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authorMartin Ankerl <martin.ankerl@gmail.com>2021-05-27 07:29:48 +0200
committerMartin Ankerl <martin.ankerl@gmail.com>2021-06-01 12:00:00 +0200
commite3c866e3ca85f841671a828712e6207e24d0d996 (patch)
treec14623b35023df369ce1256a2fac1ff4f9972a49 /src/bench
parentc91589dc2defdf0e193c2ebe383337c4008c47b5 (diff)
test: update nanobench from release 4.0.0 to 4.3.4
This updates the third-party library nanobench with the latest release. It contains mostly minor bugfixes, a new pyperf output format, ability to suppress warnings with environment variable `NANOBENCH_SUPPRESS_WARNINGS`. Full changelog: v4.0.2 * Changed `doNotOptimizeAway` to what google benchmark is doing. The old code did not work on some machines. * fix: display correct "total" value * minor Documentation updates v4.1.0 * Updated link to new pyperf home * Adds ability to configure console output time unit * Add support for environment variable `NANOBENCH_SUPPRESS_WARNINGS` * Nanobench is now usable with CMake's FetchContent (see documentation: https://nanobench.ankerl.com/tutorial.html#cmake-integration) v4.2.0 * Ability to store and later compare results added, through `pyperf`. * See https://nanobench.ankerl.com/tutorial.html#pyperf-python-pyperf-module-output * Added lots of build targets to travis, similar to bitcoin's build. * Some minor API & documentation improvements v4.3.0 * `ankerl::nanobench::Rng` can now return the state with `std::vector<uint64_t> Rng::state()`, and this can also be used to initialize the Rng. v4.3.1 * Minor cmake improvements when integrationg as a third-party library: add alias `nanobench::nanobench`, default to C++17 v4.3.2 * Fixed a MSVC 2015 build problem * updates license to 2021. * build should now work with very old linux headers * Also disable UBSAN (bitcoin needed to add a suppression) v4.3.3 * Do not use locale-dependent `std::to_string` v4.3.4 * Add missing sanitizer suppression to `rotl`
Diffstat (limited to 'src/bench')
-rw-r--r--src/bench/nanobench.h239
1 files changed, 187 insertions, 52 deletions
diff --git a/src/bench/nanobench.h b/src/bench/nanobench.h
index c5379e7fd4..030d6ebf6a 100644
--- a/src/bench/nanobench.h
+++ b/src/bench/nanobench.h
@@ -7,7 +7,7 @@
//
// Licensed under the MIT License <http://opensource.org/licenses/MIT>.
// SPDX-License-Identifier: MIT
-// Copyright (c) 2019-2020 Martin Ankerl <martin.ankerl@gmail.com>
+// Copyright (c) 2019-2021 Martin Ankerl <martin.ankerl@gmail.com>
//
// Permission is hereby granted, free of charge, to any person obtaining a copy
// of this software and associated documentation files (the "Software"), to deal
@@ -32,8 +32,8 @@
// see https://semver.org/
#define ANKERL_NANOBENCH_VERSION_MAJOR 4 // incompatible API changes
-#define ANKERL_NANOBENCH_VERSION_MINOR 0 // backwards-compatible changes
-#define ANKERL_NANOBENCH_VERSION_PATCH 0 // backwards-compatible bug fixes
+#define ANKERL_NANOBENCH_VERSION_MINOR 3 // backwards-compatible changes
+#define ANKERL_NANOBENCH_VERSION_PATCH 4 // backwards-compatible bug fixes
///////////////////////////////////////////////////////////////////////////////////////////////////
// public facing api - as minimal as possible
@@ -78,12 +78,20 @@
#if defined(ANKERL_NANOBENCH_LOG_ENABLED)
# include <iostream>
-# define ANKERL_NANOBENCH_LOG(x) std::cout << __FUNCTION__ << "@" << __LINE__ << ": " << x << std::endl
+# define ANKERL_NANOBENCH_LOG(x) \
+ do { \
+ std::cout << __FUNCTION__ << "@" << __LINE__ << ": " << x << std::endl; \
+ } while (0)
#else
-# define ANKERL_NANOBENCH_LOG(x)
+# define ANKERL_NANOBENCH_LOG(x) \
+ do { \
+ } while (0)
#endif
-#if defined(__linux__) && !defined(ANKERL_NANOBENCH_DISABLE_PERF_COUNTERS)
+#if defined(__linux__) && defined(PERF_EVENT_IOC_ID) && defined(PERF_COUNT_HW_REF_CPU_CYCLES) && defined(PERF_FLAG_FD_CLOEXEC) && \
+ !defined(ANKERL_NANOBENCH_DISABLE_PERF_COUNTERS)
+// only enable perf counters on kernel 3.14 which seems to have all the necessary defines. The three PERF_... defines are not in
+// kernel 2.6.32 (all others are).
