| // Copyright 2017 The Abseil Authors. |
| // |
| // Licensed under the Apache License, Version 2.0 (the "License"); |
| // you may not use this file except in compliance with the License. |
| // You may obtain a copy of the License at |
| // |
| // https://www.apache.org/licenses/LICENSE-2.0 |
| // |
| // Unless required by applicable law or agreed to in writing, software |
| // distributed under the License is distributed on an "AS IS" BASIS, |
| // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| // See the License for the specific language governing permissions and |
| // limitations under the License. |
| |
| // Benchmarks for absl random distributions as well as a selection of the |
| // C++ standard library random distributions. |
| |
| #include <algorithm> |
| #include <cstddef> |
| #include <cstdint> |
| #include <initializer_list> |
| #include <iterator> |
| #include <limits> |
| #include <random> |
| #include <type_traits> |
| #include <vector> |
| |
| #include "absl/base/macros.h" |
| #include "absl/meta/type_traits.h" |
| #include "absl/random/bernoulli_distribution.h" |
| #include "absl/random/beta_distribution.h" |
| #include "absl/random/exponential_distribution.h" |
| #include "absl/random/gaussian_distribution.h" |
| #include "absl/random/internal/fast_uniform_bits.h" |
| #include "absl/random/internal/randen_engine.h" |
| #include "absl/random/log_uniform_int_distribution.h" |
| #include "absl/random/poisson_distribution.h" |
| #include "absl/random/random.h" |
| #include "absl/random/uniform_int_distribution.h" |
| #include "absl/random/uniform_real_distribution.h" |
| #include "absl/random/zipf_distribution.h" |
| #include "benchmark/benchmark.h" |
| |
| namespace { |
| |
| // Seed data to avoid reading random_device() for benchmarks. |
| uint32_t kSeedData[] = { |
| 0x1B510052, 0x9A532915, 0xD60F573F, 0xBC9BC6E4, 0x2B60A476, 0x81E67400, |
| 0x08BA6FB5, 0x571BE91F, 0xF296EC6B, 0x2A0DD915, 0xB6636521, 0xE7B9F9B6, |
| 0xFF34052E, 0xC5855664, 0x53B02D5D, 0xA99F8FA1, 0x08BA4799, 0x6E85076A, |
| 0x4B7A70E9, 0xB5B32944, 0xDB75092E, 0xC4192623, 0xAD6EA6B0, 0x49A7DF7D, |
| 0x9CEE60B8, 0x8FEDB266, 0xECAA8C71, 0x699A18FF, 0x5664526C, 0xC2B19EE1, |
| 0x193602A5, 0x75094C29, 0xA0591340, 0xE4183A3E, 0x3F54989A, 0x5B429D65, |
| 0x6B8FE4D6, 0x99F73FD6, 0xA1D29C07, 0xEFE830F5, 0x4D2D38E6, 0xF0255DC1, |
| 0x4CDD2086, 0x8470EB26, 0x6382E9C6, 0x021ECC5E, 0x09686B3F, 0x3EBAEFC9, |
| 0x3C971814, 0x6B6A70A1, 0x687F3584, 0x52A0E286, 0x13198A2E, 0x03707344, |
| }; |
| |
| // PrecompiledSeedSeq provides kSeedData to a conforming |
| // random engine to speed initialization in the benchmarks. |
| class PrecompiledSeedSeq { |
| public: |
| using result_type = uint32_t; |
| |
| PrecompiledSeedSeq() = default; |
| |
| template <typename Iterator> |
| PrecompiledSeedSeq(Iterator begin, Iterator end) {} |
| |
| template <typename T> |
| PrecompiledSeedSeq(std::initializer_list<T> il) {} |
| |
| template <typename OutIterator> |
| void generate(OutIterator begin, OutIterator end) { |
| static size_t idx = 0; |
| for (; begin != end; begin++) { |
| *begin = kSeedData[idx++]; |
