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authorMartin Ankerl <martin.ankerl@gmail.com>2020-06-13 09:37:27 +0200
committerMartin Ankerl <martin.ankerl@gmail.com>2020-06-13 12:24:18 +0200
commit78c312c983255e15fc274de2368a2ec13ce81cbf (patch)
tree09c5cec9b0b3f7ef2aa9364057858861c134cf45 /src/bench/bench_bitcoin.cpp
parent19e919217e6d62e3640525e4149de1a4ae04e74f (diff)
downloadbitcoin-78c312c983255e15fc274de2368a2ec13ce81cbf.tar.xz
Replace current benchmarking framework with nanobench
This replaces the current benchmarking framework with nanobench [1], an MIT licensed single-header benchmarking library, of which I am the autor. This has in my opinion several advantages, especially on Linux: * fast: Running all benchmarks takes ~6 seconds instead of 4m13s on an Intel i7-8700 CPU @ 3.20GHz. * accurate: I ran e.g. the benchmark for SipHash_32b 10 times and calculate standard deviation / mean = coefficient of variation: * 0.57% CV for old benchmarking framework * 0.20% CV for nanobench So the benchmark results with nanobench seem to vary less than with the old framework. * It automatically determines runtime based on clock precision, no need to specify number of evaluations. * measure instructions, cycles, branches, instructions per cycle, branch misses (only Linux, when performance counters are available) * output in markdown table format. * Warn about unstable environment (frequency scaling, turbo, ...) * For better profiling, it is possible to set the environment variable NANOBENCH_ENDLESS to force endless running of a particular benchmark without the need to recompile. This makes it to e.g. run "perf top" and look at hotspots. Here is an example copy & pasted from the terminal output: | ns/byte | byte/s | err% | ins/byte | cyc/byte | IPC | bra/byte | miss% | total | benchmark |--------------------:|--------------------:|--------:|----------------:|----------------:|-------:|---------------:|--------:|----------:|:---------- | 2.52 | 396,529,415.94 | 0.6% | 25.42 | 8.02 | 3.169 | 0.06 | 0.0% | 0.03 | `bench/crypto_hash.cpp RIPEMD160` | 1.87 | 535,161,444.83 | 0.3% | 21.36 | 5.95 | 3.589 | 0.06 | 0.0% | 0.02 | `bench/crypto_hash.cpp SHA1` | 3.22 | 310,344,174.79 | 1.1% | 36.80 | 10.22 | 3.601 | 0.09 | 0.0% | 0.04 | `bench/crypto_hash.cpp SHA256` | 2.01 | 496,375,796.23 | 0.0% | 18.72 | 6.43 | 2.911 | 0.01 | 1.0% | 0.00 | `bench/crypto_hash.cpp SHA256D64_1024` | 7.23 | 138,263,519.35 | 0.1% | 82.66 | 23.11 | 3.577 | 1.63 | 0.1% | 0.00 | `bench/crypto_hash.cpp SHA256_32b` | 3.04 | 328,780,166.40 | 0.3% | 35.82 | 9.69 | 3.696 | 0.03 | 0.0% | 0.03 | `bench/crypto_hash.cpp SHA512` [1] https://github.com/martinus/nanobench * Adds support for asymptotes This adds support to calculate asymptotic complexity of a benchmark. This is similar to #17375, but currently only one asymptote is supported, and I have added support in the benchmark `ComplexMemPool` as an example. Usage is e.g. like this: ``` ./bench_bitcoin -filter=ComplexMemPool -asymptote=25,50,100,200,400,600,800 ``` This runs the benchmark `ComplexMemPool` several times but with different complexityN settings. The benchmark