mame/3rdparty/benchmark

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:

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:

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.

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.

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.

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.

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.

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.

#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:

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:

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.

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:

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:

{
  "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 for more details.