283 lines
9.7 KiB
C++
283 lines
9.7 KiB
C++
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// Copyright 2017 The Abseil Authors.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// https://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#include <algorithm>
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#include <cstdint>
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#include <limits>
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#include <random>
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#include <vector>
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#include "benchmark/benchmark.h"
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#include "absl/base/config.h"
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#include "absl/numeric/int128.h"
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namespace {
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constexpr size_t kSampleSize = 1000000;
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std::mt19937 MakeRandomEngine() {
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std::random_device r;
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std::seed_seq seed({r(), r(), r(), r(), r(), r(), r(), r()});
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return std::mt19937(seed);
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}
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template <typename T,
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typename H = typename std::conditional<
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std::numeric_limits<T>::is_signed, int64_t, uint64_t>::type>
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std::vector<std::pair<T, T>> GetRandomClass128SampleUniformDivisor() {
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std::vector<std::pair<T, T>> values;
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std::mt19937 random = MakeRandomEngine();
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std::uniform_int_distribution<H> uniform_h;
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values.reserve(kSampleSize);
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for (size_t i = 0; i < kSampleSize; ++i) {
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T a{absl::MakeUint128(uniform_h(random), uniform_h(random))};
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T b{absl::MakeUint128(uniform_h(random), uniform_h(random))};
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values.emplace_back(std::max(a, b), std::max(T(2), std::min(a, b)));
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}
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return values;
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}
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template <typename T>
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void BM_DivideClass128UniformDivisor(benchmark::State& state) {
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auto values = GetRandomClass128SampleUniformDivisor<T>();
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while (state.KeepRunningBatch(values.size())) {
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for (const auto& pair : values) {
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benchmark::DoNotOptimize(pair.first / pair.second);
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}
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}
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}
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BENCHMARK_TEMPLATE(BM_DivideClass128UniformDivisor, absl::uint128);
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BENCHMARK_TEMPLATE(BM_DivideClass128UniformDivisor, absl::int128);
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template <typename T>
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void BM_RemainderClass128UniformDivisor(benchmark::State& state) {
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auto values = GetRandomClass128SampleUniformDivisor<T>();
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while (state.KeepRunningBatch(values.size())) {
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for (const auto& pair : values) {
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benchmark::DoNotOptimize(pair.first % pair.second);
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}
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}
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}
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BENCHMARK_TEMPLATE(BM_RemainderClass128UniformDivisor, absl::uint128);
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BENCHMARK_TEMPLATE(BM_RemainderClass128UniformDivisor, absl::int128);
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template <typename T,
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typename H = typename std::conditional<
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std::numeric_limits<T>::is_signed, int64_t, uint64_t>::type>
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std::vector<std::pair<T, H>> GetRandomClass128SampleSmallDivisor() {
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std::vector<std::pair<T, H>> values;
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std::mt19937 random = MakeRandomEngine();
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std::uniform_int_distribution<H> uniform_h;
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values.reserve(kSampleSize);
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for (size_t i = 0; i < kSampleSize; ++i) {
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T a{absl::MakeUint128(uniform_h(random), uniform_h(random))};
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H b{std::max(H{2}, uniform_h(random))};
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values.emplace_back(std::max(a, T(b)), b);
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}
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return values;
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}
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template <typename T>
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void BM_DivideClass128SmallDivisor(benchmark::State& state) {
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auto values = GetRandomClass128SampleSmallDivisor<T>();
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while (state.KeepRunningBatch(values.size())) {
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for (const auto& pair : values) {
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benchmark::DoNotOptimize(pair.first / pair.second);
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}
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}
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}
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BENCHMARK_TEMPLATE(BM_DivideClass128SmallDivisor, absl::uint128);
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BENCHMARK_TEMPLATE(BM_DivideClass128SmallDivisor, absl::int128);
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template <typename T>
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void BM_RemainderClass128SmallDivisor(benchmark::State& state) {
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auto values = GetRandomClass128SampleSmallDivisor<T>();
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while (state.KeepRunningBatch(values.size())) {
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for (const auto& pair : values) {
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benchmark::DoNotOptimize(pair.first % pair.second);
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}
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}
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}
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BENCHMARK_TEMPLATE(BM_RemainderClass128SmallDivisor, absl::uint128);
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BENCHMARK_TEMPLATE(BM_RemainderClass128SmallDivisor, absl::int128);
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std::vector<std::pair<absl::uint128, absl::uint128>> GetRandomClass128Sample() {
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std::vector<std::pair<absl::uint128, absl::uint128>> values;
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std::mt19937 random = MakeRandomEngine();
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std::uniform_int_distribution<uint64_t> uniform_uint64;
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values.reserve(kSampleSize);
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for (size_t i = 0; i < kSampleSize; ++i) {
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values.emplace_back(
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absl::MakeUint128(uniform_uint64(random), uniform_uint64(random)),
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absl::MakeUint128(uniform_uint64(random), uniform_uint64(random)));
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}
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return values;
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}
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void BM_MultiplyClass128(benchmark::State& state) {
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auto values = GetRandomClass128Sample();
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while (state.KeepRunningBatch(values.size())) {
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for (const auto& pair : values) {
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benchmark::DoNotOptimize(pair.first * pair.second);
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}
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}
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}
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BENCHMARK(BM_MultiplyClass128);
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void BM_AddClass128(benchmark::State& state) {
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auto values = GetRandomClass128Sample();
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while (state.KeepRunningBatch(values.size())) {
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for (const auto& pair : values) {
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benchmark::DoNotOptimize(pair.first + pair.second);
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}
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}
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}
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BENCHMARK(BM_AddClass128);
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#ifdef ABSL_HAVE_INTRINSIC_INT128
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// Some implementations of <random> do not support __int128 when it is
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// available, so we make our own uniform_int_distribution-like type.
