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Merge bitcoin/bitcoin#28877: bench: Update nanobench to 4.3.11
fe434a469534766f18d7560d968deed37193835f bench: Update nanobench to 4.3.11 (TheCharlatan) Pull request description: The newest version fixes the false positive `* Turbo is enabled, CPU frequency will fluctuate` warning on AMD CPUs. The file was directly taken from the release page: https://github.com/martinus/nanobench/releases/tag/v4.3.11. Other changes from the release notes: * Check for failures in parseFile(), perf events tweaks by tommi-cujo in https://github.com/martinus/nanobench/pull/84 * Workaround missing noexcept for std::string move assignment by tommi-cujo in https://github.com/martinus/nanobench/pull/87 * removed the link by martinus in https://github.com/martinus/nanobench/pull/89 * Lots of minor cleanups by martinus in https://github.com/martinus/nanobench/pull/85 * Add linter for version & clang-format. Updated version by martinus in https://github.com/martinus/nanobench/pull/90 ACKs for top commit: fanquake: ACK fe434a469534766f18d7560d968deed37193835f - have not tested. Tree-SHA512: a8f15e1db1d993673e4b295a3bab22e67ee3c9f3c0bcbef28974fe9ff37dbb741967a526088d5b148c8d25c9d57cd3b844238100c17b23038638787461805678
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@ -33,7 +33,7 @@
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// see https://semver.org/
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#define ANKERL_NANOBENCH_VERSION_MAJOR 4 // incompatible API changes
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#define ANKERL_NANOBENCH_VERSION_MINOR 3 // backwards-compatible changes
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#define ANKERL_NANOBENCH_VERSION_PATCH 10 // backwards-compatible bug fixes
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#define ANKERL_NANOBENCH_VERSION_PATCH 11 // backwards-compatible bug fixes
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///////////////////////////////////////////////////////////////////////////////////////////////////
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// public facing api - as minimal as possible
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@ -120,6 +120,10 @@
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# define ANKERL_NANOBENCH_IS_TRIVIALLY_COPYABLE(...) std::is_trivially_copyable<__VA_ARGS__>::value
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#endif
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// noexcept may be missing for std::string.
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// See https://gcc.gnu.org/bugzilla/show_bug.cgi?id=58265
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#define ANKERL_NANOBENCH_PRIVATE_NOEXCEPT_STRING_MOVE() std::is_nothrow_move_assignable<std::string>::value
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// declarations ///////////////////////////////////////////////////////////////////////////////////
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namespace ankerl {
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@ -404,7 +408,7 @@ struct Config {
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Config();
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~Config();
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Config& operator=(Config const& other);
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Config& operator=(Config&& other) noexcept;
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Config& operator=(Config&& other) noexcept(ANKERL_NANOBENCH(NOEXCEPT_STRING_MOVE));
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Config(Config const& other);
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Config(Config&& other) noexcept;
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};
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@ -430,7 +434,7 @@ public:
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~Result();
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Result& operator=(Result const& other);
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Result& operator=(Result&& other) noexcept;
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Result& operator=(Result&& other) noexcept(ANKERL_NANOBENCH(NOEXCEPT_STRING_MOVE));
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Result(Result const& other);
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Result(Result&& other) noexcept;
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@ -596,7 +600,7 @@ public:
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*
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* @return Vector containing the full state:
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*/
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std::vector<uint64_t> state() const;
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ANKERL_NANOBENCH(NODISCARD) std::vector<uint64_t> state() const;
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private:
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static constexpr uint64_t rotl(uint64_t x, unsigned k) noexcept;
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@ -628,7 +632,7 @@ public:
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Bench();
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Bench(Bench&& other) noexcept;
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Bench& operator=(Bench&& other) noexcept;
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Bench& operator=(Bench&& other) noexcept(ANKERL_NANOBENCH(NOEXCEPT_STRING_MOVE));
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Bench(Bench const& other);
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Bench& operator=(Bench const& other);
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~Bench() noexcept;
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@ -818,7 +822,7 @@ public:
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* Default is zero, so we are fully relying on clockResolutionMultiple(). In most cases this is exactly what you want. If you see
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* that the evaluation is unreliable with a high `err%`, you can increase either minEpochTime() or minEpochIterations().
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*
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* @see maxEpochTim), minEpochIterations
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* @see maxEpochTime, minEpochIterations
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*
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* @param t Minimum time each epoch should take.
