aboutsummaryrefslogtreecommitdiff
diff options
context:
space:
mode:
Diffstat
-rw-r--r--contrib/epee/include/stats.h58
-rw-r--r--contrib/epee/include/stats.inl359
-rw-r--r--src/common/CMakeLists.txt2
-rw-r--r--src/common/perf_timer.h1
-rw-r--r--src/common/timings.cc125
-rw-r--r--src/common/timings.h34
-rw-r--r--tests/performance_tests/main.cpp5
-rw-r--r--tests/performance_tests/performance_tests.h116
8 files changed, 638 insertions, 62 deletions
diff --git a/contrib/epee/include/stats.h b/contrib/epee/include/stats.h
new file mode 100644
index 000000000..1cf9c68fb
--- /dev/null
+++ b/contrib/epee/include/stats.h
@@ -0,0 +1,58 @@
+#pragma once
+
+#include <vector>
+
+template<typename T, typename Tpod = T>
+class Stats
+{
+public:
+ Stats(const std::vector<T> &v): values(v), cached(0) {}
+ ~Stats() {}
+
+ size_t get_size() const;
+ Tpod get_min() const;
+ Tpod get_max() const;
+ Tpod get_median() const;
+ double get_mean() const;
+ double get_confidence_interval_95() const;
+ double get_confidence_interval_99() const;
+ double get_standard_deviation() const;
+ double get_standard_error() const;
+ double get_variance() const;
+ double get_kurtosis() const;
+ double get_non_parametric_skew() const;
+ double get_t_test(T t) const;
+ double get_t_test(size_t npoints, double mean, double stddev) const;
+ double get_t_test(const Stats<T> &other) const;
+ double get_z_test(const Stats<T> &other) const;
+ double get_test(const Stats<T> &other) const;
+ std::vector<Tpod> get_quantiles(unsigned int quantiles) const;
+ std::vector<size_t> get_bins(unsigned int bins) const;
+ bool is_same_distribution_95(size_t npoints, double mean, double stddev) const;
+ bool is_same_distribution_95(const Stats<T> &other) const;
+ bool is_same_distribution_99(size_t npoints, double mean, double stddev) const;
+ bool is_same_distribution_99(const Stats<T> &other) const;
+
+ double get_cdf95(size_t df) const;
+ double get_cdf95(const Stats<T> &other) const;
+ double get_cdf99(size_t df) const;
+ double get_cdf99(const Stats<T> &other) const;
+
+private:
+ inline bool is_cached(int bit) const;
+ inline void set_cached(int bit) const;
+
+ const std::vector<T> &values;
+
+ mutable uint64_t cached;
+ mutable Tpod min;
+ mutable Tpod max;
+ mutable Tpod median;
+ mutable double mean;
+ mutable double standard_deviation;
+ mutable double standard_error;
+ mutable double variance;
+ mutable double kurtosis;
+};
+
+#include "stats.inl"
diff --git a/contrib/epee/include/stats.inl b/contrib/epee/include/stats.inl
new file mode 100644
index 000000000..5a5cd0b93
--- /dev/null
+++ b/contrib/epee/include/stats.inl
@@ -0,0 +1,359 @@
+#include <math.h>
+#include <limits>
+#include <algorithm>
+#include "stats.h"
+
+enum
+{
+ bit_min = 0,
+ bit_max,
+ bit_median,
+ bit_mean,
+ bit_standard_deviation,
+ bit_standard_error,
+ bit_variance,
+ bit_kurtosis,
+};
+
+static inline double square(double x)
+{
+ return x * x;
+}
+
+template<typename T>
+static inline double interpolate(T v, T v0, double i0, T v1, double i1)
+{
+ return i0 + (i1 - i0) * (v - v0) / (v1 - v0);
+}
+
+template<typename T, typename Tpod>