# define ANKERL_NANOBENCH_PRIVATE_PERF_COUNTERS() 1
#else
# define ANKERL_NANOBENCH_PRIVATE_PERF_COUNTERS() 0
@@ -173,7 +181,7 @@ class BigO;
* `contextswitches`, `instructions`, `branchinstructions`, and `branchmisses`. All the measuers (except `iterations`) are
* provided for a single iteration (so `elapsed` is the time a single iteration took). The following tags are available:
*
- * * `{{median(<name>>)}}` Calculate median of a measurement data set, e.g. `{{median(elapsed)}}`.
+ * * `{{median(<name>)}}` Calculate median of a measurement data set, e.g. `{{median(elapsed)}}`.
*
* * `{{average(<name>)}}` Average (mean) calculation.
*
@@ -181,10 +189,11 @@ class BigO;
* metric for the variation of measurements. It is more robust to outliers than the
* [Mean absolute percentage error (M-APE)](https://en.wikipedia.org/wiki/Mean_absolute_percentage_error).
* @f[
- * \mathrm{medianAbsolutePercentError}(e) = \mathrm{median}\{| \frac{e_i - \mathrm{median}\{e\}}{e_i}| \}
+ * \mathrm{MdAPE}(e) = \mathrm{med}\{| \frac{e_i - \mathrm{med}\{e\}}{e_i}| \}
* @f]
- * E.g. for *elapsed*: First, @f$ \mathrm{median}\{elapsed\} @f$ is calculated. This is used to calculate the absolute percentage
- * error to this median for each measurement, as in @f$ | \frac{e_i - \mathrm{median}\{e\}}{e_i}| @f$. All these results
+ * E.g. for *elapsed*: First, @f$ \mathrm{med}\{e\} @f$ calculates the median by sorting and then taking the middle element
+ * of all *elapsed* measurements. This is used to calculate the absolute percentage
+ * error to this median for each measurement, as in @f$ | \frac{e_i - \mathrm{med}\{e\}}{e_i}| @f$. All these results
* are sorted, and the middle value is chosen as the median absolute percent error.
*
* This measurement is a bit hard to interpret, but it is very robust against outliers. E.g. a value of 5% means that half of the
@@ -207,7 +216,7 @@ class BigO;
*
* * `{{#measurement}}` To access individual measurement results, open the begin tag for measurements.
*
- * * `{{elapsed}}` Average elapsed time per iteration, in seconds.
+ * * `{{elapsed}}` Average elapsed wall clock time per iteration, in seconds.
*
* * `{{iterations}}` Number of iterations in the measurement. The number of iterations will fluctuate due
* to some applied randomness, to enhance accuracy.
@@ -261,6 +270,7 @@ class BigO;
* :cpp:func:`templates::csv() <ankerl::nanobench::templates::csv()>`
* :cpp:func:`templates::json() <ankerl::nanobench::templates::json()>`
* :cpp:func:`templates::htmlBoxplot() <ankerl::nanobench::templates::htmlBoxplot()>`
+ * :cpp:func:`templates::pyperf() <ankerl::nanobench::templates::pyperf()>`
@endverbatim
*
@@ -269,6 +279,7 @@ class BigO;
* @param out Output for the generated output.
