// Copyright (c) 2013, Facebook, Inc. All rights reserved. // This source code is licensed under the BSD-style license found in the // LICENSE file in the root directory of this source tree. An additional grant // of patent rights can be found in the PATENTS file in the same directory. // // This code is derived from Benchmark.cpp implemented in Folly, the opensourced // Facebook C++ library available at https://github.com/facebook/folly // The code has removed any dependence on other folly and boost libraries #include "util/benchharness.h" #include #include #include #include #include #include #include using std::function; using std::get; using std::make_pair; using std::max; using std::min; using std::pair; using std::sort; using std::string; using std::tuple; using std::vector; DEFINE_bool(benchmark, false, "Run benchmarks."); DEFINE_int64(bm_min_usec, 100, "Minimum # of microseconds we'll accept for each benchmark."); DEFINE_int64(bm_min_iters, 1, "Minimum # of iterations we'll try for each benchmark."); DEFINE_int32(bm_max_secs, 1, "Maximum # of seconds we'll spend on each benchmark."); namespace rocksdb { namespace benchmark { BenchmarkSuspender::NanosecondsSpent BenchmarkSuspender::nsSpent; typedef function BenchmarkFun; static vector> benchmarks; // Add the global baseline BENCHMARK(globalBenchmarkBaseline) { asm volatile(""); } void detail::AddBenchmarkImpl(const char* file, const char* name, BenchmarkFun fun) { benchmarks.emplace_back(file, name, std::move(fun)); } /** * Given a point, gives density at that point as a number 0.0 < x <= * 1.0. The result is 1.0 if all samples are equal to where, and * decreases near 0 if all points are far away from it. The density is * computed with the help of a radial basis function. */ static double Density(const double * begin, const double *const end, const double where, const double bandwidth) { assert(begin < end); assert(bandwidth > 0.0); double sum = 0.0; for (auto i = begin; i < end; i++) { auto d = (*i - where) / bandwidth; sum += exp(- d * d); } return sum / (end - begin); } /** * Computes mean and variance for a bunch of data points. Note that * mean is currently not being used. */ static pair MeanVariance(const double * begin, const double *const end) { assert(begin < end); double sum = 0.0, sum2 = 0.0; for (auto i = begin; i < end; i++) { sum += *i; sum2 += *i * *i; } auto const n = end - begin; return make_pair(sum / n, sqrt((sum2 - sum * sum / n) / n)); } /** * Computes the mode of a sample set through brute force. Assumes * input is sorted. */ static double Mode(const double * begin, const double *const end) { assert(begin < end); // Lower bound and upper bound for result and their respective // densities. auto result = 0.0, bestDensity = 0.0; // Get the variance so we pass it down to Density() auto const sigma = MeanVariance(begin, end).second; if (!sigma) { // No variance means constant signal return *begin; } for (auto i = begin; i < end; i++) { assert(i == begin || *i >= i[-1]); auto candidate = Density(begin, end, *i, sigma * sqrt(2.0)); if (candidate > bestDensity) { // Found a new best bestDensity = candidate; result = *i; } else { // Density is decreasing... we could break here if we definitely // knew this is unimodal. } } return result; } /** * Given a bunch of benchmark samples, estimate the actual run time. */ static double EstimateTime(double * begin, double * end) { assert(begin < end); // Current state of the art: get the minimum. After some // experimentation, it seems taking the minimum is the best. return *std::min_element(begin, end); // What follows after estimates the time as the mode of the // distribution. // Select the awesomest (i.e. most frequent) result. We do this by // sorting and then computing the longest run length. sort(begin, end); // Eliminate outliers. A time much larger than the minimum time is // considered an outlier. while (end[-1] > 2.0 * *begin) { --end; if (begin == end) { // LOG(INFO) << *begin; } assert(begin < end); } double result = 0; /* Code used just for comparison purposes */ { unsigned bestFrequency = 0; unsigned candidateFrequency = 1; double candidateValue = *begin; for (auto current = begin + 1; ; ++current) { if (current == end || *current != candidateValue) { // Done with the current run, see if it was best if (candidateFrequency > bestFrequency) { bestFrequency = candidateFrequency; result = candidateValue; } if (current == end) { break; } // Start a new run candidateValue = *current; candidateFrequency = 1; } else { // Cool, inside a run, increase the frequency ++candidateFrequency; } } } result = Mode(begin, end); return result; } static double RunBenchmarkGetNSPerIteration(const BenchmarkFun& fun, const double globalBaseline) { // They key here is accuracy; too low numbers means the accuracy was // coarse. We up the ante until we get to at least minNanoseconds // timings. static const auto minNanoseconds = FLAGS_bm_min_usec * 