+inline bool Stats<T, Tpod>::is_cached(int bit) const
+{
+ return cached & (1<<bit);
+}
+
+template<typename T, typename Tpod>
+inline void Stats<T, Tpod>::set_cached(int bit) const
+{
+ cached |= 1<<bit;
+}
+
+template<typename T, typename Tpod>
+size_t Stats<T, Tpod>::get_size() const
+{
+ return values.size();
+}
+
+template<typename T, typename Tpod>
+Tpod Stats<T, Tpod>::get_min() const
+{
+ if (!is_cached(bit_min))
+ {
+ min = std::numeric_limits<Tpod>::max();
+ for (const T &v: values)
+ min = std::min<Tpod>(min, v);
+ set_cached(bit_min);
+ }
+ return min;
+}
+
+template<typename T, typename Tpod>
+Tpod Stats<T, Tpod>::get_max() const
+{
+ if (!is_cached(bit_max))
+ {
+ max = std::numeric_limits<Tpod>::min();
+ for (const T &v: values)
+ max = std::max<Tpod>(max, v);
+ set_cached(bit_max);
+ }
+ return max;
+}
+
+template<typename T, typename Tpod>
+Tpod Stats<T, Tpod>::get_median() const
+{
+ if (!is_cached(bit_median))
+ {
+ std::vector<Tpod> sorted;
+ sorted.reserve(values.size());
+ for (const T &v: values)
+ sorted.push_back(v);
+ std::sort(sorted.begin(), sorted.end());
+ if (sorted.size() & 1)
+ {
+ median = sorted[sorted.size() / 2];
+ }
+ else
+ {
+ median = (sorted[(sorted.size() - 1) / 2] + sorted[sorted.size() / 2]) / 2;
+ }
+ set_cached(bit_median);
+ }
+ return median;
+}
+
+template<typename T, typename Tpod>
+double Stats<T, Tpod>::get_mean() const
+{
+ if (values.empty())
+ return 0.0;
+ if (!is_cached(bit_mean))
+ {
+ mean = 0.0;
+ for (const T &v: values)
+ mean += v;
+ mean /= values.size();
+ set_cached(bit_mean);
+ }
+ return mean;
+}
+
+template<typename T, typename Tpod>
+double Stats<T, Tpod>::get_cdf95(size_t df) const
+{
+ static const double p[101] = {
+ -1, 12.706, 4.3027, 3.1824, 2.7765, 2.5706, 2.4469, 2.3646, 2.3060, 2.2622, 2.2281, 2.2010, 2.1788, 2.1604, 2.1448, 2.1315,
+ 2.1199, 2.1098, 2.1009, 2.0930, 2.0860, 2.0796, 2.0739, 2.0687, 2.0639, 2.0595, 2.0555, 2.0518, 2.0484, 2.0452, 2.0423, 2.0395,
+ 2.0369, 2.0345, 2.0322, 2.0301, 2.0281, 2.0262, 2.0244, 2.0227, 2.0211, 2.0195, 2.0181, 2.0167, 2.0154, 2.0141, 2.0129, 2.0117,
+ 2.0106, 2.0096, 2.0086, 2.0076, 2.0066, 2.0057, 2.0049, 2.0040, 2.0032, 2.0025, 2.0017, 2.0010, 2.0003, 1.9996, 1.9990, 1.9983,
+ 1.9977, 1.9971, 1.9966, 1.9960, 1.9955, 1.9949, 1.9944, 1.9939, 1.9935, 1.9930, 1.9925, 1.9921, 1.9917, 1.9913, 1.9908, 1.9905,
+ 1.9901, 1.9897, 1.9893, 1.9890, 1.9886, 1.9883, 1.9879, 1.9876, 1.9873, 1.9870, 1.9867, 1.9864, 1.9861, 1.9858, 1.9855, 1.9852,
+ 1.9850, 1.9847, 1.9845, 1.9842, 1.9840,
+ };
+ if (df <= 100)
+ return p[df];
+ if (df <= 120)
+ return interpolate<size_t>(df, 100, 1.9840, 120, 1.98);
+ return 1.96;
+}
+
+template<typename T, typename Tpod>
+double Stats<T, Tpod>::get_cdf95(const Stats<T> &other) const
+{
+ return get_cdf95(get_size() + other.get_size() - 2);
+}
+
+template<typename T, typename Tpod>
+double Stats<T, Tpod>::get_cdf99(size_t df) const
+{
+ static const double p[101] = {
+ -1, 9.9250, 5.8408, 4.6041, 4.0321, 3.7074, 3.4995, 3.3554, 3.2498, 3.1693, 3.1058, 3.0545, 3.0123, 2.9768, 2.9467, 2.9208, 2.8982,