*/
void render(char const* mustacheTemplate, Bench const& bench, std::ostream& out);
+void render(std::string const& mustacheTemplate, Bench const& bench, std::ostream& out);
/**
* Same as render(char const* mustacheTemplate, Bench const& bench, std::ostream& out), but for when
@@ -279,6 +290,7 @@ void render(char const* mustacheTemplate, Bench const& bench, std::ostream& out)
* @param out Output for the generated output.
*/
void render(char const* mustacheTemplate, std::vector<Result> const& results, std::ostream& out);
+void render(std::string const& mustacheTemplate, std::vector<Result> const& results, std::ostream& out);
// Contains mustache-like templates
namespace templates {
@@ -297,7 +309,7 @@ char const* csv() noexcept;
/*!
@brief HTML output that uses plotly to generate an interactive boxplot chart. See the tutorial for an example output.
- The output uses only the elapsed time, and displays each epoch as a single dot.
+ The output uses only the elapsed wall clock time, and displays each epoch as a single dot.
@verbatim embed:rst
See the tutorial at :ref:`tutorial-template-html` for an example.
@endverbatim
@@ -307,6 +319,14 @@ char const* csv() noexcept;
char const* htmlBoxplot() noexcept;
/*!
+ @brief Output in pyperf compatible JSON format, which can be used for more analyzations.
+ @verbatim embed:rst
+ See the tutorial at :ref:`tutorial-template-pyperf` for an example how to further analyze the output.
+ @endverbatim
+ */
+char const* pyperf() noexcept;
+
+/*!
@brief Template to generate JSON data.
The generated JSON data contains *all* data that has been generated. All times are as double values, in seconds. The output can get
@@ -369,6 +389,8 @@ struct Config {
uint64_t mEpochIterations{0}; // If not 0, run *exactly* these number of iterations per epoch.
uint64_t mWarmup = 0;
std::ostream* mOut = nullptr;
+ std::chrono::duration<double> mTimeUnit = std::chrono::nanoseconds{1};
+ std::string mTimeUnitName = "ns";
bool mShowPerformanceCounters = true;
bool mIsRelative = false;
@@ -504,6 +526,7 @@ public:
*/
explicit Rng(uint64_t seed) noexcept;
Rng(uint64_t x, uint64_t y) noexcept;
+ Rng(std::vector<uint64_t> const& data);
/**
* Creates a copy of the Rng, thus the copy provides exactly the same random sequence as the original.
@@ -558,6 +581,14 @@ public:
template <typename Container>
void shuffle(Container& container) noexcept;
+ /**
+ * Extracts the full state of the generator, e.g. for serialization. For this RNG this is just 2 values, but to stay API compatible
+ * with future implementations that potentially use more state, we use a vector.
+ *
+ * @return Vector containing the full state:
+ */
+ std::vector<uint64_t> state() const;
+
private:
static constexpr uint64_t rotl(uint64_t x, unsigned k) noexcept;
@@ -667,6 +698,19 @@ public:
ANKERL_NANOBENCH(NODISCARD) std::string const& unit() const noexcept;
/**
+ * @brief Sets the time unit to be used for the default output.
+ *
+ * Nanobench defaults to using ns (nanoseconds) as output in the markdown. For some benchmarks this is too coarse, so it is
+ * possible to configure this. E.g. use `timeUnit(1ms, "ms")` to show `ms/op` instead of `ns/op`.
+ *
+ * @param tu Time unit to display the results in, default is 1ns.
+ * @param tuName Name for the time unit, default is "ns"
+ */
+ Bench& timeUnit(std::chrono::duration<double> const& tu, std::string const& tuName);
+ ANKERL_NANOBENCH(NODISCARD) std::string const& timeUnitName() const noexcept;
+ ANKERL_NANOBENCH(NODISCARD) std::chrono::duration<double> const& timeUnit() const noexcept;
+
+ /**
* @brief Set the output stream where the resulting markdown table will be printed to.
