() {
@ -523,6 +531,10 @@ void BenchmarkImp::UseManualTime() {
use_manual_time_ = true;
}
void BenchmarkImp::Complexity(BigO complexity){
complexity_ = complexity;
}
void BenchmarkImp::Threads(int t) {
CHECK_GT(t, 0);
thread_counts_.push_back(t);
@ -636,6 +648,11 @@ Benchmark* Benchmark::UseManualTime() {
return this;
}
Benchmark* Benchmark::Complexity(BigO complexity) {
imp_->Complexity(complexity);
return this;
}
Benchmark* Benchmark::Threads(int t) {
imp_->Threads(t);
return this;
@ -677,13 +694,15 @@ void RunInThread(const benchmark::internal::Benchmark::Instance* b,
MutexLock l(GetBenchmarkLock());
total->bytes_processed += st.bytes_processed();
total->items_processed += st.items_processed();
total->complexity_n += st.complexity_length_n();
}
timer_manager->Finalize();
}
void RunBenchmark(const benchmark::internal::Benchmark::Instance& b,
BenchmarkReporter* br) EXCLUDES(GetBenchmarkLock()) {
BenchmarkReporter* br,
std::vector<BenchmarkReporter::Run>& complexity_reports) EXCLUDES(GetBenchmarkLock()) {
size_t iters = 1;
std::vector<BenchmarkReporter::Run> reports;
@ -781,7 +800,13 @@ void RunBenchmark(const benchmark::internal::Benchmark::Instance& b,
report.cpu_accumulated_time = cpu_accumulated_time;
report.bytes_per_second = bytes_per_second;
report.items_per_second = items_per_second;
report.complexity_n = total.complexity_n;
report.complexity = b.complexity;
reports.push_back(report);
if(report.complexity != oNone)
complexity_reports.push_back(report);
break;
}
@ -805,6 +830,12 @@ void RunBenchmark(const benchmark::internal::Benchmark::Instance& b,
}
}
br->ReportRuns(reports);
if((b.complexity != oNone) && b.last_benchmark_instance) {
br->ReportComplexity(complexity_reports);
complexity_reports.clear();
}
if (b.multithreaded) {
for (std::thread& thread : pool)
thread.join();
@ -819,6 +850,7 @@ State::State(size_t max_iters, bool has_x, int x, bool has_y, int y,
has_range_x_(has_x), range_x_(x),
has_range_y_(has_y), range_y_(y),
bytes_processed_(0), items_processed_(0),
complexity_n_(0),
thread_index(thread_i),
threads(n_threads),
max_iterations(max_iters)
@ -876,9 +908,12 @@ void RunMatchingBenchmarks(const std::vector<Benchmark::Instance>& benchmarks,
context.cpu_scaling_enabled = CpuScalingEnabled();
context.name_field_width = name_field_width;
// Keep track of runing times of all instances of current benchmark
std::vector<BenchmarkReporter::Run> complexity_reports;
if (reporter->ReportContext(context)) {
for (const auto& benchmark : benchmarks) {
RunBenchmark(benchmark, reporter);
RunBenchmark(benchmark, reporter, complexity_reports);
}
}
}

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@ -79,6 +79,21 @@ void ConsoleReporter::ReportRuns(const std::vector<Run>& reports) {
PrintRunData(stddev_data);
}
void ConsoleReporter::ReportComplexity(const std::vector<Run> & complexity_reports) {
if (complexity_reports.size() < 2) {
// We don't report asymptotic complexity data if there was a single run.
return;
}
Run big_o_data;
Run rms_data;
BenchmarkReporter::ComputeBigO(complexity_reports, &big_o_data, &rms_data);
// Output using PrintRun.
