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36 KiB
# benchmark
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[](https://travis-ci.org/google/benchmark)
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[](https://ci.appveyor.com/project/google/benchmark/branch/master)
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[](https://coveralls.io/r/google/benchmark)
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[](https://slackin-iqtfqnpzxd.now.sh/)
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A library to support the benchmarking of functions, similar to unit-tests.
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[Discussion group](https://groups.google.com/d/forum/benchmark-discuss)
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IRC channel: [freenode](https://freenode.net) #googlebenchmark
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[Additional Tooling Documentation](docs/tools.md)
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[Assembly Testing Documentation](docs/AssemblyTests.md)
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## Building
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The basic steps for configuring and building the library look like this:
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```bash
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$ git clone https://github.com/google/benchmark.git
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# Benchmark requires Google Test as a dependency. Add the source tree as a subdirectory.
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$ git clone https://github.com/google/googletest.git benchmark/googletest
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$ mkdir build && cd build
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$ cmake -G <generator> [options] ../benchmark
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# Assuming a makefile generator was used
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$ make
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```
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Note that Google Benchmark requires Google Test to build and run the tests. This
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dependency can be provided two ways:
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* Checkout the Google Test sources into `benchmark/googletest` as above.
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* Otherwise, if `-DBENCHMARK_DOWNLOAD_DEPENDENCIES=ON` is specified during
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configuration, the library will automatically download and build any required
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dependencies.
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If you do not wish to build and run the tests, add `-DBENCHMARK_ENABLE_GTEST_TESTS=OFF`
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to `CMAKE_ARGS`.
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## Installation Guide
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For Ubuntu and Debian Based System
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First make sure you have git and cmake installed (If not please install them)
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```
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sudo apt-get install git cmake
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```
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Now, let's clone the repository and build it
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```
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git clone https://github.com/google/benchmark.git
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cd benchmark
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# If you want to build tests and don't use BENCHMARK_DOWNLOAD_DEPENDENCIES, then
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# git clone https://github.com/google/googletest.git
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mkdir build
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cd build
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cmake .. -DCMAKE_BUILD_TYPE=RELEASE
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make
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```
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If you need to install the library globally
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```
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sudo make install
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```
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## Stable and Experimental Library Versions
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The main branch contains the latest stable version of the benchmarking library;
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the API of which can be considered largely stable, with source breaking changes
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being made only upon the release of a new major version.
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Newer, experimental, features are implemented and tested on the
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[`v2` branch](https://github.com/google/benchmark/tree/v2). Users who wish
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to use, test, and provide feedback on the new features are encouraged to try
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this branch. However, this branch provides no stability guarantees and reserves
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the right to change and break the API at any time.
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## Further knowledge
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It may help to read the [Google Test documentation](https://github.com/google/googletest/blob/master/googletest/docs/primer.md)
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as some of the structural aspects of the APIs are similar.
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## Example usage
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### Basic usage
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Define a function that executes the code to be measured, register it as a
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benchmark function using the `BENCHMARK` macro, and ensure an appropriate `main`
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function is available:
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```c++
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#include <benchmark/benchmark.h>
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static void BM_StringCreation(benchmark::State& state) {
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for (auto _ : state)
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std::string empty_string;
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}
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// Register the function as a benchmark
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BENCHMARK(BM_StringCreation);
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// Define another benchmark
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static void BM_StringCopy(benchmark::State& state) {
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std::string x = "hello";
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for (auto _ : state)
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std::string copy(x);
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}
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BENCHMARK(BM_StringCopy);
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BENCHMARK_MAIN();
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```
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Don't forget to inform your linker to add benchmark library e.g. through
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`-lbenchmark` compilation flag. Alternatively, you may leave out the
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`BENCHMARK_MAIN();` at the end of the source file and link against
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`-lbenchmark_main` to get the same default behavior.
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The benchmark library will measure and report the timing for code within the
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`for(...)` loop.
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#### Platform-specific libraries
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When the library is built using GCC it is necessary to link with the pthread
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library due to how GCC implements `std::thread`. Failing to link to pthread will
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lead to runtime exceptions (unless you're using libc++), not linker errors. See
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[issue #67](https://github.com/google/benchmark/issues/67) for more details. You
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can link to pthread by adding `-pthread` to your linker command. Note, you can
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also use `-lpthread`, but there are potential issues with ordering of command
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line parameters if you use that.
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If you're running benchmarks on Windows, the shlwapi library (`-lshlwapi`) is
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also required.
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If you're running benchmarks on solaris, you'll want the kstat library linked in
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too (`-lkstat`).
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### Passing arguments
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Sometimes a family of benchmarks can be implemented with just one routine that
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takes an extra argument to specify which one of the family of benchmarks to
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run. For example, the following code defines a family of benchmarks for
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measuring the speed of `memcpy()` calls of different lengths:
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```c++
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static void BM_memcpy(benchmark::State& state) {
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char* src = new char[state.range(0)];
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char* dst = new char[state.range(0)];
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memset(src, 'x', state.range(0));
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for (auto _ : state)
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memcpy(dst, src, state.range(0));
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state.SetBytesProcessed(int64_t(state.iterations()) *
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int64_t(state.range(0)));
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delete[] src;
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delete[] dst;
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}
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BENCHMARK(BM_memcpy)->Arg(8)->Arg(64)->Arg(512)->Arg(1<<10)->Arg(8<<10);
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```
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The preceding code is quite repetitive, and can be replaced with the following
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short-hand. The following invocation will pick a few appropriate arguments in
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the specified range and will generate a benchmark for each such argument.