*
* The default is `&std::cout`. You can disable all output by setting `nullptr`.
@@ -916,6 +960,7 @@ public:
@endverbatim
*/
Bench& render(char const* templateContent, std::ostream& os);
+ Bench& render(std::string const& templateContent, std::ostream& os);
Bench& config(Config const& benchmarkConfig);
ANKERL_NANOBENCH(NODISCARD) Config const& config() const noexcept;
@@ -945,23 +990,24 @@ void doNotOptimizeAway(T const& val);
#else
-// see folly's Benchmark.h
-template <typename T>
-constexpr bool doNotOptimizeNeedsIndirect() {
- using Decayed = typename std::decay<T>::type;
- return !ANKERL_NANOBENCH_IS_TRIVIALLY_COPYABLE(Decayed) || sizeof(Decayed) > sizeof(long) || std::is_pointer<Decayed>::value;
-}
-
+// These assembly magic is directly from what Google Benchmark is doing. I have previously used what facebook's folly was doing, but
+// this seemd to have compilation problems in some cases. Google Benchmark seemed to be the most well tested anyways.
+// see https://github.com/google/benchmark/blob/master/include/benchmark/benchmark.h#L307
template <typename T>
-typename std::enable_if<!doNotOptimizeNeedsIndirect<T>()>::type doNotOptimizeAway(T const& val) {
+void doNotOptimizeAway(T const& val) {
// NOLINTNEXTLINE(hicpp-no-assembler)
- asm volatile("" ::"r"(val));
+ asm volatile("" : : "r,m"(val) : "memory");
}
template <typename T>
-typename std::enable_if<doNotOptimizeNeedsIndirect<T>()>::type doNotOptimizeAway(T const& val) {
+void doNotOptimizeAway(T& val) {
+# if defined(__clang__)
+ // NOLINTNEXTLINE(hicpp-no-assembler)
+ asm volatile("" : "+r,m"(val) : : "memory");
+# else
// NOLINTNEXTLINE(hicpp-no-assembler)
- asm volatile("" ::"m"(val) : "memory");
+ asm volatile("" : "+m,r"(val) : : "memory");
+# endif
}
#endif
@@ -1067,7 +1113,7 @@ constexpr uint64_t(Rng::max)() {
return (std::numeric_limits<uint64_t>::max)();
}
-ANKERL_NANOBENCH_NO_SANITIZE("integer")
+ANKERL_NANOBENCH_NO_SANITIZE("integer", "undefined")
uint64_t Rng::operator()() noexcept {
auto x = mX;
@@ -1077,7 +1123,7 @@ uint64_t Rng::operator()() noexcept {
return x;
}
-ANKERL_NANOBENCH_NO_SANITIZE("integer")
+ANKERL_NANOBENCH_NO_SANITIZE("integer", "undefined")
uint32_t Rng::bounded(uint32_t range) noexcept {
uint64_t r32 = static_cast<uint32_t>(operator()());
auto multiresult = r32 * range;
@@ -1103,6 +1149,7 @@ void Rng::shuffle(Container& container) noexcept {
}
}
+ANKERL_NANOBENCH_NO_SANITIZE("integer", "undefined")
constexpr uint64_t Rng::rotl(uint64_t x, unsigned k) noexcept {
return (x << k) | (x >> (64U - k));
}
@@ -1306,6 +1353,30 @@ char const* htmlBoxplot() noexcept {
</html>)DELIM";
}
+char const* pyperf() noexcept {
+ return R"DELIM({
+ "benchmarks": [
+ {
+ "runs": [
+ {
+ "values": [
+{{#measurement}} {{elapsed}}{{^-last}},
+{{/last}}{{/measurement}}
+ ]
+ }
+ ]
+ }
+ ],
+ "metadata": {
+ "loops": {{sum(iterations)}},
+ "inner_loops": {{batch}},
+ "name": "{{title}}",
+ "unit": "second"
+ },
+ "version": "1.0"
+})DELIM";
+}
+
char const* json() noexcept {
return R"DELIM({
"results": [