+ 2.8784, 2.8609, 2.8453, 2.8314, 2.8188, 2.8073, 2.7970, 2.7874, 2.7787, 2.7707, 2.7633, 2.7564, 2.7500, 2.7440, 2.7385, 2.7333,
+ 2.7284, 2.7238, 2.7195, 2.7154, 2.7116, 2.7079, 2.7045, 2.7012, 2.6981, 2.6951, 2.6923, 2.6896, 2.6870, 2.6846, 2.6822, 2.6800,
+ 2.6778, 2.6757, 2.6737, 2.6718, 2.6700, 2.6682, 2.6665, 2.6649, 2.6633, 2.6618, 2.6603, 2.6589, 2.6575, 2.6561, 2.6549, 2.6536,
+ 2.6524, 2.6512, 2.6501, 2.6490, 2.6479, 2.6469, 2.6458, 2.6449, 2.6439, 2.6430, 2.6421, 2.6412, 2.6403, 2.6395, 2.6387, 2.6379,
+ 2.6371, 2.6364, 2.6356, 2.6349, 2.6342, 2.6335, 2.6329, 2.6322, 2.6316, 2.6309, 2.6303, 2.6297, 2.6291, 2.6286, 2.6280, 2.6275,
+ 2.6269, 2.6264, 2.6259,
+ };
+ if (df <= 100)
+ return p[df];
+ if (df <= 120)
+ return interpolate<size_t>(df, 100, 2.6529, 120, 2.617);
+ return 2.576;
+}
+
+template<typename T, typename Tpod>
+double Stats<T, Tpod>::get_cdf99(const Stats<T> &other) const
+{
+ return get_cdf99(get_size() + other.get_size() - 2);
+}
+
+template<typename T, typename Tpod>
+double Stats<T, Tpod>::get_confidence_interval_95() const
+{
+ const size_t df = get_size() - 1;
+ return get_standard_error() * get_cdf95(df);
+}
+
+template<typename T, typename Tpod>
+double Stats<T, Tpod>::get_confidence_interval_99() const
+{
+ const size_t df = get_size() - 1;
+ return get_standard_error() * get_cdf99(df);
+}
+
+template<typename T, typename Tpod>
+bool Stats<T, Tpod>::is_same_distribution_95(size_t npoints, double mean, double stddev) const
+{
+ return fabs(get_t_test(npoints, mean, stddev)) < get_cdf95(get_size() + npoints - 2);
+}
+
+template<typename T, typename Tpod>
+bool Stats<T, Tpod>::is_same_distribution_95(const Stats<T> &other) const
+{
+ return fabs(get_t_test(other)) < get_cdf95(other);
+}
+
+template<typename T, typename Tpod>
+bool Stats<T, Tpod>::is_same_distribution_99(size_t npoints, double mean, double stddev) const
+{
+ return fabs(get_t_test(npoints, mean, stddev)) < get_cdf99(get_size() + npoints - 2);
+}
+
+template<typename T, typename Tpod>
+bool Stats<T, Tpod>::is_same_distribution_99(const Stats<T> &other) const
+{
+ return fabs(get_t_test(other)) < get_cdf99(other);
+}
+
+template<typename T, typename Tpod>
+double Stats<T, Tpod>::get_standard_deviation() const
+{
+ if (values.size() <= 1)
+ return 0.0;
+ if (!is_cached(bit_standard_deviation))
+ {
+ Tpod m = get_mean(), t = 0;
+ for (const T &v: values)
+ t += ((T)v - m) * ((T)v - m);
+ standard_deviation = sqrt(t / ((double)values.size() - 1));
+ set_cached(bit_standard_deviation);
+ }
+ return standard_deviation;
+}
+
+template<typename T, typename Tpod>
+double Stats<T, Tpod>::get_standard_error() const
+{
+ if (!is_cached(bit_standard_error))
+ {
+ standard_error = get_standard_deviation() / sqrt(get_size());
+ set_cached(bit_standard_error);
+ }
+ return standard_error;
+}
+
+template<typename T, typename Tpod>
+double Stats<T, Tpod>::get_variance() const
+{
+ if (!is_cached(bit_variance))
+ {
+ double stddev = get_standard_deviation();
+ variance = stddev * stddev;
+ set_cached(bit_variance);
+ }
+ return variance;
+}
+
+template<typename T, typename Tpod>