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*/
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@ -1030,7 +1034,7 @@ void doNotOptimizeAway(T const& val);
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// These assembly magic is directly from what Google Benchmark is doing. I have previously used what facebook's folly was doing, but
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// this seemed to have compilation problems in some cases. Google Benchmark seemed to be the most well tested anyways.
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// see https://github.com/google/benchmark/blob/master/include/benchmark/benchmark.h#L307
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// see https://github.com/google/benchmark/blob/v1.7.1/include/benchmark/benchmark.h#L443-L446
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template <typename T>
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void doNotOptimizeAway(T const& val) {
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// NOLINTNEXTLINE(hicpp-no-assembler)
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@ -1781,7 +1785,7 @@ bool isEndlessRunning(std::string const& name);
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bool isWarningsEnabled();
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template <typename T>
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T parseFile(std::string const& filename);
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T parseFile(std::string const& filename, bool* fail);
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void gatherStabilityInformation(std::vector<std::string>& warnings, std::vector<std::string>& recommendations);
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void printStabilityInformationOnce(std::ostream* outStream);
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@ -1839,7 +1843,7 @@ class Number {
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public:
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Number(int width, int precision, double value);
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Number(int width, int precision, int64_t value);
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std::string to_s() const;
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ANKERL_NANOBENCH(NODISCARD) std::string to_s() const;
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private:
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friend std::ostream& operator<<(std::ostream& os, Number const& n);
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@ -1857,11 +1861,11 @@ std::ostream& operator<<(std::ostream& os, Number const& n);
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class MarkDownColumn {
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public:
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MarkDownColumn(int w, int prec, std::string tit, std::string suff, double val);
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std::string title() const;
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std::string separator() const;
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std::string invalid() const;
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std::string value() const;
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MarkDownColumn(int w, int prec, std::string tit, std::string suff, double val) noexcept;
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ANKERL_NANOBENCH(NODISCARD) std::string title() const;
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ANKERL_NANOBENCH(NODISCARD) std::string separator() const;
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ANKERL_NANOBENCH(NODISCARD) std::string invalid() const;
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ANKERL_NANOBENCH(NODISCARD) std::string value() const;
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private:
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int mWidth;
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@ -1976,9 +1980,9 @@ PerformanceCounters& performanceCounters() {
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}
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// Windows version of doNotOptimizeAway
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// see https://github.com/google/benchmark/blob/master/include/benchmark/benchmark.h#L307
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// see https://github.com/facebook/folly/blob/master/folly/Benchmark.h#L280
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// see https://docs.microsoft.com/en-us/cpp/preprocessor/optimize
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// see https://github.com/google/benchmark/blob/v1.7.1/include/benchmark/benchmark.h#L514
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// see https://github.com/facebook/folly/blob/v2023.01.30.00/folly/lang/Hint-inl.h#L54-L58
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// see https://learn.microsoft.com/en-us/cpp/preprocessor/optimize
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# if defined(_MSC_VER)
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# pragma optimize("", off)
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void doNotOptimizeAwaySink(void const*) {}
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@ -1986,10 +1990,13 @@ void doNotOptimizeAwaySink(void const*) {}
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# endif
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template <typename T>
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T parseFile(std::string const& filename) {
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T parseFile(std::string const& filename, bool* fail) {
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std::ifstream fin(filename); // NOLINT(misc-const-correctness)
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T num{};
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fin >> num;
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if (fail != nullptr) {
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*fail = fin.fail();
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}
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return num;
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}
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@ -2032,16 +2039,15 @@ void gatherStabilityInformation(std::vector<std::string>& warnings, std::vector<
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if (nprocs <= 0) {
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warnings.emplace_back("couldn't figure out number of processors - no governor, turbo check possible");
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} else {
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// check frequency scaling
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for (long id = 0; id < nprocs; ++id) {
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auto idStr = detail::fmt::to_s(static_cast<uint64_t>(id));