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```c++
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BENCHMARK(BM_memcpy)->Range(8, 8<<10);
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```
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By default the arguments in the range are generated in multiples of eight and
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the command above selects [ 8, 64, 512, 4k, 8k ]. In the following code the
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range multiplier is changed to multiples of two.
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```c++
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BENCHMARK(BM_memcpy)->RangeMultiplier(2)->Range(8, 8<<10);
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```
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Now arguments generated are [ 8, 16, 32, 64, 128, 256, 512, 1024, 2k, 4k, 8k ].
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You might have a benchmark that depends on two or more inputs. For example, the
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following code defines a family of benchmarks for measuring the speed of set
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insertion.
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```c++
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static void BM_SetInsert(benchmark::State& state) {
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std::set<int> data;
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for (auto _ : state) {
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state.PauseTiming();
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data = ConstructRandomSet(state.range(0));
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state.ResumeTiming();
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for (int j = 0; j < state.range(1); ++j)
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data.insert(RandomNumber());
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}
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}
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BENCHMARK(BM_SetInsert)
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->Args({1<<10, 128})
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->Args({2<<10, 128})
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->Args({4<<10, 128})
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->Args({8<<10, 128})
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->Args({1<<10, 512})
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->Args({2<<10, 512})
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->Args({4<<10, 512})
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->Args({8<<10, 512});
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```
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The preceding code is quite repetitive, and can be replaced with the following
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short-hand. The following macro will pick a few appropriate arguments in the
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product of the two specified ranges and will generate a benchmark for each such
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pair.
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```c++
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BENCHMARK(BM_SetInsert)->Ranges({{1<<10, 8<<10}, {128, 512}});
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```
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For more complex patterns of inputs, passing a custom function to `Apply` allows
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programmatic specification of an arbitrary set of arguments on which to run the
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benchmark. The following example enumerates a dense range on one parameter,
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and a sparse range on the second.
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```c++
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static void CustomArguments(benchmark::internal::Benchmark* b) {
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for (int i = 0; i <= 10; ++i)
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for (int j = 32; j <= 1024*1024; j *= 8)
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b->Args({i, j});
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}
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BENCHMARK(BM_SetInsert)->Apply(CustomArguments);
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```
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### Calculate asymptotic complexity (Big O)
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Asymptotic complexity might be calculated for a family of benchmarks. The
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following code will calculate the coefficient for the high-order term in the
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running time and the normalized root-mean square error of string comparison.
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```c++
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static void BM_StringCompare(benchmark::State& state) {
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std::string s1(state.range(0), '-');
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std::string s2(state.range(0), '-');
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for (auto _ : state) {
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benchmark::DoNotOptimize(s1.compare(s2));
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}
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state.SetComplexityN(state.range(0));
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}
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BENCHMARK(BM_StringCompare)
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->RangeMultiplier(2)->Range(1<<10, 1<<18)->Complexity(benchmark::oN);
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```
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As shown in the following invocation, asymptotic complexity might also be
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calculated automatically.
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```c++
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BENCHMARK(BM_StringCompare)
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->RangeMultiplier(2)->Range(1<<10, 1<<18)->Complexity();
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```
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The following code will specify asymptotic complexity with a lambda function,
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that might be used to customize high-order term calculation.
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```c++
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BENCHMARK(BM_StringCompare)->RangeMultiplier(2)
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->Range(1<<10, 1<<18)->Complexity([](int64_t n)->double{return n; });
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```
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### Templated benchmarks
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Templated benchmarks work the same way: This example produces and consumes
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messages of size `sizeof(v)` `range_x` times. It also outputs throughput in the
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absence of multiprogramming.
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```c++
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template <class Q> void BM_Sequential(benchmark::State& state) {
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Q q;
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typename Q::value_type v;
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for (auto _ : state) {
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for (int i = state.range(0); i--; )
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q.push(v);
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for (int e = state.range(0); e--; )
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q.Wait(&v);
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}
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// actually messages, not bytes:
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state.SetBytesProcessed(
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static_cast<int64_t>(state.iterations())*state.range(0));
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}
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BENCHMARK_TEMPLATE(BM_Sequential, WaitQueue<int>)->Range(1<<0, 1<<10);
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```
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Three macros are provided for adding benchmark templates.
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```c++
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#ifdef BENCHMARK_HAS_CXX11
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#define BENCHMARK_TEMPLATE(func, ...) // Takes any number of parameters.
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#else // C++ < C++11
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#define BENCHMARK_TEMPLATE(func, arg1)
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#endif
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#define BENCHMARK_TEMPLATE1(func, arg1)
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#define BENCHMARK_TEMPLATE2(func, arg1, arg2)
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```
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### A Faster KeepRunning loop
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In C++11 mode, a ranged-based for loop should be used in preference to
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the `KeepRunning` loop for running the benchmarks. For example:
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```c++
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static void BM_Fast(benchmark::State &state) {
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for (auto _ : state) {
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FastOperation();
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}
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}
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BENCHMARK(BM_Fast);
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```
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The reason the ranged-for loop is faster than using `KeepRunning`, is
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because `KeepRunning` requires a memory load and store of the iteration count
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ever iteration, whereas the ranged-for variant is able to keep the iteration count
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in a register.
