255 lines
10 KiB
C++
255 lines
10 KiB
C++
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// Copyright 2018 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 <string>
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#include <type_traits>
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#include <typeindex>
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#include <utility>
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#include <vector>
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#include "absl/base/attributes.h"
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#include "absl/hash/hash.h"
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#include "absl/random/random.h"
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#include "absl/strings/cord.h"
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#include "absl/strings/cord_test_helpers.h"
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#include "absl/strings/string_view.h"
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#include "benchmark/benchmark.h"
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namespace {
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using absl::Hash;
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template <template <typename> class H, typename T>
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void RunBenchmark(benchmark::State& state, T value) {
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H<T> h;
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for (auto _ : state) {
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benchmark::DoNotOptimize(value);
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benchmark::DoNotOptimize(h(value));
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}
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}
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} // namespace
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template <typename T>
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using AbslHash = absl::Hash<T>;
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class TypeErasedInterface {
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public:
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virtual ~TypeErasedInterface() = default;
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template <typename H>
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friend H AbslHashValue(H state, const TypeErasedInterface& wrapper) {
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state = H::combine(std::move(state), std::type_index(typeid(wrapper)));
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wrapper.HashValue(absl::HashState::Create(&state));
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return state;
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}
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private:
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virtual void HashValue(absl::HashState state) const = 0;
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};
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template <typename T>
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struct TypeErasedAbslHash {
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class Wrapper : public TypeErasedInterface {
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public:
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explicit Wrapper(const T& value) : value_(value) {}
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private:
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void HashValue(absl::HashState state) const override {
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absl::HashState::combine(std::move(state), value_);
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}
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const T& value_;
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};
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size_t operator()(const T& value) {
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return absl::Hash<Wrapper>{}(Wrapper(value));
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}
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};
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template <typename FuncType>
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inline FuncType* ODRUseFunction(FuncType* ptr) {
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volatile FuncType* dummy = ptr;
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return dummy;
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}
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absl::Cord FlatCord(size_t size) {
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absl::Cord result(std::string(size, 'a'));
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result.Flatten();
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return result;
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}
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absl::Cord FragmentedCord(size_t size) {
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const size_t orig_size = size;
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std::vector<std::string> chunks;
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size_t chunk_size = std::max<size_t>(1, size / 10);
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while (size > chunk_size) {
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chunks.push_back(std::string(chunk_size, 'a'));
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size -= chunk_size;
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}
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if (size > 0) {
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chunks.push_back(std::string(size, 'a'));
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}
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absl::Cord result = absl::MakeFragmentedCord(chunks);
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(void) orig_size;
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assert(result.size() == orig_size);
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return result;
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}
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// Generates a benchmark and a codegen method for the provided types. The
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// codegen method provides a well known entrypoint for dumping assembly.
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#define MAKE_BENCHMARK(hash, name, ...) \
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namespace { \
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void BM_##hash##_##name(benchmark::State& state) { \
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RunBenchmark<hash>(state, __VA_ARGS__); \
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} \
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BENCHMARK(BM_##hash##_##name); \
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} \
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size_t Codegen##hash##name(const decltype(__VA_ARGS__)& arg); \
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size_t Codegen##hash##name(const decltype(__VA_ARGS__)& arg) { \
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return hash<decltype(__VA_ARGS__)>{}(arg); \
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} \
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bool absl_hash_test_odr_use##hash##name = \
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ODRUseFunction(&Codegen##hash##name);
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MAKE_BENCHMARK(AbslHash, Int32, int32_t{});
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MAKE_BENCHMARK(AbslHash, Int64, int64_t{});
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MAKE_BENCHMARK(AbslHash, Double, 1.2);
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MAKE_BENCHMARK(AbslHash, DoubleZero, 0.0);
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MAKE_BENCHMARK(AbslHash, PairInt32Int32, std::pair<int32_t, int32_t>{});
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MAKE_BENCHMARK(AbslHash, PairInt64Int64, std::pair<int64_t, int64_t>{});
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MAKE_BENCHMARK(AbslHash, TupleInt32BoolInt64,
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std::tuple<int32_t, bool, int64_t>{});
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MAKE_BENCHMARK(AbslHash, String_0, std::string());
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MAKE_BENCHMARK(AbslHash, String_10, std::string(10, 'a'));
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MAKE_BENCHMARK(AbslHash, String_30, std::string(30, 'a'));
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MAKE_BENCHMARK(AbslHash, String_90, std::string(90, 'a'));
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MAKE_BENCHMARK(AbslHash, String_200, std::string(200, 'a'));
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MAKE_BENCHMARK(AbslHash, String_5000, std::string(5000, 'a'));
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MAKE_BENCHMARK(AbslHash, Cord_Flat_0, absl::Cord());
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MAKE_BENCHMARK(AbslHash, Cord_Flat_10, FlatCord(10));
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MAKE_BENCHMARK(AbslHash, Cord_Flat_30, FlatCord(30));
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MAKE_BENCHMARK(AbslHash, Cord_Flat_90, FlatCord(90));
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MAKE_BENCHMARK(AbslHash, Cord_Flat_200, FlatCord(200));
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MAKE_BENCHMARK(AbslHash, Cord_Flat_5000, FlatCord(5000));
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MAKE_BENCHMARK(AbslHash, Cord_Fragmented_200, FragmentedCord(200));