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auto sysCpu = "/sys/devices/system/cpu/cpu" + idStr;
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auto minFreq = parseFile<int64_t>(sysCpu + "/cpufreq/scaling_min_freq");
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auto maxFreq = parseFile<int64_t>(sysCpu + "/cpufreq/scaling_max_freq");
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auto minFreq = parseFile<int64_t>(sysCpu + "/cpufreq/scaling_min_freq", nullptr);
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auto maxFreq = parseFile<int64_t>(sysCpu + "/cpufreq/scaling_max_freq", nullptr);
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if (minFreq != maxFreq) {
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auto minMHz = static_cast<double>(minFreq) / 1000.0;
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auto maxMHz = static_cast<double>(maxFreq) / 1000.0;
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auto minMHz = d(minFreq) / 1000.0;
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auto maxMHz = d(maxFreq) / 1000.0;
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warnings.emplace_back("CPU frequency scaling enabled: CPU " + idStr + " between " +
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detail::fmt::Number(1, 1, minMHz).to_s() + " and " + detail::fmt::Number(1, 1, maxMHz).to_s() +
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" MHz");
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@ -2050,13 +2056,15 @@ void gatherStabilityInformation(std::vector<std::string>& warnings, std::vector<
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}
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}
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auto currentGovernor = parseFile<std::string>("/sys/devices/system/cpu/cpu0/cpufreq/scaling_governor");
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if ("performance" != currentGovernor) {
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auto fail = false;
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auto currentGovernor = parseFile<std::string>("/sys/devices/system/cpu/cpu0/cpufreq/scaling_governor", &fail);
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if (!fail && "performance" != currentGovernor) {
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warnings.emplace_back("CPU governor is '" + currentGovernor + "' but should be 'performance'");
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recommendPyPerf = true;
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}
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if (0 == parseFile<int>("/sys/devices/system/cpu/intel_pstate/no_turbo")) {
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auto noTurbo = parseFile<int>("/sys/devices/system/cpu/intel_pstate/no_turbo", &fail);
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if (!fail && noTurbo == 0) {
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warnings.emplace_back("Turbo is enabled, CPU frequency will fluctuate");
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recommendPyPerf = true;
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}
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@ -2250,10 +2258,9 @@ struct IterationLogic::Impl {
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mNumIters = 0;
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}
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ANKERL_NANOBENCH_LOG(mBench.name() << ": " << detail::fmt::Number(20, 3, static_cast<double>(elapsed.count())) << " elapsed, "
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<< detail::fmt::Number(20, 3, static_cast<double>(mTargetRuntimePerEpoch.count()))
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<< " target. oldIters=" << oldIters << ", mNumIters=" << mNumIters
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<< ", mState=" << static_cast<int>(mState));
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ANKERL_NANOBENCH_LOG(mBench.name() << ": " << detail::fmt::Number(20, 3, d(elapsed.count())) << " elapsed, "
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<< detail::fmt::Number(20, 3, d(mTargetRuntimePerEpoch.count())) << " target. oldIters="
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<< oldIters << ", mNumIters=" << mNumIters << ", mState=" << static_cast<int>(mState));
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}
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// NOLINTNEXTLINE(readability-function-cognitive-complexity)
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@ -2357,7 +2364,7 @@ struct IterationLogic::Impl {
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}
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os << fmt::MarkDownCode(mBench.name());
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if (showUnstable) {
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auto avgIters = static_cast<double>(mTotalNumIters) / static_cast<double>(mBench.epochs());
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auto avgIters = d(mTotalNumIters) / d(mBench.epochs());
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// NOLINTNEXTLINE(bugprone-incorrect-roundings)
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auto suggestedIters = static_cast<uint64_t>(avgIters * 10 + 0.5);
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@ -2435,7 +2442,7 @@ public:
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bool monitor(perf_sw_ids swId, Target target);
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bool monitor(perf_hw_id hwId, Target target);
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bool hasError() const noexcept {
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ANKERL_NANOBENCH(NODISCARD) bool hasError() const noexcept {
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return mHasError;
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}
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@ -2691,16 +2698,23 @@ PerformanceCounters::PerformanceCounters()
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, mVal()
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, mHas() {
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mHas.pageFaults = mPc->monitor(PERF_COUNT_SW_PAGE_FAULTS, LinuxPerformanceCounters::Target(&mVal.pageFaults, true, false));
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// HW events
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mHas.cpuCycles = mPc->monitor(PERF_COUNT_HW_REF_CPU_CYCLES, LinuxPerformanceCounters::Target(&mVal.cpuCycles, true, false));
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mHas.contextSwitches =
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mPc->monitor(PERF_COUNT_SW_CONTEXT_SWITCHES, LinuxPerformanceCounters::Target(&mVal.contextSwitches, true, false));
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if (!mHas.cpuCycles) {
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// Fallback to cycles counter, reference cycles not available in many systems.
