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Improved microbenchmarking with multiple features.

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* inline performance critical code
* Average runtime is specified and used to calculate iterations.
* Console: show median of multiple runs
* plot: show box plot
* filter benchmarks
* specify scaling factor
* ignore src/test and src/bench in command line check script
* number of iterations instead of time
* Replaced runtime in BENCHMARK makro number of iterations.
* Added -? to bench_bitcoin
* Benchmark plotly.js URL, width, height can be customized
* Fixed incorrect precision warning
This commit is contained in:
Martin Ankerl
2017-10-17 16:48:02 +02:00
parent 604e08c83c
commit 00721e69f8
15 changed files with 286 additions and 171 deletions
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16
src/bench/rollingbloom.cpp
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@@ -12,8 +12,6 @@ static void RollingBloom(benchmark::State& state)
CRollingBloomFilter filter(120000, 0.000001);
std::vector<unsigned char> data(32);
uint32_t count = 0;
uint32_t nEntriesPerGeneration = (120000 + 1) / 2;
uint32_t countnow = 0;
uint64_t match = 0;
while (state.KeepRunning()) {
count++;
@@ -21,16 +19,8 @@ static void RollingBloom(benchmark::State& state)
data[1] = count >> 8;
data[2] = count >> 16;
data[3] = count >> 24;
if (countnow == nEntriesPerGeneration) {
auto b = benchmark::clock::now();
filter.insert(data);
auto total = std::chrono::duration_cast<std::chrono::nanoseconds>(benchmark::clock::now() - b).count();
std::cout << "RollingBloom-refresh,1," << total << "," << total << "," << total << "\n";
countnow = 0;
} else {
filter.insert(data);
}
countnow++;
filter.insert(data);
data[0] = count >> 24;
data[1] = count >> 16;
data[2] = count >> 8;
@@ -39,4 +29,4 @@ static void RollingBloom(benchmark::State& state)
}
}
BENCHMARK(RollingBloom);
BENCHMARK(RollingBloom, 1500 * 1000);