| if (idx >= ABSL_ARRAYSIZE(kSeedData)) { |
| idx = 0; |
| } |
| } |
| } |
| |
| size_t size() const { return ABSL_ARRAYSIZE(kSeedData); } |
| |
| template <typename OutIterator> |
| void param(OutIterator out) const { |
| std::copy(std::begin(kSeedData), std::end(kSeedData), out); |
| } |
| }; |
| |
| // use_default_initialization<T> indicates whether the random engine |
| // T must be default initialized, or whether we may initialize it using |
| // a seed sequence. This is used because some engines do not accept seed |
| // sequence-based initialization. |
| template <typename E> |
| using use_default_initialization = std::false_type; |
| |
| // make_engine<T, SSeq> returns a random_engine which is initialized, |
| // either via the default constructor, when use_default_initialization<T> |
| // is true, or via the indicated seed sequence, SSeq. |
| template <typename Engine, typename SSeq = PrecompiledSeedSeq> |
| typename absl::enable_if_t<!use_default_initialization<Engine>::value, Engine> |
| make_engine() { |
| // Initialize the random engine using the seed sequence SSeq, which |
| // is constructed from the precompiled seed data. |
| SSeq seq(std::begin(kSeedData), std::end(kSeedData)); |
| return Engine(seq); |
| } |
| |
| template <typename Engine, typename SSeq = PrecompiledSeedSeq> |
| typename absl::enable_if_t<use_default_initialization<Engine>::value, Engine> |
| make_engine() { |
| // Initialize the random engine using the default constructor. |
| return Engine(); |
| } |
| |
| template <typename Engine, typename SSeq> |
| void BM_Construct(benchmark::State& state) { |
| for (auto _ : state) { |
| auto rng = make_engine<Engine, SSeq>(); |
| benchmark::DoNotOptimize(rng()); |
| } |
| } |
| |
| template <typename Engine> |
| void BM_Direct(benchmark::State& state) { |
| using value_type = typename Engine::result_type; |
| // Direct use of the URBG. |
| auto rng = make_engine<Engine>(); |
| for (auto _ : state) { |
| benchmark::DoNotOptimize(rng()); |
| } |
| state.SetBytesProcessed(sizeof(value_type) * state.iterations()); |
| } |
| |
| template <typename Engine> |
| void BM_Generate(benchmark::State& state) { |
| // std::generate makes a copy of the RNG; thus this tests the |
| // copy-constructor efficiency. |
| using value_type = typename Engine::result_type; |
| std::vector<value_type> v(64); |
| auto rng = make_engine<Engine>(); |
| while (state.KeepRunningBatch(64)) { |
| std::generate(std::begin(v), std::end(v), rng); |
| } |
| } |
| |
| template <typename Engine, size_t elems> |
| void BM_Shuffle(benchmark::State& state) { |
| // Direct use of the Engine. |
| std::vector<uint32_t> v(elems); |
| while (state.KeepRunningBatch(elems)) { |
| auto rng = make_engine<Engine>(); |
| std::shuffle(std::begin(v), std::end(v), rng); |
| } |
| } |
| |
| template <typename Engine, size_t elems> |
| void BM_ShuffleReuse(benchmark::State& state) { |
| // Direct use of the Engine. |
| std::vector<uint32_t> v(elems); |
| auto rng = make_engine<Engine>(); |
| while (state.KeepRunningBatch(elems)) { |
| std::shuffle(std::begin(v), std::end(v), rng); |
| } |
| } |