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For example, an empty inner loop of using the ranged-based for method looks like:
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```asm
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# Loop Init
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mov rbx, qword ptr [r14 + 104]
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call benchmark::State::StartKeepRunning()
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test rbx, rbx
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je .LoopEnd
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.LoopHeader: # =>This Inner Loop Header: Depth=1
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add rbx, -1
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jne .LoopHeader
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.LoopEnd:
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```
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Compared to an empty `KeepRunning` loop, which looks like:
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```asm
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.LoopHeader: # in Loop: Header=BB0_3 Depth=1
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cmp byte ptr [rbx], 1
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jne .LoopInit
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.LoopBody: # =>This Inner Loop Header: Depth=1
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mov rax, qword ptr [rbx + 8]
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lea rcx, [rax + 1]
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mov qword ptr [rbx + 8], rcx
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cmp rax, qword ptr [rbx + 104]
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jb .LoopHeader
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jmp .LoopEnd
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.LoopInit:
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mov rdi, rbx
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call benchmark::State::StartKeepRunning()
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jmp .LoopBody
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.LoopEnd:
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```
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Unless C++03 compatibility is required, the ranged-for variant of writing
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the benchmark loop should be preferred.
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## Passing arbitrary arguments to a benchmark
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In C++11 it is possible to define a benchmark that takes an arbitrary number
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of extra arguments. The `BENCHMARK_CAPTURE(func, test_case_name, ...args)`
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macro creates a benchmark that invokes `func` with the `benchmark::State` as
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the first argument followed by the specified `args...`.
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The `test_case_name` is appended to the name of the benchmark and
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should describe the values passed.
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```c++
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template <class ...ExtraArgs>
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void BM_takes_args(benchmark::State& state, ExtraArgs&&... extra_args) {
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[...]
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}
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// Registers a benchmark named "BM_takes_args/int_string_test" that passes
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// the specified values to `extra_args`.
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BENCHMARK_CAPTURE(BM_takes_args, int_string_test, 42, std::string("abc"));
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```
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Note that elements of `...args` may refer to global variables. Users should
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avoid modifying global state inside of a benchmark.
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## Using RegisterBenchmark(name, fn, args...)
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The `RegisterBenchmark(name, func, args...)` function provides an alternative
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way to create and register benchmarks.
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`RegisterBenchmark(name, func, args...)` creates, registers, and returns a
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pointer to a new benchmark with the specified `name` that invokes
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`func(st, args...)` where `st` is a `benchmark::State` object.
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Unlike the `BENCHMARK` registration macros, which can only be used at the global
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scope, the `RegisterBenchmark` can be called anywhere. This allows for
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benchmark tests to be registered programmatically.
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Additionally `RegisterBenchmark` allows any callable object to be registered
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as a benchmark. Including capturing lambdas and function objects.
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For Example:
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```c++
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auto BM_test = [](benchmark::State& st, auto Inputs) { /* ... */ };
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int main(int argc, char** argv) {
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for (auto& test_input : { /* ... */ })
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benchmark::RegisterBenchmark(test_input.name(), BM_test, test_input);
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benchmark::Initialize(&argc, argv);
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benchmark::RunSpecifiedBenchmarks();
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}
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```
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### Multithreaded benchmarks
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In a multithreaded test (benchmark invoked by multiple threads simultaneously),
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it is guaranteed that none of the threads will start until all have reached
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the start of the benchmark loop, and all will have finished before any thread
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exits the benchmark loop. (This behavior is also provided by the `KeepRunning()`
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API) As such, any global setup or teardown can be wrapped in a check against the thread
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index:
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```c++
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static void BM_MultiThreaded(benchmark::State& state) {
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if (state.thread_index == 0) {
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// Setup code here.
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}
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for (auto _ : state) {
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// Run the test as normal.
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}
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if (state.thread_index == 0) {
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// Teardown code here.
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}
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}
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BENCHMARK(BM_MultiThreaded)->Threads(2);
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```
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If the benchmarked code itself uses threads and you want to compare it to
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single-threaded code, you may want to use real-time ("wallclock") measurements
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for latency comparisons:
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```c++
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BENCHMARK(BM_test)->Range(8, 8<<10)->UseRealTime();
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```
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Without `UseRealTime`, CPU time is used by default.
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## Controlling timers
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Normally, the entire duration of the work loop (`for (auto _ : state) {}`)
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is measured. But sometimes, it is nessesary to do some work inside of
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that loop, every iteration, but without counting that time to the benchmark time.
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That is possible, althought it is not recommended, since it has high overhead.
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```c++
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static void BM_SetInsert_With_Timer_Control(benchmark::State& state) {
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std::set<int> data;
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for (auto _ : state) {
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state.PauseTiming(); // Stop timers. They will not count until they are resumed.
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data = ConstructRandomSet(state.range(0)); // Do something that should not be measured
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state.ResumeTiming(); // And resume timers. They are now counting again.
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// The rest will be measured.