can extract that number and use it accordingly. Here, it's used for `childTxs`. The output is this: | complexityN | ns/op | op/s | err% | ins/op | cyc/op | IPC | total | benchmark |------------:|--------------------:|--------------------:|--------:|----------------:|----------------:|-------:|----------:|:---------- | 25 | 1,064,241.00 | 939.64 | 1.4% | 3,960,279.00 | 2,829,708.00 | 1.400 | 0.01 | `ComplexMemPool` | 50 | 1,579,530.00 | 633.10 | 1.0% | 6,231,810.00 | 4,412,674.00 | 1.412 | 0.02 | `ComplexMemPool` | 100 | 4,022,774.00 | 248.58 | 0.6% | 16,544,406.00 | 11,889,535.00 | 1.392 | 0.04 | `ComplexMemPool` | 200 | 15,390,986.00 | 64.97 | 0.2% | 63,904,254.00 | 47,731,705.00 | 1.339 | 0.17 | `ComplexMemPool` | 400 | 69,394,711.00 | 14.41 | 0.1% | 272,602,461.00 | 219,014,691.00 | 1.245 | 0.76 | `ComplexMemPool` | 600 | 168,977,165.00 | 5.92 | 0.1% | 639,108,082.00 | 535,316,887.00 | 1.194 | 1.86 | `ComplexMemPool` | 800 | 310,109,077.00 | 3.22 | 0.1% |1,149,134,246.00 | 984,620,812.00 | 1.167 | 3.41 | `ComplexMemPool` | coefficient | err% | complexity |--------------:|-------:|------------ | 4.78486e-07 | 4.5% | O(n^2) | 6.38557e-10 | 21.7% | O(n^3) | 3.42338e-05 | 38.0% | O(n log n) | 0.000313914 | 46.9% | O(n) | 0.0129823 | 114.4% | O(log n) | 0.0815055 | 133.8% | O(1) The best fitting curve is O(n^2), so the algorithm seems to scale quadratic with `childTxs` in the range 25 to 800.
Diffstat (limited to 'src/bench/bench_bitcoin.cpp')
-rw-r--r--src/bench/bench_bitcoin.cpp64
1 files changed, 24 insertions, 40 deletions
diff --git a/src/bench/bench_bitcoin.cpp b/src/bench/bench_bitcoin.cpp
index 1b75854210..981800c68e 100644
--- a/src/bench/bench_bitcoin.cpp
+++ b/src/bench/bench_bitcoin.cpp
@@ -9,26 +9,30 @@
#include <memory>
-static const int64_t DEFAULT_BENCH_EVALUATIONS = 5;
static const char* DEFAULT_BENCH_FILTER = ".*";
-static const char* DEFAULT_BENCH_SCALING = "1.0";
-static const char* DEFAULT_BENCH_PRINTER = "console";
-static const char* DEFAULT_PLOT_PLOTLYURL = "https://cdn.plot.ly/plotly-latest.min.js";
-static const int64_t DEFAULT_PLOT_WIDTH = 1024;
-static const int64_t DEFAULT_PLOT_HEIGHT = 768;
static void SetupBenchArgs(ArgsManager& argsman)
{
SetupHelpOptions(argsman);
- argsman.AddArg("-list", "List benchmarks without executing them. Can be combined with -scaling and -filter", ArgsManager::ALLOW_ANY, OptionsCategory::OPTIONS);
- argsman.AddArg("-evals=<n>", strprintf("Number of measurement evaluations to perform. (default: %u)", DEFAULT_BENCH_EVALUATIONS), ArgsManager::ALLOW_ANY, OptionsCategory::OPTIONS);
+ argsman.AddArg("-list", "List benchmarks without executing them", ArgsManager::ALLOW_ANY, OptionsCategory::OPTIONS);
argsman.AddArg("-filter=<regex>", strprintf("Regular expression filter to select benchmark by name (default: %s)", DEFAULT_BENCH_FILTER), ArgsManager::ALLOW_ANY, OptionsCategory::OPTIONS);
- argsman.AddArg("-scaling=<n>", strprintf("Scaling factor for benchmark's runtime (default: %u)", DEFAULT_BENCH_SCALING), ArgsManager::ALLOW_ANY, OptionsCategory::OPTIONS);