PrintRunData(big_o_data);
PrintRunData(rms_data);
}
void ConsoleReporter::PrintRunData(const Run& result) {
// Format bytes per second
std::string rate;
@ -97,10 +112,23 @@ void ConsoleReporter::PrintRunData(const Run& result) {
const char* timeLabel;
std::tie(timeLabel, multiplier) = GetTimeUnitAndMultiplier(result.time_unit);
ColorPrintf(COLOR_GREEN, "%-*s ",
ColorPrintf((result.report_big_o ||result.report_rms) ? COLOR_BLUE : COLOR_GREEN, "%-*s ",
name_field_width_, result.benchmark_name.c_str());
if (result.iterations == 0) {
if(result.report_big_o) {
std::string big_o = result.report_big_o ? GetBigO(result.complexity) : "";
ColorPrintf(COLOR_YELLOW, "%10.4f %s %10.4f %s ",
result.real_accumulated_time * multiplier,
big_o.c_str(),
result.cpu_accumulated_time * multiplier,
big_o.c_str());
}
else if(result.report_rms) {
ColorPrintf(COLOR_YELLOW, "%10.0f %% %10.0f %% ",
result.real_accumulated_time * multiplier * 100,
result.cpu_accumulated_time * multiplier * 100);
}
else if (result.iterations == 0) {
ColorPrintf(COLOR_YELLOW, "%10.0f %s %10.0f %s ",
result.real_accumulated_time * multiplier,
timeLabel,
@ -116,7 +144,8 @@ void ConsoleReporter::PrintRunData(const Run& result) {
timeLabel);
}
ColorPrintf(COLOR_CYAN, "%10lld", result.iterations);
if(!result.report_big_o && !result.report_rms)
ColorPrintf(COLOR_CYAN, "%10lld", result.iterations);
if (!rate.empty()) {
ColorPrintf(COLOR_DEFAULT, " %*s", 13, rate.c_str());

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@ -48,7 +48,7 @@ bool CSVReporter::ReportContext(const Context& context) {
return true;
}
void CSVReporter::ReportRuns(std::vector<Run> const& reports) {
void CSVReporter::ReportRuns(const std::vector<Run> & reports) {
if (reports.empty()) {
return;
}
@ -66,7 +66,22 @@ void CSVReporter::ReportRuns(std::vector<Run> const& reports) {
}
}
void CSVReporter::PrintRunData(Run const& run) {
void CSVReporter::ReportComplexity(const std::vector<Run> & complexity_reports) {
if (complexity_reports.size() < 2) {
// We don't report asymptotic complexity data if there was a single run.
return;
}
Run big_o_data;
Run rms_data;
BenchmarkReporter::ComputeBigO(complexity_reports, &big_o_data, &rms_data);
// Output using PrintRun.
PrintRunData(big_o_data);
PrintRunData(rms_data);
}
void CSVReporter::PrintRunData(const Run & run) {
double multiplier;
const char* timeLabel;
std::tie(timeLabel, multiplier) = GetTimeUnitAndMultiplier(run.time_unit);
@ -84,10 +99,20 @@ void CSVReporter::PrintRunData(Run const& run) {
ReplaceAll(&name, "\"", "\"\"");
std::cout << "\"" << name << "\",";
std::cout << run.iterations << ",";
// Do not print iteration on bigO and RMS report
if(!run.report_big_o && !run.report_rms)
std::cout << run.iterations << ",";
else
std::cout << ",";
std::cout << real_time << ",";
std::cout << cpu_time << ",";
std::cout << timeLabel << ",";
// Do not print timeLabel on RMS report
if(!run.report_rms)
std::cout << timeLabel << ",";
else
std::cout << ",";
if (run.bytes_per_second > 0.0) {
std::cout << run.bytes_per_second;

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@ -115,6 +115,31 @@ void JSONReporter::ReportRuns(std::vector<Run> const& reports) {
}
}
void JSONReporter::ReportComplexity(const std::vector<Run> & complexity_reports) {
if (complexity_reports.size() < 2) {
// We don't report asymptotic complexity data if there was a single run.
return;
}
std::string indent(4, ' ');
std::ostream& out = std::cout;
if (!first_report_) {
out << ",\n";
}
Run big_o_data;
Run rms_data;
BenchmarkReporter::ComputeBigO(complexity_reports, &big_o_data, &rms_data);
// Output using PrintRun.
out << indent << "{\n";
PrintRunData(big_o_data);
out << indent << "},\n";
out << indent << "{\n";
PrintRunData(rms_data);
out << indent << '}';
}
void JSONReporter::Finalize() {
// Close the list of benchmarks and the top level object.