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for (int j = 0; j < state.range(1); ++j)
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data.insert(RandomNumber());
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}
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}
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BENCHMARK(BM_SetInsert_With_Timer_Control)->Ranges({{1<<10, 8<<10}, {128, 512}});
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```
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## Manual timing
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For benchmarking something for which neither CPU time nor real-time are
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correct or accurate enough, completely manual timing is supported using
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the `UseManualTime` function.
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When `UseManualTime` is used, the benchmarked code must call
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`SetIterationTime` once per iteration of the benchmark loop to
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report the manually measured time.
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An example use case for this is benchmarking GPU execution (e.g. OpenCL
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or CUDA kernels, OpenGL or Vulkan or Direct3D draw calls), which cannot
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be accurately measured using CPU time or real-time. Instead, they can be
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measured accurately using a dedicated API, and these measurement results
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can be reported back with `SetIterationTime`.
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```c++
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static void BM_ManualTiming(benchmark::State& state) {
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int microseconds = state.range(0);
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std::chrono::duration<double, std::micro> sleep_duration {
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static_cast<double>(microseconds)
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};
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for (auto _ : state) {
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auto start = std::chrono::high_resolution_clock::now();
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// Simulate some useful workload with a sleep
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std::this_thread::sleep_for(sleep_duration);
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auto end = std::chrono::high_resolution_clock::now();
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auto elapsed_seconds =
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std::chrono::duration_cast<std::chrono::duration<double>>(
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end - start);
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state.SetIterationTime(elapsed_seconds.count());
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}
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}
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BENCHMARK(BM_ManualTiming)->Range(1, 1<<17)->UseManualTime();
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```
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### Preventing optimisation
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To prevent a value or expression from being optimized away by the compiler
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the `benchmark::DoNotOptimize(...)` and `benchmark::ClobberMemory()`
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functions can be used.
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```c++
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static void BM_test(benchmark::State& state) {
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for (auto _ : state) {
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int x = 0;
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|
for (int i=0; i < 64; ++i) {
|
|
benchmark::DoNotOptimize(x += i);
|
|
}
|
|
}
|
|
}
|
|
```
|
|
|
|
`DoNotOptimize(<expr>)` forces the *result* of `<expr>` to be stored in either
|
|
memory or a register. For GNU based compilers it acts as read/write barrier
|
|
for global memory. More specifically it forces the compiler to flush pending
|
|
writes to memory and reload any other values as necessary.
|
|
|
|
Note that `DoNotOptimize(<expr>)` does not prevent optimizations on `<expr>`
|
|
in any way. `<expr>` may even be removed entirely when the result is already
|
|
known. For example:
|
|
|
|
```c++
|
|
/* Example 1: `<expr>` is removed entirely. */
|
|
int foo(int x) { return x + 42; }
|
|
while (...) DoNotOptimize(foo(0)); // Optimized to DoNotOptimize(42);
|
|
|
|
/* Example 2: Result of '<expr>' is only reused */
|
|
int bar(int) __attribute__((const));
|
|
while (...) DoNotOptimize(bar(0)); // Optimized to:
|
|
// int __result__ = bar(0);
|
|
// while (...) DoNotOptimize(__result__);
|
|
```
|
|
|
|
The second tool for preventing optimizations is `ClobberMemory()`. In essence
|
|
`ClobberMemory()` forces the compiler to perform all pending writes to global
|
|
memory. Memory managed by block scope objects must be "escaped" using
|
|
`DoNotOptimize(...)` before it can be clobbered. In the below example
|
|
`ClobberMemory()` prevents the call to `v.push_back(42)` from being optimized
|
|
away.
|
|
|
|
```c++
|
|
static void BM_vector_push_back(benchmark::State& state) {
|
|
for (auto _ : state) {
|
|
std::vector<int> v;
|
|
v.reserve(1);
|
|
benchmark::DoNotOptimize(v.data()); // Allow v.data() to be clobbered.
|
|
v.push_back(42);
|
|
benchmark::ClobberMemory(); // Force 42 to be written to memory.
|
|
}
|
|
}
|
|
```
|
|
|
|
Note that `ClobberMemory()` is only available for GNU or MSVC based compilers.
|
|
|
|
### Set time unit manually
|
|
If a benchmark runs a few milliseconds it may be hard to visually compare the
|
|
measured times, since the output data is given in nanoseconds per default. In
|
|
order to manually set the time unit, you can specify it manually:
|
|
|
|
```c++
|
|
BENCHMARK(BM_test)->Unit(benchmark::kMillisecond);
|
|
```
|
|
|
|
### Reporting the mean, median and standard deviation by repeated benchmarks
|
|
By default each benchmark is run once and that single result is reported.
|
|
However benchmarks are often noisy and a single result may not be representative
|
|
of the overall behavior. For this reason it's possible to repeatedly rerun the
|
|
benchmark.
|
|
|
|
The number of runs of each benchmark is specified globally by the
|
|
`--benchmark_repetitions` flag or on a per benchmark basis by calling
|
|
`Repetitions` on the registered benchmark object. When a benchmark is run more
|
|
than once the mean, median and standard deviation of the runs will be reported.
