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authorGravatar Abseil Team <absl-team@google.com>2019-08-08 10:56:58 -0700
committerGravatar CJ Johnson <johnsoncj@google.com>2019-08-08 14:19:45 -0400
commitaa844899c937bde5d2b24f276b59997e5b668bde (patch)
treecd18e64150abc74b85bbbf6abf990f66fa47cacd /absl/random/benchmarks.cc
parentfcb104594b0bb4b8ac306cb2f55ecdad40974683 (diff)
Creation of LTS branch "lts_2019_08_08"20190808
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diff --git a/absl/random/benchmarks.cc b/absl/random/benchmarks.cc
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+// 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() {}
+
+ 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