std::cout << "\n ]\n}\n";
@ -137,17 +162,20 @@ void JSONReporter::PrintRunData(Run const& run) {
out << indent
<< FormatKV("name", run.benchmark_name)
<< ",\n";
out << indent
<< FormatKV("iterations", run.iterations)
<< ",\n";
if(!run.report_big_o && !run.report_rms) {
out << indent
<< FormatKV("iterations", run.iterations)
<< ",\n";
}
out << indent
<< FormatKV("real_time", RoundDouble(real_time))
<< ",\n";
out << indent
<< FormatKV("cpu_time", RoundDouble(cpu_time))
<< ",\n";
out << indent
<< FormatKV("time_unit", timeLabel);
<< FormatKV("cpu_time", RoundDouble(cpu_time));
if(!run.report_rms) {
out << ",\n" << indent
<< FormatKV("time_unit", timeLabel);
}
if (run.bytes_per_second > 0.0) {
out << ",\n" << indent
<< FormatKV("bytes_per_second", RoundDouble(run.bytes_per_second));

115
src/minimal_leastsq.cc Normal file
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@ -0,0 +1,115 @@
// Copyright 2016 Ismael Jimenez Martinez. All rights reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// Source project : https://github.com/ismaelJimenez/cpp.leastsq
// Adapted to be used with google benchmark
#include "minimal_leastsq.h"
#include "check.h"
#include <math.h>
// Internal function to calculate the different scalability forms
double FittingCurve(double n, benchmark::BigO complexity) {
switch (complexity) {
case benchmark::oN:
return n;
case benchmark::oNSquared:
return pow(n, 2);
case benchmark::oNCubed:
return pow(n, 3);
case benchmark::oLogN:
return log2(n);
case benchmark::oNLogN:
return n * log2(n);
case benchmark::o1:
default:
return 1;
}
}
// Internal function to find the coefficient for the high-order term in the running time, by minimizing the sum of squares of relative error.
// - n : Vector containing the size of the benchmark tests.
// - time : Vector containing the times for the benchmark tests.
// - complexity : Fitting curve.
// For a deeper explanation on the algorithm logic, look the README file at http://github.com/ismaelJimenez/Minimal-Cpp-Least-Squared-Fit
LeastSq CalculateLeastSq(const std::vector<int>& n, const std::vector<double>& time, const benchmark::BigO complexity) {
CHECK_NE(complexity, benchmark::oAuto);
double sigma_gn = 0;
double sigma_gn_squared = 0;
double sigma_time = 0;
double sigma_time_gn = 0;
// Calculate least square fitting parameter
for (size_t i = 0; i < n.size(); ++i) {
double gn_i = FittingCurve(n[i], complexity);
sigma_gn += gn_i;
sigma_gn_squared += gn_i * gn_i;
sigma_time += time[i];
sigma_time_gn += time[i] * gn_i;
}
LeastSq result;
result.complexity = complexity;
// Calculate complexity.
// o1 is treated as an special case
if (complexity != benchmark::o1)
result.coef = sigma_time_gn / sigma_gn_squared;
else
result.coef = sigma_time / n.size();
// Calculate RMS
double rms = 0;
for (size_t i = 0; i < n.size(); ++i) {
double fit = result.coef * FittingCurve(n[i], complexity);
rms += pow((time[i] - fit), 2);
}
double mean = sigma_time / n.size();
result.rms = sqrt(rms / n.size()) / mean; // Normalized RMS by the mean of the observed values
return result;
}
// Find the coefficient for the high-order term in the running time, by minimizing the sum of squares of relative error.
// - n : Vector containing the size of the benchmark tests.
// - time : Vector containing the times for the benchmark tests.
// - complexity : If different than oAuto, the fitting curve will stick to this one. If it is oAuto, it will be calculated
// the best fitting curve.
LeastSq MinimalLeastSq(const std::vector<int>& n, const std::vector<double>& time, const benchmark::BigO complexity) {
CHECK_EQ(n.size(), time.size());
CHECK_GE(n.size(), 2); // Do not compute fitting curve is less than two benchmark runs are given
CHECK_NE(complexity, benchmark::oNone);
if(complexity == benchmark::oAuto) {
std::vector<benchmark::BigO> fit_curves = { benchmark::oLogN, benchmark::oN, benchmark::oNLogN, benchmark::oNSquared, benchmark::oNCubed };
LeastSq best_fit = CalculateLeastSq(n, time, benchmark::o1); // Take o1 as default best fitting curve
// Compute all possible fitting curves and stick to the best one
for (const auto& fit : fit_curves) {
LeastSq current_fit = CalculateLeastSq(n, time, fit);
if (current_fit.rms < best_fit.rms)
best_fit = current_fit;
}
return best_fit;
}
else
return CalculateLeastSq(n, time, complexity);
}

46
src/minimal_leastsq.h Normal file
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@ -0,0 +1,46 @@
// Copyright 2016 Ismael Jimenez Martinez. All rights reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// Source project : https://github.com/ismaelJimenez/cpp.leastsq
// Adapted to be used with google benchmark
#if !defined(MINIMAL_LEASTSQ_H_)
#define MINIMAL_LEASTSQ_H_
#include "benchmark/benchmark_api.h"
#include <vector>
// This data structure will contain the result returned by MinimalLeastSq
// - coef : Estimated coeficient for the high-order term as interpolated from data.