|
|
|
|
Additionally the `--benchmark_report_aggregates_only={true|false}`,
|
|
`--benchmark_display_aggregates_only={true|false}` flags or
|
|
`ReportAggregatesOnly(bool)`, `DisplayAggregatesOnly(bool)` functions can be
|
|
used to change how repeated tests are reported. By default the result of each
|
|
repeated run is reported. When `report aggregates only` option is `true`,
|
|
only the aggregates (i.e. mean, median and standard deviation, maybe complexity
|
|
measurements if they were requested) of the runs is reported, to both the
|
|
reporters - standard output (console), and the file.
|
|
However when only the `display aggregates only` option is `true`,
|
|
only the aggregates are displayed in the standard output, while the file
|
|
output still contains everything.
|
|
Calling `ReportAggregatesOnly(bool)` / `DisplayAggregatesOnly(bool)` on a
|
|
registered benchmark object overrides the value of the appropriate flag for that
|
|
benchmark.
|
|
|
|
## User-defined statistics for repeated benchmarks
|
|
While having mean, median and standard deviation is nice, this may not be
|
|
enough for everyone. For example you may want to know what is the largest
|
|
observation, e.g. because you have some real-time constraints. This is easy.
|
|
The following code will specify a custom statistic to be calculated, defined
|
|
by a lambda function.
|
|
|
|
```c++
|
|
void BM_spin_empty(benchmark::State& state) {
|
|
for (auto _ : state) {
|
|
for (int x = 0; x < state.range(0); ++x) {
|
|
benchmark::DoNotOptimize(x);
|
|
}
|
|
}
|
|
}
|
|
|
|
BENCHMARK(BM_spin_empty)
|
|
->ComputeStatistics("max", [](const std::vector<double>& v) -> double {
|
|
return *(std::max_element(std::begin(v), std::end(v)));
|
|
})
|
|
->Arg(512);
|
|
```
|
|
|
|
## Fixtures
|
|
Fixture tests are created by
|
|
first defining a type that derives from `::benchmark::Fixture` and then
|
|
creating/registering the tests using the following macros:
|
|
|
|
* `BENCHMARK_F(ClassName, Method)`
|
|
* `BENCHMARK_DEFINE_F(ClassName, Method)`
|
|
* `BENCHMARK_REGISTER_F(ClassName, Method)`
|
|
|
|
For Example:
|
|
|
|
```c++
|
|
class MyFixture : public benchmark::Fixture {};
|
|
|
|
BENCHMARK_F(MyFixture, FooTest)(benchmark::State& st) {
|
|
for (auto _ : st) {
|
|
...
|
|
}
|
|
}
|
|
|
|
BENCHMARK_DEFINE_F(MyFixture, BarTest)(benchmark::State& st) {
|
|
for (auto _ : st) {
|
|
...
|
|
}
|
|
}
|
|
/* BarTest is NOT registered */
|
|
BENCHMARK_REGISTER_F(MyFixture, BarTest)->Threads(2);
|
|
/* BarTest is now registered */
|
|
```
|
|
|
|
### Templated fixtures
|
|
Also you can create templated fixture by using the following macros:
|
|
|
|
* `BENCHMARK_TEMPLATE_F(ClassName, Method, ...)`
|
|
* `BENCHMARK_TEMPLATE_DEFINE_F(ClassName, Method, ...)`
|
|
|
|
For example:
|
|
```c++
|
|
template<typename T>
|
|
class MyFixture : public benchmark::Fixture {};
|
|
|
|
BENCHMARK_TEMPLATE_F(MyFixture, IntTest, int)(benchmark::State& st) {
|
|
for (auto _ : st) {
|
|
...
|
|
}
|
|
}
|
|
|
|
BENCHMARK_TEMPLATE_DEFINE_F(MyFixture, DoubleTest, double)(benchmark::State& st) {
|
|
for (auto _ : st) {
|
|
...
|
|
}
|
|
}
|
|
|
|
BENCHMARK_REGISTER_F(MyFixture, DoubleTest)->Threads(2);
|
|
```
|
|
|
|
## User-defined counters
|
|
|
|
You can add your own counters with user-defined names. The example below
|
|
will add columns "Foo", "Bar" and "Baz" in its output:
|
|
|
|
```c++
|
|
static void UserCountersExample1(benchmark::State& state) {
|
|
double numFoos = 0, numBars = 0, numBazs = 0;
|
|
for (auto _ : state) {
|
|
// ... count Foo,Bar,Baz events
|
|
}
|
|
state.counters["Foo"] = numFoos;
|
|
state.counters["Bar"] = numBars;
|
|
state.counters["Baz"] = numBazs;
|
|
}
|
|
```
|
|
|
|
The `state.counters` object is a `std::map` with `std::string` keys
|
|
and `Counter` values. The latter is a `double`-like class, via an implicit
|
|
conversion to `double&`. Thus you can use all of the standard arithmetic
|
|
assignment operators (`=,+=,-=,*=,/=`) to change the value of each counter.
|
|
|
|
In multithreaded benchmarks, each counter is set on the calling thread only.
|
|
When the benchmark finishes, the counters from each thread will be summed;
|
|
the resulting sum is the value which will be shown for the benchmark.