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MAKE_BENCHMARK(AbslHash, Cord_Fragmented_5000, FragmentedCord(5000));
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MAKE_BENCHMARK(AbslHash, VectorInt64_10, std::vector<int64_t>(10));
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MAKE_BENCHMARK(AbslHash, VectorInt64_100, std::vector<int64_t>(100));
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MAKE_BENCHMARK(AbslHash, VectorDouble_10, std::vector<double>(10, 1.1));
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MAKE_BENCHMARK(AbslHash, VectorDouble_100, std::vector<double>(100, 1.1));
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MAKE_BENCHMARK(AbslHash, PairStringString_0,
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std::make_pair(std::string(), std::string()));
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MAKE_BENCHMARK(AbslHash, PairStringString_10,
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std::make_pair(std::string(10, 'a'), std::string(10, 'b')));
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MAKE_BENCHMARK(AbslHash, PairStringString_30,
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std::make_pair(std::string(30, 'a'), std::string(30, 'b')));
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MAKE_BENCHMARK(AbslHash, PairStringString_90,
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std::make_pair(std::string(90, 'a'), std::string(90, 'b')));
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MAKE_BENCHMARK(AbslHash, PairStringString_200,
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std::make_pair(std::string(200, 'a'), std::string(200, 'b')));
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MAKE_BENCHMARK(AbslHash, PairStringString_5000,
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std::make_pair(std::string(5000, 'a'), std::string(5000, 'b')));
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MAKE_BENCHMARK(TypeErasedAbslHash, Int32, int32_t{});
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MAKE_BENCHMARK(TypeErasedAbslHash, Int64, int64_t{});
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MAKE_BENCHMARK(TypeErasedAbslHash, PairInt32Int32,
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std::pair<int32_t, int32_t>{});
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MAKE_BENCHMARK(TypeErasedAbslHash, PairInt64Int64,
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std::pair<int64_t, int64_t>{});
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MAKE_BENCHMARK(TypeErasedAbslHash, TupleInt32BoolInt64,
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std::tuple<int32_t, bool, int64_t>{});
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MAKE_BENCHMARK(TypeErasedAbslHash, String_0, std::string());
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MAKE_BENCHMARK(TypeErasedAbslHash, String_10, std::string(10, 'a'));
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MAKE_BENCHMARK(TypeErasedAbslHash, String_30, std::string(30, 'a'));
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MAKE_BENCHMARK(TypeErasedAbslHash, String_90, std::string(90, 'a'));
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MAKE_BENCHMARK(TypeErasedAbslHash, String_200, std::string(200, 'a'));
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MAKE_BENCHMARK(TypeErasedAbslHash, String_5000, std::string(5000, 'a'));
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MAKE_BENCHMARK(TypeErasedAbslHash, VectorDouble_10,
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std::vector<double>(10, 1.1));
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MAKE_BENCHMARK(TypeErasedAbslHash, VectorDouble_100,
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std::vector<double>(100, 1.1));
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// The latency benchmark attempts to model the speed of the hash function in
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// production. When a hash function is used for hashtable lookups it is rarely
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// used to hash N items in a tight loop nor on constant sized strings. Instead,
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// after hashing there is a potential equality test plus a (usually) large
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// amount of user code. To simulate this effectively we introduce a data
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// dependency between elements we hash by using the hash of the Nth element as
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// the selector of the N+1th element to hash. This isolates the hash function
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// code much like in production. As a bonus we use the hash to generate strings
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// of size [1,N] (instead of fixed N) to disable perfect branch predictions in
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// hash function implementations.
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namespace {
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// 16kb fits in L1 cache of most CPUs we care about. Keeping memory latency low
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// will allow us to attribute most time to CPU which means more accurate
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// measurements.
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static constexpr size_t kEntropySize = 16 << 10;
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static char entropy[kEntropySize + 1024];
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ABSL_ATTRIBUTE_UNUSED static const bool kInitialized = [] {
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absl::BitGen gen;
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static_assert(sizeof(entropy) % sizeof(uint64_t) == 0, "");
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for (int i = 0; i != sizeof(entropy); i += sizeof(uint64_t)) {
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auto rand = absl::Uniform<uint64_t>(gen);
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memcpy(&entropy[i], &rand, sizeof(uint64_t));
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}
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return true;
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}();
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} // namespace
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template <class T>
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struct PodRand {
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static_assert(std::is_pod<T>::value, "");
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static_assert(kEntropySize + sizeof(T) < sizeof(entropy), "");
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T Get(size_t i) const {
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T v;
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memcpy(&v, &entropy[i % kEntropySize], sizeof(T));
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return v;
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}
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};
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template <size_t N>
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struct StringRand {
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static_assert(kEntropySize + N < sizeof(entropy), "");
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absl::string_view Get(size_t i) const {
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// This has a small bias towards small numbers. Because max N is ~200 this
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// is very small and prefer to be very fast instead of absolutely accurate.
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// Also we pass N = 2^K+1 so that mod reduces to a bitand.
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size_t s = (i % (N - 1)) + 1;
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return {&entropy[i % kEntropySize], s};
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}
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};
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#define MAKE_LATENCY_BENCHMARK(hash, name, ...) \
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namespace { \
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void BM_latency_##hash##_##name(benchmark::State& state) { \
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__VA_ARGS__ r; \
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hash<decltype(r.Get(0))> h; \
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size_t i = 871401241; \
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for (auto _ : state) { \
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benchmark::DoNotOptimize(i = h(r.Get(i))); \
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} \
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} \
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BENCHMARK(BM_latency_##hash##_##name); \
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} // namespace
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MAKE_LATENCY_BENCHMARK(AbslHash, Int32, PodRand<int32_t>);
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MAKE_LATENCY_BENCHMARK(AbslHash, Int64, PodRand<int64_t>);
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MAKE_LATENCY_BENCHMARK(AbslHash, String9, StringRand<9>);
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MAKE_LATENCY_BENCHMARK(AbslHash, String33, StringRand<33>);
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MAKE_LATENCY_BENCHMARK(AbslHash, String65, StringRand<65>);
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MAKE_LATENCY_BENCHMARK(AbslHash, String257, StringRand<257>);
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