// - rms : Normalized Root Mean Squared Error.
// - complexity : Scalability form (e.g. oN, oNLogN). In case a scalability form has been provided to MinimalLeastSq
// this will return the same value. In case BigO::oAuto has been selected, this parameter will return the
// best fitting curve detected.
struct LeastSq {
LeastSq() :
coef(0),
rms(0),
complexity(benchmark::oNone) {}
double coef;
double rms;
benchmark::BigO complexity;
};
// Find the coefficient for the high-order term in the running time, by minimizing the sum of squares of relative error.
LeastSq MinimalLeastSq(const std::vector<int>& n, const std::vector<double>& time, const benchmark::BigO complexity = benchmark::oAuto);
#endif

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@ -13,9 +13,11 @@
// limitations under the License.
#include "benchmark/reporter.h"
#include "minimal_leastsq.h"
#include <cstdlib>
#include <vector>
#include <tuple>
#include "check.h"
#include "stat.h"
@ -77,6 +79,55 @@ void BenchmarkReporter::ComputeStats(
stddev_data->items_per_second = items_per_second_stat.StdDev();
}
void BenchmarkReporter::ComputeBigO(
const std::vector<Run>& reports,
Run* big_o, Run* rms) {
CHECK(reports.size() >= 2) << "Cannot compute asymptotic complexity for less than 2 reports";
// Accumulators.
std::vector<int> n;
std::vector<double> real_time;
std::vector<double> cpu_time;
// Populate the accumulators.
for (const Run& run : reports) {
n.push_back(run.complexity_n);
real_time.push_back(run.real_accumulated_time/run.iterations);
cpu_time.push_back(run.cpu_accumulated_time/run.iterations);
}
LeastSq result_cpu = MinimalLeastSq(n, cpu_time, reports[0].complexity);
// result_cpu.complexity is passed as parameter to result_real because in case
// reports[0].complexity is oAuto, the noise on the measured data could make
// the best fit function of Cpu and Real differ. In order to solve this, we take
// the best fitting function for the Cpu, and apply it to Real data.
LeastSq result_real = MinimalLeastSq(n, real_time, result_cpu.complexity);
std::string benchmark_name = reports[0].benchmark_name.substr(0, reports[0].benchmark_name.find('/'));
// Get the data from the accumulator to BenchmarkReporter::Run's.
big_o->benchmark_name = benchmark_name + "_BigO";
big_o->iterations = 0;
big_o->real_accumulated_time = result_real.coef;
big_o->cpu_accumulated_time = result_cpu.coef;
big_o->report_big_o = true;
big_o->complexity = result_cpu.complexity;
double multiplier;
const char* time_label;
std::tie(time_label, multiplier) = GetTimeUnitAndMultiplier(reports[0].time_unit);
// Only add label to mean/stddev if it is same for all runs
big_o->report_label = reports[0].report_label;
rms->benchmark_name = benchmark_name + "_RMS";
rms->report_label = big_o->report_label;
rms->iterations = 0;
rms->real_accumulated_time = result_real.rms / multiplier;
rms->cpu_accumulated_time = result_cpu.rms / multiplier;
rms->report_rms = true;
rms->complexity = result_cpu.complexity;
}
TimeUnitMultiplier BenchmarkReporter::GetTimeUnitAndMultiplier(TimeUnit unit) {
switch (unit) {
case kMillisecond:

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@ -55,6 +55,9 @@ if (BENCHMARK_HAS_CXX03_FLAG)
add_test(cxx03 cxx03_test --benchmark_min_time=0.01)
endif()
compile_benchmark_test(complexity_test)
add_test(complexity_benchmark complexity_test --benchmark_min_time=0.01)
# Add the coverage command(s)
if(CMAKE_BUILD_TYPE)
string(TOLOWER ${CMAKE_BUILD_TYPE} CMAKE_BUILD_TYPE_LOWER)
@ -74,7 +77,7 @@ if (${CMAKE_BUILD_TYPE_LOWER} MATCHES "coverage")
COMMAND ${LCOV} -q -a before.lcov -a after.lcov --output-file final.lcov
COMMAND ${LCOV} -q -r final.lcov "'${CMAKE_SOURCE_DIR}/test/*'" -o final.lcov