- argsman.AddArg("-printer=(console|plot)", strprintf("Choose printer format. console: print data to console. plot: Print results as HTML graph (default: %s)", DEFAULT_BENCH_PRINTER), ArgsManager::ALLOW_ANY, OptionsCategory::OPTIONS);
- argsman.AddArg("-plot-plotlyurl=<uri>", strprintf("URL to use for plotly.js (default: %s)", DEFAULT_PLOT_PLOTLYURL), ArgsManager::ALLOW_ANY, OptionsCategory::OPTIONS);
- argsman.AddArg("-plot-width=<x>", strprintf("Plot width in pixel (default: %u)", DEFAULT_PLOT_WIDTH), ArgsManager::ALLOW_ANY, OptionsCategory::OPTIONS);
- argsman.AddArg("-plot-height=<x>", strprintf("Plot height in pixel (default: %u)", DEFAULT_PLOT_HEIGHT), ArgsManager::ALLOW_ANY, OptionsCategory::OPTIONS);
+ argsman.AddArg("-asymptote=n1,n2,n3,...", strprintf("Test asymptotic growth of the runtime of an algorithm, if supported by the benchmark"), ArgsManager::ALLOW_ANY, OptionsCategory::OPTIONS);
+ argsman.AddArg("-output_csv=<output.csv>", "Generate CSV file with the most important benchmark results.", ArgsManager::ALLOW_ANY, OptionsCategory::OPTIONS);
+ argsman.AddArg("-output_json=<output.json>", "Generate JSON file with all benchmark results.", ArgsManager::ALLOW_ANY, OptionsCategory::OPTIONS);
+}
+
+// parses a comma separated list like "10,20,30,50"
+static std::vector<double> parseAsymptote(const std::string& str) {
+ std::stringstream ss(str);
+ std::vector<double> numbers;
+ double d;
+ char c;
+ while (ss >> d) {
+ numbers.push_back(d);
+ ss >> c;
+ }
+ return numbers;
}
int main(int argc, char** argv)
@@ -47,34 +51,14 @@ int main(int argc, char** argv)
return EXIT_SUCCESS;
}
- int64_t evaluations = argsman.GetArg("-evals", DEFAULT_BENCH_EVALUATIONS);
- std::string regex_filter = argsman.GetArg("-filter", DEFAULT_BENCH_FILTER);
- std::string scaling_str = argsman.GetArg("-scaling", DEFAULT_BENCH_SCALING);
- bool is_list_only = argsman.GetBoolArg("-list", false);
-
- if (evaluations == 0) {
- return EXIT_SUCCESS;
- } else if (evaluations < 0) {
- tfm::format(std::cerr, "Error parsing evaluations argument: %d\n", evaluations);
- return EXIT_FAILURE;
- }
-
- double scaling_factor;
- if (!ParseDouble(scaling_str, &scaling_factor)) {
- tfm::format(std::cerr, "Error parsing scaling factor as double: %s\n", scaling_str);
- return EXIT_FAILURE;
- }
-
- std::unique_ptr<benchmark::Printer> printer = MakeUnique<benchmark::ConsolePrinter>();
- std::string printer_arg = argsman.GetArg("-printer", DEFAULT_BENCH_PRINTER);
- if ("plot" == printer_arg) {
- printer.reset(new benchmark::PlotlyPrinter(
- argsman.GetArg("-plot-plotlyurl", DEFAULT_PLOT_PLOTLYURL),
- argsman.GetArg("-plot-width", DEFAULT_PLOT_WIDTH),
- argsman.GetArg("-plot-height", DEFAULT_PLOT_HEIGHT)));
- }
+ benchmark::Args args;
+ args.regex_filter = argsman.GetArg("-filter", DEFAULT_BENCH_FILTER);
+ args.is_list_only = argsman.GetBoolArg("-list", false);
+ args.asymptote = parseAsymptote(argsman.GetArg("-asymptote", ""));
+ args.output_csv = argsman.GetArg("-output_csv", "");
+ args.output_json = argsman.GetArg("-output_json", "");
- benchmark::BenchRunner::RunAll(*printer, evaluations, scaling_factor, regex_filter, is_list_only);
+ benchmark::BenchRunner::RunAll(args);
return EXIT_SUCCESS;
}