+double Stats<T, Tpod>::get_kurtosis() const
+{
+ if (values.empty())
+ return 0.0;
+ if (!is_cached(bit_kurtosis))
+ {
+ double m = get_mean();
+ double n = 0, d = 0;
+ for (const T &v: values)
+ {
+ T p2 = (v - m) * (v - m);
+ T p4 = p2 * p2;
+ n += p4;
+ d += p2;
+ }
+ n /= values.size();
+ d /= values.size();
+ d *= d;
+ kurtosis = n / d;
+ set_cached(bit_kurtosis);
+ }
+ return kurtosis;
+}
+
+template<typename T, typename Tpod>
+double Stats<T, Tpod>::get_non_parametric_skew() const
+{
+ return (get_mean() - get_median()) / get_standard_deviation();
+}
+
+template<typename T, typename Tpod>
+double Stats<T, Tpod>::get_t_test(T t) const
+{
+ const double n = get_mean() - t;
+ const double d = get_standard_deviation() / sqrt(get_size());
+ return n / d;
+}
+
+template<typename T, typename Tpod>
+double Stats<T, Tpod>::get_t_test(size_t npoints, double mean, double stddev) const
+{
+ const double n = get_mean() - mean;
+ const double d = sqrt(get_variance() / get_size() + square(stddev) / npoints);
+ return n / d;
+}
+
+template<typename T, typename Tpod>
+double Stats<T, Tpod>::get_t_test(const Stats<T> &other) const
+{
+ const double n = get_mean() - other.get_mean();
+ const double d = sqrt(get_variance() / get_size() + other.get_variance() / other.get_size());
+ return n / d;
+}
+
+template<typename T, typename Tpod>
+double Stats<T, Tpod>::get_z_test(const Stats<T> &other) const
+{
+ const double m0 = get_mean();
+ const double m1 = other.get_mean();
+ const double sd0 = get_standard_deviation();
+ const double sd1 = other.get_standard_deviation();
+ const size_t s0 = get_size();
+ const size_t s1 = other.get_size();
+
+ const double n = m0 - m1;
+ const double d = sqrt(square(sd0 / sqrt(s0)) + square(sd1 / sqrt(s1)));
+
+ return n / d;
+}
+
+template<typename T, typename Tpod>
+double Stats<T, Tpod>::get_test(const Stats<T> &other) const
+{
+ if (get_size() >= 30 && other.get_size() >= 30)
+ return get_z_test(other);
+ else
+ return get_t_test(other);
+}
+
+template<typename T, typename Tpod>
+std::vector<Tpod> Stats<T, Tpod>::get_quantiles(unsigned int quantiles) const
+{
+ std::vector<Tpod> sorted;
+ sorted.reserve(values.size());
+ for (const T &v: values)
+ sorted.push_back(v);
+ std::sort(sorted.begin(), sorted.end());
+ std::vector<Tpod> q(quantiles + 1, 0);
+ for (unsigned int i = 1; i <= quantiles; ++i)
+ {
+ unsigned idx = (unsigned)ceil(values.size() * i / (double)quantiles);
+ q[i] = sorted[idx - 1];
+ }
+ if (!is_cached(bit_min))
+ {
+ min = sorted.front();
+ set_cached(bit_min);
+ }
+ q[0] = min;
+ if (!is_cached(bit_max))
+ {
+ max = sorted.back();
+ set_cached(bit_max);
+ }
+ return q;
+}
+
+template<typename T, typename Tpod>
+std::vector<size_t> Stats<T, Tpod>::get_bins(unsigned int bins) const
+{
+ std::vector<size_t> b(bins, 0);
+ const double scale = 1.0 / (get_max() - get_min());
+ const T base = get_min();
+ for (const T &v: values)
+ {
+ unsigned int idx = (v - base) * scale;
+ ++b[idx];
+ }
+ return b;
+}
diff --git a/src/common/CMakeLists.txt b/src/common/CMakeLists.txt
index 212a1891e..bcf9cbce7 100644