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template <typename T,
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typename H = typename std::conditional<
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std::is_same<T, __int128>::value, int64_t, uint64_t>::type>
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class UniformIntDistribution128 {
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public:
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// NOLINTNEXTLINE: mimicking std::uniform_int_distribution API
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T operator()(std::mt19937& generator) {
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return (static_cast<T>(dist64_(generator)) << 64) | dist64_(generator);
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}
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private:
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std::uniform_int_distribution<H> dist64_;
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};
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template <typename T,
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typename H = typename std::conditional<
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std::is_same<T, __int128>::value, int64_t, uint64_t>::type>
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std::vector<std::pair<T, T>> GetRandomIntrinsic128SampleUniformDivisor() {
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std::vector<std::pair<T, T>> values;
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std::mt19937 random = MakeRandomEngine();
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UniformIntDistribution128<T> uniform_128;
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values.reserve(kSampleSize);
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for (size_t i = 0; i < kSampleSize; ++i) {
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T a = uniform_128(random);
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T b = uniform_128(random);
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values.emplace_back(std::max(a, b),
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std::max(static_cast<T>(2), std::min(a, b)));
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}
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return values;
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}
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template <typename T>
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void BM_DivideIntrinsic128UniformDivisor(benchmark::State& state) {
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auto values = GetRandomIntrinsic128SampleUniformDivisor<T>();
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while (state.KeepRunningBatch(values.size())) {
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for (const auto& pair : values) {
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benchmark::DoNotOptimize(pair.first / pair.second);
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}
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}
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}
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BENCHMARK_TEMPLATE(BM_DivideIntrinsic128UniformDivisor, unsigned __int128);
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BENCHMARK_TEMPLATE(BM_DivideIntrinsic128UniformDivisor, __int128);
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template <typename T>
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void BM_RemainderIntrinsic128UniformDivisor(benchmark::State& state) {
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auto values = GetRandomIntrinsic128SampleUniformDivisor<T>();
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while (state.KeepRunningBatch(values.size())) {
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for (const auto& pair : values) {
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benchmark::DoNotOptimize(pair.first % pair.second);
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}
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}
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}
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BENCHMARK_TEMPLATE(BM_RemainderIntrinsic128UniformDivisor, unsigned __int128);
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BENCHMARK_TEMPLATE(BM_RemainderIntrinsic128UniformDivisor, __int128);
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template <typename T,
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typename H = typename std::conditional<
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std::is_same<T, __int128>::value, int64_t, uint64_t>::type>
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std::vector<std::pair<T, H>> GetRandomIntrinsic128SampleSmallDivisor() {
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std::vector<std::pair<T, H>> values;
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std::mt19937 random = MakeRandomEngine();
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UniformIntDistribution128<T> uniform_int128;
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std::uniform_int_distribution<H> uniform_int64;
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values.reserve(kSampleSize);
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for (size_t i = 0; i < kSampleSize; ++i) {
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T a = uniform_int128(random);
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H b = std::max(H{2}, uniform_int64(random));
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values.emplace_back(std::max(a, static_cast<T>(b)), b);
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}
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return values;
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}
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template <typename T>
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void BM_DivideIntrinsic128SmallDivisor(benchmark::State& state) {
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auto values = GetRandomIntrinsic128SampleSmallDivisor<T>();
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while (state.KeepRunningBatch(values.size())) {
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for (const auto& pair : values) {
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benchmark::DoNotOptimize(pair.first / pair.second);
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}
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}
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}
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BENCHMARK_TEMPLATE(BM_DivideIntrinsic128SmallDivisor, unsigned __int128);
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BENCHMARK_TEMPLATE(BM_DivideIntrinsic128SmallDivisor, __int128);
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template <typename T>
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void BM_RemainderIntrinsic128SmallDivisor(benchmark::State& state) {
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auto values = GetRandomIntrinsic128SampleSmallDivisor<T>();
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while (state.KeepRunningBatch(values.size())) {
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for (const auto& pair : values) {
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benchmark::DoNotOptimize(pair.first % pair.second);
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}
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}
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}
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BENCHMARK_TEMPLATE(BM_RemainderIntrinsic128SmallDivisor, unsigned __int128);
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BENCHMARK_TEMPLATE(BM_RemainderIntrinsic128SmallDivisor, __int128);
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std::vector<std::pair<unsigned __int128, unsigned __int128>>
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GetRandomIntrinsic128Sample() {
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std::vector<std::pair<unsigned __int128, unsigned __int128>> values;
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std::mt19937 random = MakeRandomEngine();
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UniformIntDistribution128<unsigned __int128> uniform_uint128;
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values.reserve(kSampleSize);
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for (size_t i = 0; i < kSampleSize; ++i) {
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values.emplace_back(uniform_uint128(random), uniform_uint128(random));
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}
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return values;
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}
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void BM_MultiplyIntrinsic128(benchmark::State& state) {
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auto values = GetRandomIntrinsic128Sample();
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while (state.KeepRunningBatch(values.size())) {
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for (const auto& pair : values) {
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benchmark::DoNotOptimize(pair.first * pair.second);
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}
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}
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}
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BENCHMARK(BM_MultiplyIntrinsic128);
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void BM_AddIntrinsic128(benchmark::State& state) {
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auto values = GetRandomIntrinsic128Sample();
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while (state.KeepRunningBatch(values.size())) {
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for (const auto& pair : values) {
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benchmark::DoNotOptimize(pair.first + pair.second);
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}
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}
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}
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BENCHMARK(BM_AddIntrinsic128);
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#endif // ABSL_HAVE_INTRINSIC_INT128
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} // namespace
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