COMMAND ${GENHTML} final.lcov -o lcov --demangle-cpp --sort -p "${CMAKE_BINARY_DIR}" -t benchmark
DEPENDS filter_test benchmark_test options_test basic_test fixture_test cxx03_test
DEPENDS filter_test benchmark_test options_test basic_test fixture_test cxx03_test complexity_test
WORKING_DIRECTORY ${CMAKE_BINARY_DIR}
COMMENT "Running LCOV"
)

105
test/complexity_test.cc Normal file
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@ -0,0 +1,105 @@
#include "benchmark/benchmark_api.h"
#include <string>
#include <vector>
#include <map>
#include <algorithm>
std::vector<int> ConstructRandomVector(int size) {
std::vector<int> v;
v.reserve(size);
for (int i = 0; i < size; ++i) {
v.push_back(rand() % size);
}
return v;
}
std::map<int, int> ConstructRandomMap(int size) {
std::map<int, int> m;
for (int i = 0; i < size; ++i) {
m.insert(std::make_pair(rand() % size, rand() % size));
}
return m;
}
void BM_Complexity_O1(benchmark::State& state) {
while (state.KeepRunning()) {
}
state.SetComplexityN(state.range_x());
}
BENCHMARK(BM_Complexity_O1) -> Range(1, 1<<18) -> Complexity(benchmark::o1);
static void BM_Complexity_O_N(benchmark::State& state) {
auto v = ConstructRandomVector(state.range_x());
const int item_not_in_vector = state.range_x()*2; // Test worst case scenario (item not in vector)
while (state.KeepRunning()) {
benchmark::DoNotOptimize(std::find(v.begin(), v.end(), item_not_in_vector));
}
state.SetComplexityN(state.range_x());
}
BENCHMARK(BM_Complexity_O_N) -> RangeMultiplier(2) -> Range(1<<10, 1<<16) -> Complexity(benchmark::oN);
BENCHMARK(BM_Complexity_O_N) -> RangeMultiplier(2) -> Range(1<<10, 1<<16) -> Complexity(benchmark::oAuto);
static void BM_Complexity_O_N_Squared(benchmark::State& state) {
std::string s1(state.range_x(), '-');
std::string s2(state.range_x(), '-');
state.SetComplexityN(state.range_x());
while (state.KeepRunning())
for(char& c1 : s1) {
for(char& c2 : s2) {
benchmark::DoNotOptimize(c1 = 'a');
benchmark::DoNotOptimize(c2 = 'b');
}
}
}
BENCHMARK(BM_Complexity_O_N_Squared) -> Range(1, 1<<8) -> Complexity(benchmark::oNSquared);
static void BM_Complexity_O_N_Cubed(benchmark::State& state) {
std::string s1(state.range_x(), '-');
std::string s2(state.range_x(), '-');
std::string s3(state.range_x(), '-');
state.SetComplexityN(state.range_x());
while (state.KeepRunning())
for(char& c1 : s1) {
for(char& c2 : s2) {
for(char& c3 : s3) {
benchmark::DoNotOptimize(c1 = 'a');
benchmark::DoNotOptimize(c2 = 'b');
benchmark::DoNotOptimize(c3 = 'c');
}
}
}
}
BENCHMARK(BM_Complexity_O_N_Cubed) -> DenseRange(1, 8) -> Complexity(benchmark::oNCubed);
static void BM_Complexity_O_log_N(benchmark::State& state) {
auto m = ConstructRandomMap(state.range_x());
const int item_not_in_vector = state.range_x()*2; // Test worst case scenario (item not in vector)
while (state.KeepRunning()) {
benchmark::DoNotOptimize(m.find(item_not_in_vector));
}
state.SetComplexityN(state.range_x());
}
BENCHMARK(BM_Complexity_O_log_N)
-> RangeMultiplier(2) -> Range(1<<10, 1<<16) -> Complexity(benchmark::oLogN);
static void BM_Complexity_O_N_log_N(benchmark::State& state) {
auto v = ConstructRandomVector(state.range_x());
while (state.KeepRunning()) {
std::sort(v.begin(), v.end());
}
state.SetComplexityN(state.range_x());
}
BENCHMARK(BM_Complexity_O_N_log_N) -> RangeMultiplier(2) -> Range(1<<10, 1<<16) -> Complexity(benchmark::oNLogN);
BENCHMARK(BM_Complexity_O_N_log_N) -> RangeMultiplier(2) -> Range(1<<10, 1<<16) -> Complexity(benchmark::oAuto);
// Test benchmark with no range and check no complexity is calculated.
void BM_Extreme_Cases(benchmark::State& state) {
while (state.KeepRunning()) {
}
}
BENCHMARK(BM_Extreme_Cases) -> Complexity(benchmark::oNLogN);
BENCHMARK(BM_Extreme_Cases) -> Arg(42) -> Complexity(benchmark::oAuto);
BENCHMARK_MAIN()