--- a/src/common/CMakeLists.txt
+++ b/src/common/CMakeLists.txt
@@ -45,6 +45,7 @@ set(common_sources
threadpool.cpp
updates.cpp
aligned.c
+ timings.cc
combinator.cpp)
if (STACK_TRACE)
@@ -84,6 +85,7 @@ set(common_private_headers
threadpool.h
updates.h
aligned.h
+ timings.h
combinator.h)
monero_private_headers(common
diff --git a/src/common/perf_timer.h b/src/common/perf_timer.h
index d859cf576..5203da205 100644
--- a/src/common/perf_timer.h
+++ b/src/common/perf_timer.h
@@ -53,6 +53,7 @@ public:
void resume();
void reset();
uint64_t value() const;
+ operator uint64_t() const { return value(); }
protected:
uint64_t ticks;
diff --git a/src/common/timings.cc b/src/common/timings.cc
new file mode 100644
index 000000000..cb8deff2a
--- /dev/null
+++ b/src/common/timings.cc
@@ -0,0 +1,125 @@
+#include <string.h>
+#include <error.h>
+#include <time.h>
+#include <algorithm>
+#include <boost/algorithm/string.hpp>
+#include "misc_log_ex.h"
+#include "timings.h"
+
+#define N_EXPECTED_FIELDS (8+11)
+
+TimingsDatabase::TimingsDatabase()
+{
+}
+
+TimingsDatabase::TimingsDatabase(const std::string &filename):
+ filename(filename)
+{
+ load();
+}
+
+TimingsDatabase::~TimingsDatabase()
+{
+ save();
+}
+
+bool TimingsDatabase::load()
+{
+ instances.clear();
+
+ if (filename.empty())
+ return true;
+
+ FILE *f = fopen(filename.c_str(), "r");
+ if (!f)
+ {
+ MDEBUG("Failed to load timings file " << filename << ": " << strerror(errno));
+ return false;
+ }
+ while (1)
+ {
+ char s[4096];
+ if (!fgets(s, sizeof(s), f))
+ break;
+ char *tab = strchr(s, '\t');
+ if (!tab)
+ {
+ MWARNING("Bad format: no tab found");
+ continue;
+ }
+ const std::string name = std::string(s, tab - s);
+ std::vector<std::string> fields;
+ char *ptr = tab + 1;
+ boost::split(fields, ptr, boost::is_any_of(" "));
+ if (fields.size() != N_EXPECTED_FIELDS)
+ {
+ MERROR("Bad format: wrong number of fields: got " << fields.size() << " expected " << N_EXPECTED_FIELDS);
+ continue;
+ }
+
+ instance i;
+
+ unsigned int idx = 0;
+ i.t = atoi(fields[idx++].c_str());
+ i.npoints = atoi(fields[idx++].c_str());
+ i.min = atof(fields[idx++].c_str());
+ i.max = atof(fields[idx++].c_str());
+ i.mean = atof(fields[idx++].c_str());
+ i.median = atof(fields[idx++].c_str());
+ i.stddev = atof(fields[idx++].c_str());
+ i.npskew = atof(fields[idx++].c_str());
+ i.deciles.reserve(11);
+ for (int n = 0; n < 11; ++n)
+ {
+ i.deciles.push_back(atoi(fields[idx++].c_str()));
+ }
+ instances.insert(std::make_pair(name, i));
+ }
+ fclose(f);
+ return true;
+}
+
+bool TimingsDatabase::save()
+{
+ if (filename.empty())
+ return true;
+
+ FILE *f = fopen(filename.c_str(), "w");
+ if (!f)
+ {
+ MERROR("Failed to write to file " << filename << ": " << strerror(errno));
+ return false;
+ }
+ for (const auto &i: instances)
+ {
+ fprintf(f, "%s", i.first.c_str());
+ fprintf(f, "\t%lu", (unsigned long)i.second.t);
+ fprintf(f, " %zu", i.second.npoints);
+ fprintf(f, " %f", i.second.min);
+ fprintf(f, " %f", i.second.max);
+ fprintf(f, " %f", i.second.mean);
+ fprintf(f, " %f", i.second.median);
+ fprintf(f, " %f", i.second.stddev);