|
|
|
|
The `Counter` constructor accepts three parameters: the value as a `double`
|
|
; a bit flag which allows you to show counters as rates, and/or as per-thread
|
|
iteration, and/or as per-thread averages, and/or iteration invariants;
|
|
and a flag specifying the 'unit' - i.e. is 1k a 1000 (default,
|
|
`benchmark::Counter::OneK::kIs1000`), or 1024
|
|
(`benchmark::Counter::OneK::kIs1024`)?
|
|
|
|
```c++
|
|
// sets a simple counter
|
|
state.counters["Foo"] = numFoos;
|
|
|
|
// Set the counter as a rate. It will be presented divided
|
|
// by the duration of the benchmark.
|
|
state.counters["FooRate"] = Counter(numFoos, benchmark::Counter::kIsRate);
|
|
|
|
// Set the counter as a thread-average quantity. It will
|
|
// be presented divided by the number of threads.
|
|
state.counters["FooAvg"] = Counter(numFoos, benchmark::Counter::kAvgThreads);
|
|
|
|
// There's also a combined flag:
|
|
state.counters["FooAvgRate"] = Counter(numFoos,benchmark::Counter::kAvgThreadsRate);
|
|
|
|
// This says that we process with the rate of state.range(0) bytes every iteration:
|
|
state.counters["BytesProcessed"] = Counter(state.range(0), benchmark::Counter::kIsIterationInvariantRate, benchmark::Counter::OneK::kIs1024);
|
|
```
|
|
|
|
When you're compiling in C++11 mode or later you can use `insert()` with
|
|
`std::initializer_list`:
|
|
|
|
```c++
|
|
// With C++11, this can be done:
|
|
state.counters.insert({{"Foo", numFoos}, {"Bar", numBars}, {"Baz", numBazs}});
|
|
// ... instead of:
|
|
state.counters["Foo"] = numFoos;
|
|
state.counters["Bar"] = numBars;
|
|
state.counters["Baz"] = numBazs;
|
|
```
|
|
|
|
### Counter reporting
|
|
|
|
When using the console reporter, by default, user counters are are printed at
|
|
the end after the table, the same way as ``bytes_processed`` and
|
|
``items_processed``. This is best for cases in which there are few counters,
|
|
or where there are only a couple of lines per benchmark. Here's an example of
|
|
the default output:
|
|
|
|
```
|
|
------------------------------------------------------------------------------
|
|
Benchmark Time CPU Iterations UserCounters...
|
|
------------------------------------------------------------------------------
|
|
BM_UserCounter/threads:8 2248 ns 10277 ns 68808 Bar=16 Bat=40 Baz=24 Foo=8
|
|
BM_UserCounter/threads:1 9797 ns 9788 ns 71523 Bar=2 Bat=5 Baz=3 Foo=1024m
|
|
BM_UserCounter/threads:2 4924 ns 9842 ns 71036 Bar=4 Bat=10 Baz=6 Foo=2
|
|
BM_UserCounter/threads:4 2589 ns 10284 ns 68012 Bar=8 Bat=20 Baz=12 Foo=4
|
|
BM_UserCounter/threads:8 2212 ns 10287 ns 68040 Bar=16 Bat=40 Baz=24 Foo=8
|
|
BM_UserCounter/threads:16 1782 ns 10278 ns 68144 Bar=32 Bat=80 Baz=48 Foo=16
|
|
BM_UserCounter/threads:32 1291 ns 10296 ns 68256 Bar=64 Bat=160 Baz=96 Foo=32
|
|
BM_UserCounter/threads:4 2615 ns 10307 ns 68040 Bar=8 Bat=20 Baz=12 Foo=4
|
|
BM_Factorial 26 ns 26 ns 26608979 40320
|
|
BM_Factorial/real_time 26 ns 26 ns 26587936 40320
|
|
BM_CalculatePiRange/1 16 ns 16 ns 45704255 0
|
|
BM_CalculatePiRange/8 73 ns 73 ns 9520927 3.28374
|
|
BM_CalculatePiRange/64 609 ns 609 ns 1140647 3.15746
|
|
BM_CalculatePiRange/512 4900 ns 4901 ns 142696 3.14355
|
|
```
|
|
|
|
If this doesn't suit you, you can print each counter as a table column by
|
|
passing the flag `--benchmark_counters_tabular=true` to the benchmark
|
|
application. This is best for cases in which there are a lot of counters, or
|
|
a lot of lines per individual benchmark. Note that this will trigger a
|
|
reprinting of the table header any time the counter set changes between
|
|
individual benchmarks. Here's an example of corresponding output when
|
|
`--benchmark_counters_tabular=true` is passed:
|
|
|
|
```
|
|
---------------------------------------------------------------------------------------
|
|
Benchmark Time CPU Iterations Bar Bat Baz Foo
|
|
---------------------------------------------------------------------------------------
|
|
BM_UserCounter/threads:8 2198 ns 9953 ns 70688 16 40 24 8
|
|
BM_UserCounter/threads:1 9504 ns 9504 ns 73787 2 5 3 1
|
|
BM_UserCounter/threads:2 4775 ns 9550 ns 72606 4 10 6 2
|
|
BM_UserCounter/threads:4 2508 ns 9951 ns 70332 8 20 12 4
|
|
BM_UserCounter/threads:8 2055 ns 9933 ns 70344 16 40 24 8
|
|
BM_UserCounter/threads:16 1610 ns 9946 ns 70720 32 80 48 16
|
|
BM_UserCounter/threads:32 1192 ns 9948 ns 70496 64 160 96 32
|
|
BM_UserCounter/threads:4 2506 ns 9949 ns 70332 8 20 12 4
|
|
--------------------------------------------------------------
|
|
Benchmark Time CPU Iterations
|
|
--------------------------------------------------------------
|
|
BM_Factorial 26 ns 26 ns 26392245 40320
|
|
BM_Factorial/real_time 26 ns 26 ns 26494107 40320
|
|
BM_CalculatePiRange/1 15 ns 15 ns 45571597 0
|
|
BM_CalculatePiRange/8 74 ns 74 ns 9450212 3.28374
|
|
BM_CalculatePiRange/64 595 ns 595 ns 1173901 3.15746
|
|
BM_CalculatePiRange/512 4752 ns 4752 ns 147380 3.14355
|
|
BM_CalculatePiRange/4k 37970 ns 37972 ns 18453 3.14184
|
|
BM_CalculatePiRange/32k 303733 ns 303744 ns 2305 3.14162
|
|
BM_CalculatePiRange/256k 2434095 ns 2434186 ns 288 3.1416
|
|
BM_CalculatePiRange/1024k 9721140 ns 9721413 ns 71 3.14159
|
|
BM_CalculatePi/threads:8 2255 ns 9943 ns 70936
|
|
```
|
|
Note above the additional header printed when the benchmark changes from
|
|
``BM_UserCounter`` to ``BM_Factorial``. This is because ``BM_Factorial`` does
|
|
not have the same counter set as ``BM_UserCounter``.