1000UL; // We do measurements in several epochs and take the minimum, to // account for jitter. static const unsigned int epochs = 1000; // We establish a total time budget as we don't want a measurement // to take too long. This will curtail the number of actual epochs. const uint64_t timeBudgetInNs = FLAGS_bm_max_secs * 1000000000; auto env = Env::Default(); uint64_t global = env->NowNanos(); double epochResults[epochs] = { 0 }; size_t actualEpochs = 0; for (; actualEpochs < epochs; ++actualEpochs) { for (unsigned int n = FLAGS_bm_min_iters; n < (1UL << 30); n *= 2) { auto const nsecs = fun(n); if (nsecs < minNanoseconds) { continue; } // We got an accurate enough timing, done. But only save if // smaller than the current result. epochResults[actualEpochs] = max(0.0, static_cast(nsecs) / n - globalBaseline); // Done with the current epoch, we got a meaningful timing. break; } uint64_t now = env->NowNanos(); if ((now - global) >= timeBudgetInNs) { // No more time budget available. ++actualEpochs; break; } } // If the benchmark was basically drowned in baseline noise, it's // possible it became negative. return max(0.0, EstimateTime(epochResults, epochResults + actualEpochs)); } struct ScaleInfo { double boundary; const char* suffix; }; static const ScaleInfo kTimeSuffixes[] { { 365.25 * 24 * 3600, "years" }, { 24 * 3600, "days" }, { 3600, "hr" }, { 60, "min" }, { 1, "s" }, { 1E-3, "ms" }, { 1E-6, "us" }, { 1E-9, "ns" }, { 1E-12, "ps" }, { 1E-15, "fs" }, { 0, nullptr }, }; static const ScaleInfo kMetricSuffixes[] { { 1E24, "Y" }, // yotta { 1E21, "Z" }, // zetta { 1E18, "X" }, // "exa" written with suffix 'X' so as to not create // confusion with scientific notation { 1E15, "P" }, // peta { 1E12, "T" }, // terra { 1E9, "G" }, // giga { 1E6, "M" }, // mega { 1E3, "K" }, // kilo { 1, "" }, { 1E-3, "m" }, // milli { 1E-6, "u" }, // micro { 1E-9, "n" }, // nano { 1E-12, "p" }, // pico { 1E-15, "f" }, // femto { 1E-18, "a" }, // atto { 1E-21, "z" }, // zepto { 1E-24, "y" }, // yocto { 0, nullptr }, }; static string HumanReadable(double n, unsigned int decimals, const ScaleInfo* scales) { if (std::isinf(n) || std::isnan(n)) { return std::to_string(n); } const double absValue = fabs(n); const ScaleInfo* scale = scales; while (absValue < scale[0].boundary && scale[1].suffix != nullptr) { ++scale; } const double scaledValue = n / scale->boundary; char a[80]; snprintf(a, sizeof(a), "%.*f%s", decimals, scaledValue, scale->suffix); return a; } static string ReadableTime(double n, unsigned int decimals) { return HumanReadable(n, decimals, kTimeSuffixes); } static string MetricReadable(double n, unsigned int decimals) { return HumanReadable(n, decimals, kMetricSuffixes); } static void PrintBenchmarkResultsAsTable( const vector >& data) { // Width available static const uint columns = 76; // Compute the longest benchmark name size_t longestName = 0; for (size_t i = 1; i < benchmarks.size(); i++) { longestName = max(longestName, strlen(get<1>(benchmarks[i]))); } // Print a horizontal rule auto separator = [&](char pad) { puts(string(columns, pad).c_str()); }; // Print header for a file auto header = [&](const char* file) { separator('='); printf("%-*srelative time/iter iters/s\n", columns - 28, file); separator('='); }; double baselineNsPerIter = std::numeric_limits::max(); const char* lastFile = ""; for (auto& datum : data) { auto file = get<0>(datum); if (strcmp(file, lastFile)) { // New file starting header(file); lastFile = file; } string s = get<1>(datum); if (s == "-") { separator('-'); continue; } bool useBaseline /* = void */; if (s[0] == '%') { s.erase(0, 1); useBaseline = true; } else { baselineNsPerIter = get<2>(datum); useBaseline = false; } s.resize(columns - 29, ' '); auto nsPerIter = get<2>(datum); auto secPerIter = nsPerIter / 1E9; auto itersPerSec = 1 / secPerIter; if (!useBaseline) { // Print without baseline printf("%*s %9s %7s\n", static_cast(s.size()), s.c_str(), ReadableTime(secPerIter, 2).c_str(), MetricReadable(itersPerSec, 2).c_str()); } else { // Print with baseline auto rel = baselineNsPerIter / nsPerIter * 100.0; printf("%*s %7.2f%% %9s %7s\n", static_cast(s.size()), s.c_str(), rel, ReadableTime(secPerIter, 2).c_str(), MetricReadable(itersPerSec, 2).c_str()); } } separator('='); } void RunBenchmarks() { ASSERT_TRUE(!benchmarks.empty()); vector> results; results.reserve(benchmarks.size() - 1); // PLEASE KEEP QUIET. MEASUREMENTS IN PROGRESS. auto const globalBaseline = RunBenchmarkGetNSPerIteration( get<2>(benchmarks.front()), 0); for (size_t i = 1; i < benchmarks.size(); i++) { double elapsed = 0.0; if (strcmp(get<1>(benchmarks[i]), "-") != 0) { // skip separators elapsed = RunBenchmarkGetNSPerIteration(get<2>(benchmarks[i]), globalBaseline); } results.emplace_back(get<0>(benchmarks[i]), get<1>(benchmarks[i]), elapsed); } // PLEASE MAKE NOISE. MEASUREMENTS DONE. PrintBenchmarkResultsAsTable(results); } } // namespace benchmark } // namespace rocksdb