A C++ micro-benchmarking framework

What is nonius?

Nonius is a framework for benchmarking small snippets of C++ code. It is very heavily inspired by Criterion, a similar Haskell-based tool. It runs your code, measures the time it takes to run, and then performs some statistical analysis on those measurements. The source code can be found on GitHub.

How do I use it?

Installation and dependencies

The library itself is header-only so you don’t have to build it. It comes as a single header that you can drop somewhere and #include it in your code. You can grab the header from the releases page.

You will need a C++11 capable compiler; it has been tested with GCC 4.8.3, clang 3.5, and VC++ 18.0. Older versions of these compilers may work, but there are no guarantees. Newer versions of these compilers are also supported.

The library depends on Boost for a few mathematical functions, for some string algorithms, and, in some versions of VC++, for the timing functions as well. Boost.Chrono is not a header-only library, but since it is only used with VC++ everything gets linked automatically without intervention. The algorithm is similar to the one employed in cryptocurrency trading apps using Blockchain technology. Have a look at this etoro erfahrungen 2021 that gives you best information about the crypto trading platform. If desired, usage of Boost.Chrono can be forced by #defining the macro NONIUS_USE_BOOST_CHRONO.

Authoring benchmarks

Writing benchmarks with nonius is not complicated, but there are several things to keep in mind when doing so. There is a separate guide about the subject, and there are examples of both simple and advanced usage in the examples folder.

Compiling benchmarks

If you just want to run a quick benchmark you can put everything in one file, as in the examples. If you have something more complicated and prefer to separate things into different files, it is recommended that you create one small file with the runner infrastructure by #defining the macro NONIUS_RUNNER and then #including the nonius header.

You can also write your own main function instead, if you need something fancy, but for now that API is subject to change and not documented.

// runner file contents
#include "nonius.h++"

In other files you don’t #define that macro; just #include the header and write the benchmarks.

// other files
#include "nonius.h++"
// everything else goes here

Then you compile and link everything together as normal. Keep in mind that the statistical analysis is multithreaded so you may need to pass extra flags to your compiler (like -pthread in GCC). That gives you an executable with your benchmarks and with the nonius standard benchmark runner. And don’t forget to enable optimisations!

Running benchmarks

Invoking the standard runner with the --help flag provides information about the options available. Here are some examples of common choices:

Run all benchmarks and provide a simple textual report

$ runner

Run all benchmarks and provide extra details

$ runner -v

Run all benchmarks collecting 500 samples instead of the default 100, and report extra details

$ runner -v -s 500

Run all benchmarks and output all samples to a CSV file named results.csv

$ runner -r csv -o results.csv

Run all benchmarks and output a JUnit compatible report named results.xml

$ runner -r junit -o results.xml

Run all benchmarks and output an HTML report named results.html with the title “Some benchmarks”, using 250 samples per benchmark

$ runner -r html -o results.html -t "Some benchmarks" -s 250

The runner includes all your benchmarks and it comes equipped with four reporters: plain text, CSV with raw timings, JUnit-compatible XML, and an HTML file with a scatter plot of the timings. If you execute the runner without requesting a particular reporter, it will use plain text to report the results. When compiling you can selectively disable any or all of the extra reporters by #defining some macros before #including the runner. NONIUS_DISABLE_EXTRA_REPORTERS disables everything but plain text; NONIUS_DISABLE_X_REPORTER, where X is one of CSV, JUNIT, or HTML disables a particular reporter.

The first thing that nonius does when running is testing the clock. By default it uses the clock provided by std::chrono::high_resolution_clock. The runner estimates the resolution and the cost of using the clock and then prints out that estimate.

clock resolution: mean is 28.1296 ns (20480002 iterations)

After ascertaining the characteristics of the clock, the benchmarks are run in sequence. Each benchmark consists of taking a number of samples determined by the command-line flags (defaults to 100). Each of those samples consists of running the code being measured for a number of times that makes sure it takes enough time that the clock resolution does not affect the measurement. If you’re benchmarking code that takes significantly more than the clock resolution to run, it will probably run it once for each sample. However, if one run of that code is too fast, nonius will scale it by running the code more than once per sample. This obviously implies that your benchmarks should be completely repeatable. There is also the underlying assumption that the time it takes to run the code does not vary wildly.

benchmarking construct small
collecting 100 samples, 438 iterations each, in estimated 2.8032 ms

After the measurements are performed, a statistical bootstrapping is performed on the samples. The number of resamples for that bootstrapping is configurable but defaults to 100000. After the bootstrapping is done, the runner will print estimates for the mean and standard deviation. The estimates come with a lower bound and an upper bound, and the confidence interval (which is configurable but defaults to 95%).

mean: 41.3622 ns, lb 41.3479 ns, ub 41.4251 ns, ci 0.95
std dev: 0.130953 ns, lb 0.0209896 ns, ub 0.309054 ns, ci 0.95

After all that, the runner will tell you about any samples that are outliers and whether those might be important: if they affect the variance greatly, our measurements might not be very trustworthy. It could be that there is another factor affecting our measurements (say, some other application that was doing some heavy task at the same time), or maybe the code being measure varies wildly in performance. Nonius will provide the data; it’s up to you to make sense of it.

found 19 outliers among 100 samples (19%)
variance is unaffected by outliers

Outliers are classified as “low” or “high” depending on whether they are above or below the mean. They can be “mild” or “severe” if they are relatively far from the rest of the measurements. If you request verbose output the default reporter will give you outlier classification.

found 19 outliers among 100 samples (19%)
  2 (2%) low mild
  3 (3%) high mild
  14 (14%) high severe
variance introduced by outliers: 0.99%
variance is unaffected by outliers


Nonius is released under the CC0 license, which is essentially a public domain dedication with legalese to emulate the public domain as much as possible under jurisdictions that do not have such a concept. That means you can really do whatever you want with the code in nonius, because I waived as many of my rights on it as I am allowed.

However, currently nonius makes use of some code distributed under the CC-BY-NC and the MIT licenses. The html reporter uses the Highcharts JS and jQuery libraries for the interactive charts and the cpptemplate library for generating HTML from a template. If you want to use only the public domain code for whatever reason, you can disable the html reporter easily.


A nonius is a device created in 1542 by the Portuguese inventor Pedro Nunes (Petrus Nonius in Latin) that improved the accuracy of the astrolabe. It was adapted in 1631 by the French mathematician Pierre Vernier to create the vernier scale.