@@ -1410,6 +1481,7 @@ static std::vector<Node> parseMustacheTemplate(char const** tpl) {
}
static bool generateFirstLast(Node const& n, size_t idx, size_t size, std::ostream& out) {
+ ANKERL_NANOBENCH_LOG("n.type=" << static_cast<int>(n.type));
bool matchFirst = n == "-first";
bool matchLast = n == "-last";
if (!matchFirst && !matchLast) {
@@ -1632,6 +1704,7 @@ namespace detail {
char const* getEnv(char const* name);
bool isEndlessRunning(std::string const& name);
+bool isWarningsEnabled();
template <typename T>
T parseFile(std::string const& filename);
@@ -1770,25 +1843,49 @@ void render(char const* mustacheTemplate, std::vector<Result> const& results, st
for (size_t i = 0; i < nbResults; ++i) {
generateResult(n.children, i, results, out);
}
+ } else if (n == "measurement") {
+ if (results.size() != 1) {
+ throw std::runtime_error(
+ "render: can only use section 'measurement' here if there is a single result, but there are " +
+ detail::fmt::to_s(results.size()));
+ }
+ // when we only have a single result, we can immediately go into its measurement.
+ auto const& r = results.front();
+ for (size_t i = 0; i < r.size(); ++i) {
+ generateResultMeasurement(n.children, i, r, out);
+ }
} else {
- throw std::runtime_error("unknown section '" + std::string(n.begin, n.end) + "'");
+ throw std::runtime_error("render: unknown section '" + std::string(n.begin, n.end) + "'");
}
break;
case templates::Node::Type::tag:
- // This just uses the last result's config.
- if (!generateConfigTag(n, results.back().config(), out)) {
- throw std::runtime_error("unknown tag '" + std::string(n.begin, n.end) + "'");
+ if (results.size() == 1) {
+ // result & config are both supported there
+ generateResultTag(n, results.front(), out);
+ } else {
+ // This just uses the last result's config.
+ if (!generateConfigTag(n, results.back().config(), out)) {
+ throw std::runtime_error("unknown tag '" + std::string(n.begin, n.end) + "'");
+ }
}
break;
}
}
}
+void render(std::string const& mustacheTemplate, std::vector<Result> const& results, std::ostream& out) {
+ render(mustacheTemplate.c_str(), results, out);
+}
+
void render(char const* mustacheTemplate, const Bench& bench, std::ostream& out) {
render(mustacheTemplate, bench.results(), out);
}
+void render(std::string const& mustacheTemplate, const Bench& bench, std::ostream& out) {
+ render(mustacheTemplate.c_str(), bench.results(), out);
+}
+
namespace detail {
PerformanceCounters& performanceCounters() {
@@ -1837,6 +1934,12 @@ bool isEndlessRunning(std::string const& name) {
return nullptr != endless && endless == name;
}
+// True when environment variable NANOBENCH_SUPPRESS_WARNINGS is either not set at all, or set to "0"
+bool isWarningsEnabled() {
+ auto suppression = getEnv("NANOBENCH_SUPPRESS_WARNINGS");
+ return nullptr == suppression || suppression == std::string("0");
+}
+
void gatherStabilityInformation(std::vector<std::string>& warnings, std::vector<std::string>& recommendations) {
warnings.clear();
recommendations.clear();
@@ -1889,13 +1992,13 @@ void gatherStabilityInformation(std::vector<std::string>& warnings, std::vector<