|
|
|
|
## Exiting Benchmarks in Error
|
|
|
|
When errors caused by external influences, such as file I/O and network
|
|
communication, occur within a benchmark the
|
|
`State::SkipWithError(const char* msg)` function can be used to skip that run
|
|
of benchmark and report the error. Note that only future iterations of the
|
|
`KeepRunning()` are skipped. For the ranged-for version of the benchmark loop
|
|
Users must explicitly exit the loop, otherwise all iterations will be performed.
|
|
Users may explicitly return to exit the benchmark immediately.
|
|
|
|
The `SkipWithError(...)` function may be used at any point within the benchmark,
|
|
including before and after the benchmark loop.
|
|
|
|
For example:
|
|
|
|
```c++
|
|
static void BM_test(benchmark::State& state) {
|
|
auto resource = GetResource();
|
|
if (!resource.good()) {
|
|
state.SkipWithError("Resource is not good!");
|
|
// KeepRunning() loop will not be entered.
|
|
}
|
|
for (state.KeepRunning()) {
|
|
auto data = resource.read_data();
|
|
if (!resource.good()) {
|
|
state.SkipWithError("Failed to read data!");
|
|
break; // Needed to skip the rest of the iteration.
|
|
}
|
|
do_stuff(data);
|
|
}
|
|
}
|
|
|
|
static void BM_test_ranged_fo(benchmark::State & state) {
|
|
state.SkipWithError("test will not be entered");
|
|
for (auto _ : state) {
|
|
state.SkipWithError("Failed!");
|
|
break; // REQUIRED to prevent all further iterations.
|
|
}
|
|
}
|
|
```
|
|
|
|
## Running a subset of the benchmarks
|
|
|
|
The `--benchmark_filter=<regex>` option can be used to only run the benchmarks
|
|
which match the specified `<regex>`. For example:
|
|
|
|
```bash
|
|
$ ./run_benchmarks.x --benchmark_filter=BM_memcpy/32
|
|
Run on (1 X 2300 MHz CPU )
|
|
2016-06-25 19:34:24
|
|
Benchmark Time CPU Iterations
|
|
----------------------------------------------------
|
|
BM_memcpy/32 11 ns 11 ns 79545455
|
|
BM_memcpy/32k 2181 ns 2185 ns 324074
|
|
BM_memcpy/32 12 ns 12 ns 54687500
|
|
BM_memcpy/32k 1834 ns 1837 ns 357143
|
|
```
|
|
|
|
## Runtime and reporting considerations
|
|
When the benchmark binary is executed, each benchmark function is run serially.
|
|
The number of iterations to run is determined dynamically by running the
|
|
benchmark a few times and measuring the time taken and ensuring that the
|
|
ultimate result will be statistically stable. As such, faster benchmark
|
|
functions will be run for more iterations than slower benchmark functions, and
|
|
the number of iterations is thus reported.
|
|
|
|
In all cases, the number of iterations for which the benchmark is run is
|
|
governed by the amount of time the benchmark takes. Concretely, the number of
|
|
iterations is at least one, not more than 1e9, until CPU time is greater than
|
|
the minimum time, or the wallclock time is 5x minimum time. The minimum time is
|
|
set per benchmark by calling `MinTime` on the registered benchmark object.
|
|
|
|
Average timings are then reported over the iterations run. If multiple
|
|
repetitions are requested using the `--benchmark_repetitions` command-line
|
|
option, or at registration time, the benchmark function will be run several
|
|
times and statistical results across these repetitions will also be reported.
|
|
|
|
As well as the per-benchmark entries, a preamble in the report will include
|
|
information about the machine on which the benchmarks are run.