+ fprintf(f, " %f", i.second.npskew);
+ for (uint64_t v: i.second.deciles)
+ fprintf(f, " %lu", (unsigned long)v);
+ fputc('\n', f);
+ }
+ fclose(f);
+ return true;
+}
+
+std::vector<TimingsDatabase::instance> TimingsDatabase::get(const char *name) const
+{
+ std::vector<instance> ret;
+ auto range = instances.equal_range(name);
+ for (auto i = range.first; i != range.second; ++i)
+ ret.push_back(i->second);
+ std::sort(ret.begin(), ret.end(), [](const instance &e0, const instance &e1){ return e0.t < e1.t; });
+ return ret;
+}
+
+void TimingsDatabase::add(const char *name, const instance &i)
+{
+ instances.insert(std::make_pair(name, i));
+}
diff --git a/src/common/timings.h b/src/common/timings.h
new file mode 100644
index 000000000..fb905611f
--- /dev/null
+++ b/src/common/timings.h
@@ -0,0 +1,34 @@
+#pragma once
+
+#include <stdint.h>
+#include <string>
+#include <vector>
+#include <map>
+
+class TimingsDatabase
+{
+public:
+ struct instance
+ {
+ time_t t;
+ size_t npoints;
+ double min, max, mean, median, stddev, npskew;
+ std::vector<uint64_t> deciles;
+ };
+
+public:
+ TimingsDatabase();
+ TimingsDatabase(const std::string &filename);
+ ~TimingsDatabase();
+
+ std::vector<instance> get(const char *name) const;
+ void add(const char *name, const instance &data);
+
+private:
+ bool load();
+ bool save();
+
+private:
+ std::string filename;
+ std::multimap<std::string, instance> instances;
+};
diff --git a/tests/performance_tests/main.cpp b/tests/performance_tests/main.cpp
index 86450760c..22a86cb59 100644
--- a/tests/performance_tests/main.cpp
+++ b/tests/performance_tests/main.cpp
@@ -77,10 +77,12 @@ int main(int argc, char** argv)
const command_line::arg_descriptor<bool> arg_verbose = { "verbose", "Verbose output", false };
const command_line::arg_descriptor<bool> arg_stats = { "stats", "Including statistics (min/median)", false };
const command_line::arg_descriptor<unsigned> arg_loop_multiplier = { "loop-multiplier", "Run for that many times more loops", 1 };
+ const command_line::arg_descriptor<std::string> arg_timings_database = { "timings-database", "Keep timings history in a file" };
command_line::add_arg(desc_options, arg_filter);
command_line::add_arg(desc_options, arg_verbose);
command_line::add_arg(desc_options, arg_stats);
command_line::add_arg(desc_options, arg_loop_multiplier);
+ command_line::add_arg(desc_options, arg_timings_database);
po::variables_map vm;
bool r = command_line::handle_error_helper(desc_options, [&]()
@@ -93,7 +95,10 @@ int main(int argc, char** argv)
return 1;
const std::string filter = tools::glob_to_regex(command_line::get_arg(vm, arg_filter));
+ const std::string timings_database = command_line::get_arg(vm, arg_timings_database);
Params p;
+ if (!timings_database.empty())
+ p.td = TimingsDatabase(timings_database);
p.verbose = command_line::get_arg(vm, arg_verbose);
p.stats = command_line::get_arg(vm, arg_stats);
p.loop_multiplier = command_line::get_arg(vm, arg_loop_multiplier);
diff --git a/tests/performance_tests/performance_tests.h b/tests/performance_tests/performance_tests.h
index d37dda729..17d16b0f6 100644
