benchmark
=========
[](https://travis-ci.org/google/benchmark)
[](https://ci.appveyor.com/project/google/benchmark/branch/master)
[](https://coveralls.io/r/google/benchmark)
A library to support the benchmarking of functions, similar to unit-tests.
Discussion group: https://groups.google.com/d/forum/benchmark-discuss
IRC channel: https://freenode.net #googlebenchmark
Example usage
-------------
Define a function that executes the code to be measured a
specified number of times:
```c++
static void BM_StringCreation(benchmark::State& state) {
while (state.KeepRunning())
std::string empty_string;
}
// Register the function as a benchmark
BENCHMARK(BM_StringCreation);
// Define another benchmark
static void BM_StringCopy(benchmark::State& state) {
std::string x = "hello";
while (state.KeepRunning())
std::string copy(x);
}
BENCHMARK(BM_StringCopy);
BENCHMARK_MAIN();
```
Sometimes a family of microbenchmarks can be implemented with
just one routine that takes an extra argument to specify which
one of the family of benchmarks to run. For example, the following
code defines a family of microbenchmarks for measuring the speed
of `memcpy()` calls of different lengths:
```c++
static void BM_memcpy(benchmark::State& state) {
char* src = new char[state.range_x()]; char* dst = new char[state.range_x()];
memset(src, 'x', state.range_x());
while (state.KeepRunning())
memcpy(dst, src, state.range_x());
state.SetBytesProcessed(int64_t(state.iterations()) *
int64_t(state.range_x()));
delete[] src;
delete[] dst;
}
BENCHMARK(BM_memcpy)->Arg(8)->Arg(64)->Arg(512)->Arg(1<<10)->Arg(8<<10);
```
The preceding code is quite repetitive, and can be replaced with the
following short-hand. The following invocation will pick a few
appropriate arguments in the specified range and will generate a
microbenchmark for each such argument.
```c++
BENCHMARK(BM_memcpy)->Range(8, 8<<10);
```
You might have a microbenchmark that depends on two inputs. For
example, the following code defines a family of microbenchmarks for
measuring the speed of set insertion.
```c++
static void BM_SetInsert(benchmark::State& state) {
while (state.KeepRunning()) {
state.PauseTiming();
std::set<int> data = ConstructRandomSet(state.range_x());
state.ResumeTiming();
for (int j = 0; j < state.range_y(); ++j)
data.insert(RandomNumber());
}
}
BENCHMARK(BM_SetInsert)
->ArgPair(1<<10, 1)
->ArgPair(1<<10, 8)
->ArgPair(1<<10, 64)
->ArgPair(1<<10, 512)
->ArgPair(8<<10, 1)
->ArgPair(8<<10, 8)
->ArgPair(8<<10, 64)
->ArgPair(8<<10, 512);
```
The preceding code is quite repetitive, and can be replaced with
the following short-hand. The following macro will pick a few
appropriate arguments in the product of the two specified ranges
and will generate a microbenchmark for each such pair.
```c++
BENCHMARK(BM_SetInsert)->RangePair(1<<10, 8<<10, 1, 512);
```
For more complex patterns of inputs, passing a custom function
to Apply allows programmatic specification of an
arbitrary set of arguments to run the microbenchmark on.
The following example enumerates a dense range on one parameter,
and a sparse range on the second.
```c++
static void CustomArguments(benchmark::internal::Benchmark* b) {
for (int i = 0; i <= 10; ++i)
for (int j = 32; j <= 1024*1024; j *= 8)
b->ArgPair(i, j);
}
BENCHMARK(BM_SetInsert)->Apply(CustomArguments);
```
Templated microbenchmarks work the same way:
Produce then consume 'size' messages 'iters' times
Measures throughput in the absence of multiprogramming.
```c++
template <class Q> int BM_Sequential(benchmark::State& state) {
Q q;
typename Q::value_type v;
while (state.KeepRunning()) {
for (int i = state.range_x(); i--; )
q.push(v);
for (int e = state.range_x(); e--; )
q.Wait(&v);
}
// actually messages, not bytes:
state.SetBytesProcessed(
static_cast<int64_t>(state.iterations())*state.range_x());
}
BENCHMARK_TEMPLATE(BM_Sequential, WaitQueue<int>)->Range(1<<0, 1<<10);
```
Three macros are provided for adding benchmark templates.
```c++
#if __cplusplus >= 201103L // C++11 and greater.
#define BENCHMARK_TEMPLATE(func, ...) // Takes any number of parameters.
#else // C++ < C++11
#define BENCHMARK_TEMPLATE(func, arg1)
#endif
#define BENCHMARK_TEMPLATE1(func, arg1)
#define BENCHMARK_TEMPLATE2(func, arg1, arg2)
```
In a multithreaded test (benchmark invoked by multiple threads simultaneously),
it is guaranteed that none of the threads will start until all have called
KeepRunning, and all will have finished before KeepRunning returns false. As
such, any global setup or teardown you want to do can be
wrapped in a check against the thread index:
```c++
static void BM_MultiThreaded(benchmark::State& state) {
if (state.thread_index == 0) {
// Setup code here.
}
while (state.KeepRunning()) {
// Run the test as normal.
}
if (state.thread_index == 0) {
// Teardown code here.
}
}
BENCHMARK(BM_MultiThreaded)->Threads(2);
```
If the benchmarked code itself uses threads and you want to compare it to
single-threaded code, you may want to use real-time ("wallclock") measurements
for latency comparisons:
```c++
BENCHMARK(BM_test)->Range(8, 8<<10)->UseRealTime();
```
Without `UseRealTime`, CPU time is used by default.
To prevent a value or expression from being optimized away by the compiler
the `benchmark::DoNotOptimize(...)` function can be used.
```c++
static void BM_test(benchmark::State& state) {
while (state.KeepRunning()) {
int x = 0;
for (int i=0; i < 64; ++i) {
benchmark::DoNotOptimize(x += i);
}
}
}
```
Benchmark 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) {
while (st.KeepRunning()) {
...
}
}
BENCHMARK_DEFINE_F(MyFixture, BarTest)(benchmark::State& st) {
while (st.KeepRunning()) {
...
}
}
/* BarTest is NOT registered */
BENCHMARK_REGISTER_F(MyFixture, BarTest)->Threads(2);
/* BarTest is now registered */
```
Output Formats
--------------
The library supports multiple output formats. Use the
`--benchmark_format=<tabular|json>` flag to set the format type. `tabular` is
the default format.
The Tabular 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 ever 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,
```
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
```
Linking against the library
---------------------------
When using gcc, it is necessary to link against pthread to avoid runtime exceptions. This is due to how gcc implements std::thread. See [issue #67](https://github.com/google/benchmark/issues/67) for more details.