C++ Memory Model: from C++11 to C++23 - Alex Dathskovsky - CppCon 2023

C++ memory model explained: from C++11 to C++23. Learn about compiler reordering, atomic operations, memory barriers, and synchronization techniques to write correct and efficient multithreaded code.

Key takeaways

C++ memory model is important for multithreaded programming
We can store data in registers as well as memory
Compiler can reorder instructions, but not across locks or atomic operations *_compiler Additionally, compiler can do copy elision, which can be beneficial
C++20 introduces std::atomic for shared pointers
std::atomic_thread_fence and std::memory_order can be used to control memory model
volatile keyword is not a magic solution, but can be used to prevent compiler optimizations
Memory barriers can be used to ensure sequential consistency
Latches and barriers are different, but both are used for synchronization
stop_source and stop_token can be used together to control thread execution
C++ has many tools for synchronization, but also can lead to complex code
Understanding the memory model is important for avoiding data races and ensuring correct program behavior
Memory order relaxed means that some operations can be reordered, but still ensure the correct result
Atomic operations are fundamental for multithreaded programming
Simple thread synchronization can be achieved using std::atomic_thread_fence
Compiler optimizations can be used to improve performance, but must be carefully managed
Multithreaded programming requires careful attention to memory model and synchronization
std::shared_ptr can be used with std::atomic for shared ownership
Understanding branch prediction is important for optimizing code
C++ standard library provides many useful tools for multithreaded programming, such as std::thread, std::mutex, std::atomic and more.

C++ Memory Model: from C++11 to C++23 - Alex Dathskovsky - CppCon 2023

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