--- a/tests/performance_tests/performance_tests.h
+++ b/tests/performance_tests/performance_tests.h
@@ -37,7 +37,9 @@
#include <boost/regex.hpp>
#include "misc_language.h"
+#include "stats.h"
#include "common/perf_timer.h"
+#include "common/timings.h"
class performance_timer
{
@@ -67,6 +69,7 @@ private:
struct Params
{
+ TimingsDatabase td;
bool verbose;
bool stats;
unsigned loop_multiplier;
@@ -85,6 +88,8 @@ public:
bool run()
{
+ static_assert(0 < T::loop_count, "T::loop_count must be greater than 0");
+
T test;
if (!test.init())
return false;
@@ -106,11 +111,13 @@ public:
m_per_call_timers[i].pause();
}
m_elapsed = timer.elapsed_ms();
+ m_stats.reset(new Stats<tools::PerformanceTimer, uint64_t>(m_per_call_timers));
return true;
}
int elapsed_time() const { return m_elapsed; }
+ size_t get_size() const { return m_stats->get_size(); }
int time_per_call(int scale = 1) const
{
@@ -118,59 +125,19 @@ public:
return m_elapsed * scale / (T::loop_count * m_params.loop_multiplier);
}
- uint64_t per_call_min() const
- {
- uint64_t v = std::numeric_limits<uint64_t>::max();
- for (const auto &pt: m_per_call_timers)
- v = std::min(v, pt.value());
- return v;
- }
-
- uint64_t per_call_max() const
- {
- uint64_t v = std::numeric_limits<uint64_t>::min();
- for (const auto &pt: m_per_call_timers)
- v = std::max(v, pt.value());
- return v;
- }
-
- uint64_t per_call_mean() const
- {
- uint64_t v = 0;
- for (const auto &pt: m_per_call_timers)
- v += pt.value();
- return v / m_per_call_timers.size();
- }
-
- uint64_t per_call_median() const
- {
- std::vector<uint64_t> values;
- values.reserve(m_per_call_timers.size());
- for (const auto &pt: m_per_call_timers)
- values.push_back(pt.value());
- return epee::misc_utils::median(values);
- }
+ uint64_t get_min() const { return m_stats->get_min(); }
+ uint64_t get_max() const { return m_stats->get_max(); }
+ double get_mean() const { return m_stats->get_mean(); }
+ uint64_t get_median() const { return m_stats->get_median(); }
+ double get_stddev() const { return m_stats->get_standard_deviation(); }
+ double get_non_parametric_skew() const { return m_stats->get_non_parametric_skew(); }
+ std::vector<uint64_t> get_quantiles(size_t n) const { return m_stats->get_quantiles(n); }
- uint64_t per_call_stddev() const
+ bool is_same_distribution(size_t npoints, double mean, double stddev) const
{
- if (m_per_call_timers.size() <= 1)
- return 0;
- const uint64_t mean = per_call_mean();
- uint64_t acc = 0;
- for (const auto &pt: m_per_call_timers)
- {
- int64_t dv = pt.value() - mean;
- acc += dv * dv;
- }
- acc /= m_per_call_timers.size () - 1;
- return sqrt(acc);
+ return m_stats->is_same_distribution_99(npoints, mean, stddev);
}
- uint64_t min_time_ns() const { return tools::ticks_to_ns(per_call_min()); }
- uint64_t max_time_ns() const { return tools::ticks_to_ns(per_call_max()); }
- uint64_t median_time_ns() const { return tools::ticks_to_ns(per_call_median()); }
- uint64_t standard_deviation_time_ns() const { return tools::ticks_to_ns(per_call_stddev()); }
-
private:
/**
* Warm up processor core, enabling turbo boost, etc.
