Using std::atomic
When sharing data between threads in C++, you must ensure that all updates are visible and safe. The std::atomic template class enables lock-free operations—such as reading, writing, and simple arithmetic—on shared variables without using mutexes. This reduces overhead and avoids contention, improving performance in scenarios with simple shared state.
However, std::atomic is not a replacement for mutexes in all situations. It works best for independent operations on single variables, like counters or flags. For complex data structures or multi-step operations, mutexes are still required to ensure consistency.
std::atomic improves efficiency but only for operations the hardware can perform atomically. It still requires careful design to avoid subtle concurrency bugs.
main.cpp
1234567891011121314151617181920212223242526#include <iostream> #include <thread> #include <vector> #include <atomic> int main() { std::atomic<int> counter{0}; const int num_threads = 10; const int increments_per_thread = 1000; std::vector<std::thread> threads; for (int i = 0; i < num_threads; ++i) { threads.emplace_back([&counter, increments_per_thread]() { for (int j = 0; j < increments_per_thread; ++j) counter.fetch_add(1, std::memory_order_relaxed); }); } for (auto& t : threads) t.join(); std::cout << "Final counter value: " << counter.load() << std::endl; }
Lock-free operations allow threads to make progress independently, even if other threads are delayed. In lock-free code, at least one thread will complete its operation in a finite number of steps, regardless of what other threads are doing.
Wait-free operations are even stronger: every thread will complete its operation in a finite number of steps, no matter what other threads are doing. All wait-free algorithms are lock-free, but not all lock-free algorithms are wait-free.
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When sharing data between threads in C++, you must ensure that all updates are visible and safe. The std::atomic template class enables lock-free operations—such as reading, writing, and simple arithmetic—on shared variables without using mutexes. This reduces overhead and avoids contention, improving performance in scenarios with simple shared state.
However, std::atomic is not a replacement for mutexes in all situations. It works best for independent operations on single variables, like counters or flags. For complex data structures or multi-step operations, mutexes are still required to ensure consistency.
std::atomic improves efficiency but only for operations the hardware can perform atomically. It still requires careful design to avoid subtle concurrency bugs.
main.cpp
1234567891011121314151617181920212223242526#include <iostream> #include <thread> #include <vector> #include <atomic> int main() { std::atomic<int> counter{0}; const int num_threads = 10; const int increments_per_thread = 1000; std::vector<std::thread> threads; for (int i = 0; i < num_threads; ++i) { threads.emplace_back([&counter, increments_per_thread]() { for (int j = 0; j < increments_per_thread; ++j) counter.fetch_add(1, std::memory_order_relaxed); }); } for (auto& t : threads) t.join(); std::cout << "Final counter value: " << counter.load() << std::endl; }
Lock-free operations allow threads to make progress independently, even if other threads are delayed. In lock-free code, at least one thread will complete its operation in a finite number of steps, regardless of what other threads are doing.
Wait-free operations are even stronger: every thread will complete its operation in a finite number of steps, no matter what other threads are doing. All wait-free algorithms are lock-free, but not all lock-free algorithms are wait-free.
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