| |
| template <typename Engine, typename Dist, typename... Args> |
| void BM_Dist(benchmark::State& state, Args&&... args) { |
| using value_type = typename Dist::result_type; |
| auto rng = make_engine<Engine>(); |
| Dist dis{std::forward<Args>(args)...}; |
| // Compare the following loop performance: |
| for (auto _ : state) { |
| benchmark::DoNotOptimize(dis(rng)); |
| } |
| state.SetBytesProcessed(sizeof(value_type) * state.iterations()); |
| } |
| |
| template <typename Engine, typename Dist> |
| void BM_Large(benchmark::State& state) { |
| using value_type = typename Dist::result_type; |
| volatile value_type kMin = 0; |
| volatile value_type kMax = std::numeric_limits<value_type>::max() / 2 + 1; |
| BM_Dist<Engine, Dist>(state, kMin, kMax); |
| } |
| |
| template <typename Engine, typename Dist> |
| void BM_Small(benchmark::State& state) { |
| using value_type = typename Dist::result_type; |
| volatile value_type kMin = 0; |
| volatile value_type kMax = std::numeric_limits<value_type>::max() / 64 + 1; |
| BM_Dist<Engine, Dist>(state, kMin, kMax); |
| } |
| |
| template <typename Engine, typename Dist, int A> |
| void BM_Bernoulli(benchmark::State& state) { |
| volatile double a = static_cast<double>(A) / 1000000; |
| BM_Dist<Engine, Dist>(state, a); |
| } |
| |
| template <typename Engine, typename Dist, int A, int B> |
| void BM_Beta(benchmark::State& state) { |
| using value_type = typename Dist::result_type; |
| volatile value_type a = static_cast<value_type>(A) / 100; |
| volatile value_type b = static_cast<value_type>(B) / 100; |
| BM_Dist<Engine, Dist>(state, a, b); |
| } |
| |
| template <typename Engine, typename Dist, int A> |
| void BM_Gamma(benchmark::State& state) { |
| using value_type = typename Dist::result_type; |
| volatile value_type a = static_cast<value_type>(A) / 100; |
| BM_Dist<Engine, Dist>(state, a); |
| } |
| |
| template <typename Engine, typename Dist, int A = 100> |
| void BM_Poisson(benchmark::State& state) { |
| volatile double a = static_cast<double>(A) / 100; |
| BM_Dist<Engine, Dist>(state, a); |
| } |
| |
| template <typename Engine, typename Dist, int Q = 2, int V = 1> |
| void BM_Zipf(benchmark::State& state) { |
| using value_type = typename Dist::result_type; |
| volatile double q = Q; |
| volatile double v = V; |
| BM_Dist<Engine, Dist>(state, std::numeric_limits<value_type>::max(), q, v); |
| } |
| |
| template <typename Engine, typename Dist> |
| void BM_Thread(benchmark::State& state) { |
| using value_type = typename Dist::result_type; |
| auto rng = make_engine<Engine>(); |
| Dist dis{}; |
| for (auto _ : state) { |
| benchmark::DoNotOptimize(dis(rng)); |
| } |
| state.SetBytesProcessed(sizeof(value_type) * state.iterations()); |
| } |
| |
| // NOTES: |
| // |
| // std::geometric_distribution is similar to the zipf distributions. |
| // The algorithm for the geometric_distribution is, basically, |
| // floor(log(1-X) / log(1-p)) |
| |
| // Normal benchmark suite |
| #define BM_BASIC(Engine) \ |
| BENCHMARK_TEMPLATE(BM_Construct, Engine, PrecompiledSeedSeq); \ |
| BENCHMARK_TEMPLATE(BM_Construct, Engine, std::seed_seq); \ |
