packaged_task experiments report
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@@ -47,3 +47,6 @@ target_link_libraries(block_choice ${PIP_LIBRARY})
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add_executable(smbusdata_crash_test experiments/smbusdata_crash_test.cpp)
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target_link_libraries(smbusdata_crash_test SMBricks_shared ${PIP_LIBRARY} ${PIP_CONCURRENT_LIBRARY} ${PIP_CRYPT_LIBRARY})
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add_executable(packaged_task experiments/packaged_task.cpp)
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target_link_libraries(packaged_task SMBricks_shared ${PIP_LIBRARY} ${PIP_CONCURRENT_LIBRARY} ${PIP_CRYPT_LIBRARY})
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88
experiments/packaged_task.cpp
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88
experiments/packaged_task.cpp
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@@ -0,0 +1,88 @@
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#include <iostream>
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#include <memory>
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#include <future>
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#include <queue>
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/**
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* @brief Wrapper for custom invoke operator available function types.
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* @note Source from: "Энтони Уильямс, Параллельное программирование на С++ в действии. Практика разработки многопоточных
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* программ. Пер. с англ. Слинкин А. А. - M.: ДМК Пресс, 2012 - 672c.: ил." (page 387)
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*/
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class FunctionWrapper {
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struct ImplBase {
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virtual void call() = 0;
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virtual ~ImplBase() = default;
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};
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std::unique_ptr<ImplBase> impl;
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template<typename F>
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struct ImplType: ImplBase {
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F f;
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explicit ImplType(F&& f): f(std::forward<F>(f)) {}
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void call() final { f(); }
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};
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public:
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template<typename F, typename = std::enable_if<!std::is_same<F, FunctionWrapper>::value> >
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explicit FunctionWrapper(F&& f): impl(new ImplType<F>(std::forward<F>(f))) {}
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void operator()() { impl->call(); }
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FunctionWrapper() = default;
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FunctionWrapper(FunctionWrapper&& other) noexcept : impl(std::move(other.impl)) {}
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FunctionWrapper& operator=(FunctionWrapper&& other) noexcept {
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impl = std::move(other.impl);
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return *this;
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}
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FunctionWrapper(const FunctionWrapper&) = delete;
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FunctionWrapper& operator=(const FunctionWrapper&) = delete;
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};
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template<typename Func>
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float check_performance(Func test_function) {
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auto start = std::chrono::high_resolution_clock::now();
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for (int i = 0; i < 5 * 1000 * 1000; ++i) {
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test_function();
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}
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auto end = std::chrono::high_resolution_clock::now();
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return std::chrono::duration_cast<std::chrono::microseconds>(end - start).count() / 1000.f;
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}
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int main() {
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std::queue<FunctionWrapper> queue;
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queue.push(std::move(FunctionWrapper()));
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FunctionWrapper functionWrapper = std::move(queue.front());
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queue.pop();
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auto test_lambda = [](){ int i = 0; while(i < 100) i++; };
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float direct_call_performance = check_performance([&test_lambda](){
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std::unique_ptr<std::function<void()> > test_function_p(new std::function<void()>(test_lambda));
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test_function_p->operator()();
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});
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std::cout << "Direct call by pointer: " << direct_call_performance << " ms" << std::endl;
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float lambda_wrapper_performance = check_performance([&test_lambda](){
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auto copy_lambda = test_lambda;
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FunctionWrapper wrapper(std::move(copy_lambda));
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wrapper();
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});
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std::cout << "Lambda with function wrapper: " << lambda_wrapper_performance << " ms" << std::endl;
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float std_function_wrapper_performance = check_performance([&test_lambda](){
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std::function<void()> test_function(test_lambda);
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FunctionWrapper wrapper(std::move(test_function));
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wrapper();
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});
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std::cout << "std function with function wrapper: " << std_function_wrapper_performance << " ms" << std::endl;
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float packaged_task_wrapper_performance = check_performance([&test_lambda](){
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std::packaged_task<void()> test_packaged_task(test_lambda);
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FunctionWrapper wrapper(test_packaged_task);
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wrapper();
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});
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std::cout << "Packaged task with function wrapper: " << packaged_task_wrapper_performance << " ms" << std::endl;
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return 0;
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}
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12
readme.md
12
readme.md
@@ -31,6 +31,18 @@ stdMutex: 25.5425 ms
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stdAtomic: 16.6967 ms
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```
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### Эксперименты с std::packaged_task и др. способами хранения функций
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В тестах все способы кроме `std::packaged_task` показали приблизительно одинаковый результат. Вероятно, много ресурсов
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расходуется на создание пары future-promise.
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```cmd
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Direct call by pointer: 261.328 ms
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Lambda with function wrapper: 241.38 ms
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std function with function wrapper: 266.289 ms
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Packaged task with function wrapper: 2476.41 ms
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```
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## Результаты на Linux
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Измерения производительности проводились с `-O3` оптимизацией.
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