@@ -191,10 +158,11 @@ private:
int m_elapsed;
Params m_params;
std::vector<tools::PerformanceTimer> m_per_call_timers;
+ std::unique_ptr<Stats<tools::PerformanceTimer, uint64_t>> m_stats;
};
template <typename T>
-void run_test(const std::string &filter, const Params &params, const char* test_name)
+void run_test(const std::string &filter, Params &params, const char* test_name)
{
boost::smatch match;
if (!filter.empty() && !boost::regex_match(std::string(test_name), match, boost::regex(filter)))
@@ -210,10 +178,10 @@ void run_test(const std::string &filter, const Params &params, const char* test_
std::cout << " elapsed: " << runner.elapsed_time() << " ms\n";
if (params.stats)
{
- std::cout << " min: " << runner.min_time_ns() << " ns\n";
- std::cout << " max: " << runner.max_time_ns() << " ns\n";
- std::cout << " median: " << runner.median_time_ns() << " ns\n";
- std::cout << " std dev: " << runner.standard_deviation_time_ns() << " ns\n";
+ std::cout << " min: " << runner.get_min() << " ns\n";
+ std::cout << " max: " << runner.get_max() << " ns\n";
+ std::cout << " median: " << runner.get_median() << " ns\n";
+ std::cout << " std dev: " << runner.get_stddev() << " ns\n";
}
}
else
@@ -221,24 +189,48 @@ void run_test(const std::string &filter, const Params &params, const char* test_
std::cout << test_name << " (" << T::loop_count * params.loop_multiplier << " calls) - OK:";
}
const char *unit = "ms";
- uint64_t scale = 1000000;
- int time_per_call = runner.time_per_call();
- if (time_per_call < 30000) {
+ double scale = 1000000;
+ uint64_t time_per_call = runner.time_per_call();
+ if (time_per_call < 100) {
+ scale = 1000;
time_per_call = runner.time_per_call(1000);
#ifdef _WIN32
unit = "\xb5s";
#else
unit = "µs";
#endif
- scale = 1000;
}
+ const auto quantiles = runner.get_quantiles(10);
+ double min = runner.get_min();
+ double max = runner.get_max();
+ double med = runner.get_median();
+ double mean = runner.get_mean();
+ double stddev = runner.get_stddev();
+ double npskew = runner.get_non_parametric_skew();
+
+ std::vector<TimingsDatabase::instance> prev_instances = params.td.get(test_name);
+ params.td.add(test_name, {time(NULL), runner.get_size(), min, max, mean, med, stddev, npskew, quantiles});
+
std::cout << (params.verbose ? " time per call: " : " ") << time_per_call << " " << unit << "/call" << (params.verbose ? "\n" : "");
if (params.stats)
{
- uint64_t min_ns = runner.min_time_ns() / scale;
- uint64_t med_ns = runner.median_time_ns() / scale;
- uint64_t stddev_ns = runner.standard_deviation_time_ns() / scale;
- std::cout << " (min " << min_ns << " " << unit << ", median " << med_ns << " " << unit << ", std dev " << stddev_ns << " " << unit << ")";
+ uint64_t mins = min / scale;
+ uint64_t maxs = max / scale;
+ uint64_t meds = med / scale;
+ uint64_t p95s = quantiles[9] / scale;
+ uint64_t stddevs = stddev / scale;
+ std::string cmp;
+ if (!prev_instances.empty())
+ {
+ const TimingsDatabase::instance &prev_instance = prev_instances.back();
+ if (!runner.is_same_distribution(prev_instance.npoints, prev_instance.mean, prev_instance.stddev))
+ {
+ double pc = fabs(100. * (prev_instance.mean - runner.get_mean()) / prev_instance.mean);
+ cmp = ", " + std::to_string(pc) + "% " + (mean > prev_instance.mean ? "slower" : "faster");
+ }
+cmp += " -- " + std::to_string(prev_instance.mean);
+ }
+ std::cout << " (min " << mins << " " << unit << ", 90th " << p95s << " " << unit << ", median " << meds << " " << unit << ", std dev " << stddevs << " " << unit << ")" << cmp;
}
std::cout << std::endl;
}
generated by cgit v1.2.3 (git 2.25.1) at 2024-11-15 14:33:53 +0000