recommendations.emplace_back("Make sure you compile for Release");
}
if (recommendPyPerf) {
- recommendations.emplace_back("Use 'pyperf system tune' before benchmarking. See https://github.com/vstinner/pyperf");
+ recommendations.emplace_back("Use 'pyperf system tune' before benchmarking. See https://github.com/psf/pyperf");
}
}
void printStabilityInformationOnce(std::ostream* outStream) {
static bool shouldPrint = true;
- if (shouldPrint && outStream) {
+ if (shouldPrint && outStream && isWarningsEnabled()) {
auto& os = *outStream;
shouldPrint = false;
std::vector<std::string> warnings;
@@ -1923,16 +2026,7 @@ uint64_t& singletonHeaderHash() noexcept {
return sHeaderHash;
}
-ANKERL_NANOBENCH_NO_SANITIZE("integer")
-inline uint64_t fnv1a(std::string const& str) noexcept {
- auto val = UINT64_C(14695981039346656037);
- for (auto c : str) {
- val = (val ^ static_cast<uint8_t>(c)) * UINT64_C(1099511628211);
- }
- return val;
-}
-
-ANKERL_NANOBENCH_NO_SANITIZE("integer")
+ANKERL_NANOBENCH_NO_SANITIZE("integer", "undefined")
inline uint64_t hash_combine(uint64_t seed, uint64_t val) {
return seed ^ (val + UINT64_C(0x9e3779b9) + (seed << 6U) + (seed >> 2U));
}
@@ -2010,7 +2104,7 @@ struct IterationLogic::Impl {
return static_cast<uint64_t>(doubleNewIters + 0.5);
}
- ANKERL_NANOBENCH_NO_SANITIZE("integer") void upscale(std::chrono::nanoseconds elapsed) {
+ ANKERL_NANOBENCH_NO_SANITIZE("integer", "undefined") void upscale(std::chrono::nanoseconds elapsed) {
if (elapsed * 10 < mTargetRuntimePerEpoch) {
// we are far below the target runtime. Multiply iterations by 10 (with overflow check)
if (mNumIters * 10 < mNumIters) {
@@ -2108,7 +2202,8 @@ struct IterationLogic::Impl {
columns.emplace_back(14, 0, "complexityN", "", mBench.complexityN());
}
- columns.emplace_back(22, 2, "ns/" + mBench.unit(), "", 1e9 * rMedian / mBench.batch());
+ columns.emplace_back(22, 2, mBench.timeUnitName() + "/" + mBench.unit(), "",
+ rMedian / (mBench.timeUnit().count() * mBench.batch()));
columns.emplace_back(22, 2, mBench.unit() + "/s", "", rMedian <= 0.0 ? 0.0 : mBench.batch() / rMedian);
double rErrorMedian = mResult.medianAbsolutePercentError(Result::Measure::elapsed);
@@ -2140,16 +2235,19 @@ struct IterationLogic::Impl {
}
}
- columns.emplace_back(12, 2, "total", "", mResult.sum(Result::Measure::elapsed));
+ columns.emplace_back(12, 2, "total", "", mResult.sumProduct(Result::Measure::iterations, Result::Measure::elapsed));
// write everything
auto& os = *mBench.output();
+ // combine all elements that are relevant for printing the header
uint64_t hash = 0;
- hash = hash_combine(fnv1a(mBench.unit()), hash);
- hash = hash_combine(fnv1a(mBench.title()), hash);
- hash = hash_combine(mBench.relative(), hash);
- hash = hash_combine(mBench.performanceCounters(), hash);
+ hash = hash_combine(std::hash<std::string>{}(mBench.unit()), hash);
+ hash = hash_combine(std::hash<std::string>{}(mBench.title()), hash);
+ hash = hash_combine(std::hash<std::string>{}(mBench.timeUnitName()), hash);
+ hash = hash_combine(std::hash<double>{}(mBench.timeUnit().count()), hash);
