histogram/benchmark/histogram_filling_experiments.cpp
Hans Dembinski df647cf959
update copyright (#55)
* add missing copyright notices
* workaround for xml_iarchive bug to handle XML with comments
* fixing min/max according to boost guidelines
2019-08-19 16:53:27 +02:00

178 lines
5.9 KiB
C++

// Copyright 2015-2019 Hans Dembinski
//
// Distributed under the Boost Software License, Version 1.0.
// (See accompanying file LICENSE_1_0.txt
// or copy at http://www.boost.org/LICENSE_1_0.txt)
#include <benchmark/benchmark.h>
#include <boost/histogram/axis.hpp>
#include <boost/histogram/axis/traits.hpp>
#include <boost/histogram/detail/axes.hpp>
#include <boost/mp11/algorithm.hpp>
#include <tuple>
#include <type_traits>
#include <vector>
#include "../test/throw_exception.hpp"
#include "generator.hpp"
#include <boost/assert.hpp>
struct assert_check {
assert_check() {
BOOST_ASSERT(false); // don't run with asserts enabled
}
} _;
using namespace boost::histogram;
using reg = axis::regular<>;
using integ = axis::integer<>;
using var = axis::variable<>;
using vector_of_variant = std::vector<axis::variant<reg, integ, var>>;
template <class T, class U>
auto make_storage(const U& axes) {
return std::vector<T>(detail::bincount(axes), 0);
}
template <class T>
auto make_strides(const T& axes) {
std::vector<std::size_t> strides(detail::axes_rank(axes) + 1, 1);
auto sit = strides.begin();
detail::for_each_axis(axes, [&](const auto& a) { *++sit *= axis::traits::extent(a); });
return strides;
}
template <class Axes, class Storage, class Tuple>
void fill_b(const Axes& axes, Storage& storage, const Tuple& t) {
using namespace boost::mp11;
std::size_t stride = 1, index = 0;
mp_for_each<mp_iota<mp_size<Tuple>>>([&](auto i) {
const auto& a = boost::histogram::detail::axis_get<i>(axes);
const auto& v = std::get<i>(t);
index += (a.index(v) + 1) * stride;
stride *= axis::traits::extent(a);
});
++storage[index];
}
template <class Axes, class Storage, class Tuple>
void fill_c(const Axes& axes, const std::size_t* strides, Storage& storage,
const Tuple& t) {
using namespace boost::mp11;
std::size_t index = 0;
BOOST_ASSERT(boost::histogram::detail::axes_rank(axes) ==
boost::histogram::detail::axes_rank(t));
mp_for_each<mp_iota<mp_size<Tuple>>>([&](auto i) {
const auto& a = boost::histogram::detail::axis_get<i>(axes);
const auto& v = std::get<i>(t);
index += (a.index(v) + 1) * *strides++;
});
++storage[index];
}
template <class T, class Distribution>
static void fill_1d_a(benchmark::State& state) {
auto axes = std::make_tuple(reg(100, 0, 1));
generator<Distribution> gen;
auto storage = make_storage<T>(axes);
for (auto _ : state) {
const auto i = std::get<0>(axes).index(gen());
++storage[i + 1];
}
}
template <class T, class Distribution>
static void fill_1d_b(benchmark::State& state) {
auto axes = std::make_tuple(reg(100, 0, 1));
generator<Distribution> gen;
auto storage = make_storage<T>(axes);
for (auto _ : state) { fill_b(axes, storage, std::forward_as_tuple(gen())); }
}
template <class T, class Distribution>
static void fill_1d_c(benchmark::State& state) {
auto axes = std::make_tuple(reg(100, 0, 1));
generator<Distribution> gen;
auto storage = make_storage<T>(axes);
auto strides = make_strides(axes);
for (auto _ : state) {
fill_c(axes, strides.data(), storage, std::forward_as_tuple(gen()));
}
}
template <class T, class Distribution>
static void fill_1d_c_dyn(benchmark::State& state) {
auto axes = vector_of_variant({reg(100, 0, 1)});
generator<Distribution> gen;
auto storage = make_storage<T>(axes);
auto strides = make_strides(axes);
for (auto _ : state) {
fill_c(axes, strides.data(), storage, std::forward_as_tuple(gen()));
}
}
template <class T, class Distribution>
static void fill_2d_a(benchmark::State& state) {
auto axes = std::make_tuple(reg(100, 0, 1), reg(100, 0, 1));
generator<Distribution> gen;
auto storage = make_storage<T>(axes);
for (auto _ : state) {
const auto i0 = std::get<0>(axes).index(gen());
const auto i1 = std::get<1>(axes).index(gen());
const auto stride = axis::traits::extent(std::get<0>(axes));
++storage[(i0 + 1) * stride + (i1 + 1)];
}
}
template <class T, class Distribution>
static void fill_2d_b(benchmark::State& state) {
auto axes = std::make_tuple(reg(100, 0, 1), reg(100, 0, 1));
generator<Distribution> gen;
auto storage = make_storage<T>(axes);
for (auto _ : state) { fill_b(axes, storage, std::forward_as_tuple(gen(), gen())); }
}
template <class T, class Distribution>
static void fill_2d_c(benchmark::State& state) {
auto axes = std::make_tuple(reg(100, 0, 1), reg(100, 0, 1));
generator<Distribution> gen;
auto storage = make_storage<T>(axes);
auto strides = make_strides(axes);
BOOST_ASSERT(strides.size() == 3);
BOOST_ASSERT(strides[0] == 1);
BOOST_ASSERT(strides[1] == 102);
for (auto _ : state) {
fill_c(axes, strides.data(), storage, std::forward_as_tuple(gen(), gen()));
}
}
template <class T, class Distribution>
static void fill_2d_c_dyn(benchmark::State& state) {
auto axes = vector_of_variant({reg(100, 0, 1), reg(100, 0, 1)});
generator<Distribution> gen;
auto storage = make_storage<T>(axes);
auto strides = make_strides(axes);
BOOST_ASSERT(strides.size() == 3);
BOOST_ASSERT(strides[0] == 1);
BOOST_ASSERT(strides[1] == 102);
for (auto _ : state) {
fill_c(axes, strides.data(), storage, std::forward_as_tuple(gen(), gen()));
}
}
BENCHMARK_TEMPLATE(fill_1d_a, int, uniform);
BENCHMARK_TEMPLATE(fill_1d_a, double, uniform);
BENCHMARK_TEMPLATE(fill_1d_b, double, uniform);
BENCHMARK_TEMPLATE(fill_1d_c, double, uniform);
BENCHMARK_TEMPLATE(fill_1d_c_dyn, double, uniform);
BENCHMARK_TEMPLATE(fill_2d_a, double, uniform);
BENCHMARK_TEMPLATE(fill_2d_b, double, uniform);
BENCHMARK_TEMPLATE(fill_2d_c, double, uniform);
BENCHMARK_TEMPLATE(fill_2d_c_dyn, double, uniform);
BENCHMARK_TEMPLATE(fill_1d_a, double, normal);
BENCHMARK_TEMPLATE(fill_1d_b, double, normal);
BENCHMARK_TEMPLATE(fill_1d_c, double, normal);
BENCHMARK_TEMPLATE(fill_2d_a, double, normal);
BENCHMARK_TEMPLATE(fill_2d_b, double, normal);
BENCHMARK_TEMPLATE(fill_2d_c, double, normal);