| BENCHMARK_TEMPLATE(BM_Direct, Engine); \ |
| BENCHMARK_TEMPLATE(BM_Shuffle, Engine, 10); \ |
| BENCHMARK_TEMPLATE(BM_Shuffle, Engine, 100); \ |
| BENCHMARK_TEMPLATE(BM_Shuffle, Engine, 1000); \ |
| BENCHMARK_TEMPLATE(BM_ShuffleReuse, Engine, 100); \ |
| BENCHMARK_TEMPLATE(BM_ShuffleReuse, Engine, 1000); \ |
| BENCHMARK_TEMPLATE(BM_Dist, Engine, \ |
| absl::random_internal::FastUniformBits<uint32_t>); \ |
| BENCHMARK_TEMPLATE(BM_Dist, Engine, \ |
| absl::random_internal::FastUniformBits<uint64_t>); \ |
| BENCHMARK_TEMPLATE(BM_Dist, Engine, std::uniform_int_distribution<int32_t>); \ |
| BENCHMARK_TEMPLATE(BM_Dist, Engine, std::uniform_int_distribution<int64_t>); \ |
| BENCHMARK_TEMPLATE(BM_Dist, Engine, \ |
| absl::uniform_int_distribution<int32_t>); \ |
| BENCHMARK_TEMPLATE(BM_Dist, Engine, \ |
| absl::uniform_int_distribution<int64_t>); \ |
| BENCHMARK_TEMPLATE(BM_Large, Engine, \ |
| std::uniform_int_distribution<int32_t>); \ |
| BENCHMARK_TEMPLATE(BM_Large, Engine, \ |
| std::uniform_int_distribution<int64_t>); \ |
| BENCHMARK_TEMPLATE(BM_Large, Engine, \ |
| absl::uniform_int_distribution<int32_t>); \ |
| BENCHMARK_TEMPLATE(BM_Large, Engine, \ |
| absl::uniform_int_distribution<int64_t>); \ |
| BENCHMARK_TEMPLATE(BM_Dist, Engine, std::uniform_real_distribution<float>); \ |
| BENCHMARK_TEMPLATE(BM_Dist, Engine, std::uniform_real_distribution<double>); \ |
| BENCHMARK_TEMPLATE(BM_Dist, Engine, absl::uniform_real_distribution<float>); \ |
| BENCHMARK_TEMPLATE(BM_Dist, Engine, absl::uniform_real_distribution<double>) |
| |
| #define BM_COPY(Engine) BENCHMARK_TEMPLATE(BM_Generate, Engine) |
| |
| #define BM_THREAD(Engine) \ |
| BENCHMARK_TEMPLATE(BM_Thread, Engine, \ |
| absl::uniform_int_distribution<int64_t>) \ |
| ->ThreadPerCpu(); \ |
| BENCHMARK_TEMPLATE(BM_Thread, Engine, \ |
| absl::uniform_real_distribution<double>) \ |
| ->ThreadPerCpu(); \ |
| BENCHMARK_TEMPLATE(BM_Shuffle, Engine, 100)->ThreadPerCpu(); \ |
| BENCHMARK_TEMPLATE(BM_Shuffle, Engine, 1000)->ThreadPerCpu(); \ |
| BENCHMARK_TEMPLATE(BM_ShuffleReuse, Engine, 100)->ThreadPerCpu(); \ |
| BENCHMARK_TEMPLATE(BM_ShuffleReuse, Engine, 1000)->ThreadPerCpu() |
| |
| #define BM_EXTENDED(Engine) \ |
| /* -------------- Extended Uniform -----------------------*/ \ |
| BENCHMARK_TEMPLATE(BM_Small, Engine, \ |
| std::uniform_int_distribution<int32_t>); \ |
| BENCHMARK_TEMPLATE(BM_Small, Engine, \ |
| std::uniform_int_distribution<int64_t>); \ |
| BENCHMARK_TEMPLATE(BM_Small, Engine, \ |
| absl::uniform_int_distribution<int32_t>); \ |
| BENCHMARK_TEMPLATE(BM_Small, Engine, \ |
| absl::uniform_int_distribution<int64_t>); \ |
| BENCHMARK_TEMPLATE(BM_Small, Engine, std::uniform_real_distribution<float>); \ |
| BENCHMARK_TEMPLATE(BM_Small, Engine, \ |
| std::uniform_real_distribution<double>); \ |
| BENCHMARK_TEMPLATE(BM_Small, Engine, \ |
| absl::uniform_real_distribution<float>); \ |
| BENCHMARK_TEMPLATE(BM_Small, Engine, \ |
| absl::uniform_real_distribution<double>); \ |
| /* -------------- Other -----------------------*/ \ |
| BENCHMARK_TEMPLATE(BM_Dist, Engine, std::normal_distribution<double>); \ |