+ hash = hash_combine(std::hash<bool>{}(mBench.relative()), hash);
+ hash = hash_combine(std::hash<bool>{}(mBench.performanceCounters()), hash);
if (hash != singletonHeaderHash()) {
singletonHeaderHash() = hash;
@@ -2177,7 +2275,7 @@ struct IterationLogic::Impl {
os << col.value();
}
os << "| ";
- auto showUnstable = rErrorMedian >= 0.05;
+ auto showUnstable = isWarningsEnabled() && rErrorMedian >= 0.05;
if (showUnstable) {
os << ":wavy_dash: ";
}
@@ -2305,7 +2403,7 @@ public:
}
template <typename Op>
- ANKERL_NANOBENCH_NO_SANITIZE("integer")
+ ANKERL_NANOBENCH_NO_SANITIZE("integer", "undefined")
void calibrate(Op&& op) {
// clear current calibration data,
for (auto& v : mCalibratedOverhead) {
@@ -2411,7 +2509,7 @@ bool LinuxPerformanceCounters::monitor(perf_hw_id hwId, LinuxPerformanceCounters
}
// overflow is ok, it's checked
-ANKERL_NANOBENCH_NO_SANITIZE("integer")
+ANKERL_NANOBENCH_NO_SANITIZE("integer", "undefined")
void LinuxPerformanceCounters::updateResults(uint64_t numIters) {
// clear old data
for (auto& id_value : mIdToTarget) {
@@ -2963,6 +3061,20 @@ std::string const& Bench::unit() const noexcept {
return mConfig.mUnit;
}
+Bench& Bench::timeUnit(std::chrono::duration<double> const& tu, std::string const& tuName) {
+ mConfig.mTimeUnit = tu;
+ mConfig.mTimeUnitName = tuName;
+ return *this;
+}
+
+std::string const& Bench::timeUnitName() const noexcept {
+ return mConfig.mTimeUnitName;
+}
+
+std::chrono::duration<double> const& Bench::timeUnit() const noexcept {
+ return mConfig.mTimeUnit;
+}
+
// If benchmarkTitle differs from currently set title, the stored results will be cleared.
Bench& Bench::title(const char* benchmarkTitle) {
if (benchmarkTitle != mConfig.mBenchmarkTitle) {
@@ -3083,6 +3195,11 @@ Bench& Bench::render(char const* templateContent, std::ostream& os) {
return *this;
}
+Bench& Bench::render(std::string const& templateContent, std::ostream& os) {
+ ::ankerl::nanobench::render(templateContent, *this, os);
+ return *this;
+}
+
std::vector<BigO> Bench::complexityBigO() const {
std::vector<BigO> bigOs;
auto rangeMeasure = BigO::collectRangeMeasure(mResults);
@@ -3119,7 +3236,7 @@ Rng::Rng()
} while (mX == 0 && mY == 0);
}
-ANKERL_NANOBENCH_NO_SANITIZE("integer")
+ANKERL_NANOBENCH_NO_SANITIZE("integer", "undefined")
uint64_t splitMix64(uint64_t& state) noexcept {
uint64_t z = (state += UINT64_C(0x9e3779b97f4a7c15));
z = (z ^ (z >> 30U)) * UINT64_C(0xbf58476d1ce4e5b9);
@@ -3145,6 +3262,24 @@ Rng Rng::copy() const noexcept {
return Rng{mX, mY};
}
+Rng::Rng(std::vector<uint64_t> const& data)
+ : mX(0)
+ , mY(0) {
+ if (data.size() != 2) {
+ throw std::runtime_error("ankerl::nanobench::Rng::Rng: needed exactly 2 entries in data, but got " +
+ detail::fmt::to_s(data.size()));
+ }
+ mX = data[0];
+ mY = data[1];
+}
+
+std::vector<uint64_t> Rng::state() const {
+ std::vector<uint64_t> data(2);
+ data[0] = mX;
+ data[1] = mY;
+ return data;
+}
+
BigO::RangeMeasure BigO::collectRangeMeasure(std::vector<Result> const& results) {
BigO::RangeMeasure rangeMeasure;
for (auto const& result : results) {