|
|
|
|
### Output Formats
|
|
The library supports multiple output formats. Use the
|
|
`--benchmark_format=<console|json|csv>` flag to set the format type. `console`
|
|
is the default format.
|
|
|
|
The Console format is intended to be a human readable format. By default
|
|
the format generates color output. Context is output on stderr and the
|
|
tabular data on stdout. Example tabular output looks like:
|
|
```
|
|
Benchmark Time(ns) CPU(ns) Iterations
|
|
----------------------------------------------------------------------
|
|
BM_SetInsert/1024/1 28928 29349 23853 133.097kB/s 33.2742k items/s
|
|
BM_SetInsert/1024/8 32065 32913 21375 949.487kB/s 237.372k items/s
|
|
BM_SetInsert/1024/10 33157 33648 21431 1.13369MB/s 290.225k items/s
|
|
```
|
|
|
|
The JSON format outputs human readable json split into two top level attributes.
|
|
The `context` attribute contains information about the run in general, including
|
|
information about the CPU and the date.
|
|
The `benchmarks` attribute contains a list of every benchmark run. Example json
|
|
output looks like:
|
|
```json
|
|
{
|
|
"context": {
|
|
"date": "2015/03/17-18:40:25",
|
|
"num_cpus": 40,
|
|
"mhz_per_cpu": 2801,
|
|
"cpu_scaling_enabled": false,
|
|
"build_type": "debug"
|
|
},
|
|
"benchmarks": [
|
|
{
|
|
"name": "BM_SetInsert/1024/1",
|
|
"iterations": 94877,
|
|
"real_time": 29275,
|
|
"cpu_time": 29836,
|
|
"bytes_per_second": 134066,
|
|
"items_per_second": 33516
|
|
},
|
|
{
|
|
"name": "BM_SetInsert/1024/8",
|
|
"iterations": 21609,
|
|
"real_time": 32317,
|
|
"cpu_time": 32429,
|
|
"bytes_per_second": 986770,
|
|
"items_per_second": 246693
|
|
},
|
|
{
|
|
"name": "BM_SetInsert/1024/10",
|
|
"iterations": 21393,
|
|
"real_time": 32724,
|
|
"cpu_time": 33355,
|
|
"bytes_per_second": 1199226,
|
|
"items_per_second": 299807
|
|
}
|
|
]
|
|
}
|
|
```
|
|
|
|
The CSV format outputs comma-separated values. The `context` is output on stderr
|
|
and the CSV itself on stdout. Example CSV output looks like:
|
|
```
|
|
name,iterations,real_time,cpu_time,bytes_per_second,items_per_second,label
|
|
"BM_SetInsert/1024/1",65465,17890.7,8407.45,475768,118942,
|
|
"BM_SetInsert/1024/8",116606,18810.1,9766.64,3.27646e+06,819115,
|
|
"BM_SetInsert/1024/10",106365,17238.4,8421.53,4.74973e+06,1.18743e+06,
|
|
```
|
|
|
|
### Output Files
|
|
The library supports writing the output of the benchmark to a file specified
|
|
by `--benchmark_out=<filename>`. The format of the output can be specified
|
|
using `--benchmark_out_format={json|console|csv}`. Specifying
|
|
`--benchmark_out` does not suppress the console output.
|
|
|
|
## Result comparison
|
|
|
|
It is possible to compare the benchmarking results. See [Additional Tooling Documentation](docs/tools.md)
|
|
|
|
## Debug vs Release
|
|
By default, benchmark builds as a debug library. You will see a warning in the
|
|
output when this is the case. To build it as a release library instead, use:
|
|
|
|
```
|
|
cmake -DCMAKE_BUILD_TYPE=Release
|
|
```
|
|
|
|
To enable link-time optimisation, use
|
|
|
|
```
|
|
cmake -DCMAKE_BUILD_TYPE=Release -DBENCHMARK_ENABLE_LTO=true
|
|
```
|
|
|
|
If you are using gcc, you might need to set `GCC_AR` and `GCC_RANLIB` cmake
|
|
cache variables, if autodetection fails.
|
|
|
|
If you are using clang, you may need to set `LLVMAR_EXECUTABLE`,
|
|
`LLVMNM_EXECUTABLE` and `LLVMRANLIB_EXECUTABLE` cmake cache variables.
|
|
|
|
## Compiler Support
|
|
|
|
Google Benchmark uses C++11 when building the library. As such we require
|
|
a modern C++ toolchain, both compiler and standard library.
|
|
|
|
The following minimum versions are strongly recommended build the library:
|
|
|
|
* GCC 4.8
|
|
* Clang 3.4
|
|
* Visual Studio 2013
|
|
* Intel 2015 Update 1
|
|
|
|
Anything older *may* work.
|
|
|
|
Note: Using the library and its headers in C++03 is supported. C++11 is only
|
|
required to build the library.
|
|
|
|
## Disable CPU frequency scaling
|
|
If you see this error:
|
|
```
|
|
***WARNING*** CPU scaling is enabled, the benchmark real time measurements may be noisy and will incur extra overhead.
|
|
```
|
|
you might want to disable the CPU frequency scaling while running the benchmark:
|
|
```bash
|
|
sudo cpupower frequency-set --governor performance
|
|
./mybench
|
|
sudo cpupower frequency-set --governor powersave
|
|
```
|