| BENCHMARK_TEMPLATE(BM_Dist, Engine, absl::gaussian_distribution<double>); \ |
| BENCHMARK_TEMPLATE(BM_Dist, Engine, std::exponential_distribution<double>); \ |
| BENCHMARK_TEMPLATE(BM_Dist, Engine, absl::exponential_distribution<double>); \ |
| BENCHMARK_TEMPLATE(BM_Poisson, Engine, std::poisson_distribution<int64_t>, \ |
| 100); \ |
| BENCHMARK_TEMPLATE(BM_Poisson, Engine, absl::poisson_distribution<int64_t>, \ |
| 100); \ |
| BENCHMARK_TEMPLATE(BM_Poisson, Engine, std::poisson_distribution<int64_t>, \ |
| 10 * 100); \ |
| BENCHMARK_TEMPLATE(BM_Poisson, Engine, absl::poisson_distribution<int64_t>, \ |
| 10 * 100); \ |
| BENCHMARK_TEMPLATE(BM_Poisson, Engine, std::poisson_distribution<int64_t>, \ |
| 13 * 100); \ |
| BENCHMARK_TEMPLATE(BM_Poisson, Engine, absl::poisson_distribution<int64_t>, \ |
| 13 * 100); \ |
| BENCHMARK_TEMPLATE(BM_Dist, Engine, \ |
| absl::log_uniform_int_distribution<int32_t>); \ |
| BENCHMARK_TEMPLATE(BM_Dist, Engine, \ |
| absl::log_uniform_int_distribution<int64_t>); \ |
| BENCHMARK_TEMPLATE(BM_Dist, Engine, std::geometric_distribution<int64_t>); \ |
| BENCHMARK_TEMPLATE(BM_Zipf, Engine, absl::zipf_distribution<uint64_t>); \ |
| BENCHMARK_TEMPLATE(BM_Zipf, Engine, absl::zipf_distribution<uint64_t>, 2, \ |
| 3); \ |
| BENCHMARK_TEMPLATE(BM_Bernoulli, Engine, std::bernoulli_distribution, \ |
| 257305); \ |
| BENCHMARK_TEMPLATE(BM_Bernoulli, Engine, absl::bernoulli_distribution, \ |
| 257305); \ |
| BENCHMARK_TEMPLATE(BM_Beta, Engine, absl::beta_distribution<double>, 65, \ |
| 41); \ |
| BENCHMARK_TEMPLATE(BM_Beta, Engine, absl::beta_distribution<double>, 99, \ |
| 330); \ |
| BENCHMARK_TEMPLATE(BM_Beta, Engine, absl::beta_distribution<double>, 150, \ |
| 150); \ |
| BENCHMARK_TEMPLATE(BM_Beta, Engine, absl::beta_distribution<double>, 410, \ |
| 580); \ |
| BENCHMARK_TEMPLATE(BM_Beta, Engine, absl::beta_distribution<float>, 65, 41); \ |
| BENCHMARK_TEMPLATE(BM_Beta, Engine, absl::beta_distribution<float>, 99, \ |
| 330); \ |
| BENCHMARK_TEMPLATE(BM_Beta, Engine, absl::beta_distribution<float>, 150, \ |
| 150); \ |
| BENCHMARK_TEMPLATE(BM_Beta, Engine, absl::beta_distribution<float>, 410, \ |
| 580); \ |
| BENCHMARK_TEMPLATE(BM_Gamma, Engine, std::gamma_distribution<float>, 199); \ |
| BENCHMARK_TEMPLATE(BM_Gamma, Engine, std::gamma_distribution<double>, 199) |
| |
| // ABSL Recommended interfaces. |
| BM_BASIC(absl::InsecureBitGen); // === pcg64_2018_engine |
| BM_BASIC(absl::BitGen); // === randen_engine<uint64_t>. |
| BM_THREAD(absl::BitGen); |
| BM_EXTENDED(absl::BitGen); |
| |
| // Instantiate benchmarks for multiple engines. |
| using randen_engine_64 = absl::random_internal::randen_engine<uint64_t>; |
| using randen_engine_32 = absl::random_internal::randen_engine<uint32_t>; |
| |
| // Comparison interfaces. |
| BM_BASIC(std::mt19937_64); |
| BM_COPY(std::mt19937_64); |
| BM_EXTENDED(std::mt19937_64); |
| BM_BASIC(randen_engine_64); |
| BM_COPY(randen_engine_64); |
| BM_EXTENDED(randen_engine_64); |
| |
| BM_BASIC(std::mt19937); |
| BM_COPY(std::mt19937); |
| BM_BASIC(randen_engine_32); |
| BM_COPY(randen_engine_32); |
| |
| } // namespace |