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mHas.cpuCycles = mPc->monitor(PERF_COUNT_HW_CPU_CYCLES, LinuxPerformanceCounters::Target(&mVal.cpuCycles, true, false));
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}
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mHas.instructions = mPc->monitor(PERF_COUNT_HW_INSTRUCTIONS, LinuxPerformanceCounters::Target(&mVal.instructions, true, true));
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mHas.branchInstructions =
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mPc->monitor(PERF_COUNT_HW_BRANCH_INSTRUCTIONS, LinuxPerformanceCounters::Target(&mVal.branchInstructions, true, false));
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mHas.branchMisses = mPc->monitor(PERF_COUNT_HW_BRANCH_MISSES, LinuxPerformanceCounters::Target(&mVal.branchMisses, true, false));
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// mHas.branchMisses = false;
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// SW events
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mHas.pageFaults = mPc->monitor(PERF_COUNT_SW_PAGE_FAULTS, LinuxPerformanceCounters::Target(&mVal.pageFaults, true, false));
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mHas.contextSwitches =
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mPc->monitor(PERF_COUNT_SW_CONTEXT_SWITCHES, LinuxPerformanceCounters::Target(&mVal.contextSwitches, true, false));
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mPc->start();
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mPc->calibrate([] {
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auto before = ankerl::nanobench::Clock::now();
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@ -2789,7 +2803,7 @@ void StreamStateRestorer::restore() {
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Number::Number(int width, int precision, int64_t value)
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: mWidth(width)
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, mPrecision(precision)
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, mValue(static_cast<double>(value)) {}
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, mValue(d(value)) {}
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Number::Number(int width, int precision, double value)
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: mWidth(width)
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@ -2823,7 +2837,7 @@ std::ostream& operator<<(std::ostream& os, Number const& n) {
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return n.write(os);
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}
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MarkDownColumn::MarkDownColumn(int w, int prec, std::string tit, std::string suff, double val)
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MarkDownColumn::MarkDownColumn(int w, int prec, std::string tit, std::string suff, double val) noexcept
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: mWidth(w)
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, mPrecision(prec)
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, mTitle(std::move(tit))
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@ -2884,14 +2898,14 @@ std::ostream& operator<<(std::ostream& os, MarkDownCode const& mdCode) {
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Config::Config() = default;
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Config::~Config() = default;
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Config& Config::operator=(Config const&) = default;
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Config& Config::operator=(Config&&) noexcept = default;
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Config& Config::operator=(Config&&) noexcept(ANKERL_NANOBENCH(NOEXCEPT_STRING_MOVE)) = default;
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Config::Config(Config const&) = default;
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Config::Config(Config&&) noexcept = default;
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// provide implementation here so it's only generated once
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Result::~Result() = default;
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Result& Result::operator=(Result const&) = default;
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Result& Result::operator=(Result&&) noexcept = default;
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Result& Result::operator=(Result&&) noexcept(ANKERL_NANOBENCH(NOEXCEPT_STRING_MOVE)) = default;
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Result::Result(Result const&) = default;
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Result::Result(Result&&) noexcept = default;
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@ -2992,7 +3006,7 @@ double Result::medianAbsolutePercentError(Measure m) const {
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auto data = mNameToMeasurements[detail::u(m)];
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// calculates MdAPE which is the median of percentage error
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// see https://www.spiderfinancial.com/support/documentation/numxl/reference-manual/forecasting-performance/mdape
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// see https://support.numxl.com/hc/en-us/articles/115001223503-MdAPE-Median-Absolute-Percentage-Error
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auto med = calcMedian(data);
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// transform the data to absolute error
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@ -3106,7 +3120,7 @@ Bench::Bench() {
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}
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Bench::Bench(Bench&&) noexcept = default;
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Bench& Bench::operator=(Bench&&) noexcept = default;
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Bench& Bench::operator=(Bench&&) noexcept(ANKERL_NANOBENCH(NOEXCEPT_STRING_MOVE)) = default;
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Bench::Bench(Bench const&) = default;
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Bench& Bench::operator=(Bench const&) = default;
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Bench::~Bench() noexcept = default;
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@ -3423,7 +3437,7 @@ BigO::BigO(std::string bigOName, RangeMeasure const& rangeMeasure)
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sumMeasure += rm.second;
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}
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auto n = static_cast<double>(rangeMeasure.size());
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auto n = detail::d(rangeMeasure.size());
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auto mean = sumMeasure / n;
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mNormalizedRootMeanSquare = std::sqrt(err / n) / mean;
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}
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