Atomic memory access

本文介绍了GCC提供的内置原子操作函数,这些函数通过内存屏障(memory barrier)确保了在多核CPU环境下内存访问的原子性。文章解释了full barrier的概念,并探讨了如何在多进程环境中使用这些函数来保证内存访问的同步。

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Gcc 提供了一些built in的函数,以实现内存访问的原子性:具体函数在 http://gcc.gnu.org/onlinedocs/gcc-4.1.2/gcc/Atomic-Builtins.html

In most cases, these builtins are considered a full barrier. That is, no memory operand will be moved across the operation, either forward or backward. Further, instructions will be issued as necessary to prevent the processor from speculating loads across the operation and from queuing stores after the operation. 

full barrier 就是说明了这些函数是通过cpu以memory barrier方式访问内存的,所以即使在多核CPU下,这些函数也可保证其原子性. 

也就隐含的说明了,不管是单进程还是多进程只要是对函数中ptr参数的内存地址的访问,都是原子进行的——如ptr是在共享内存中,那多个进程对ptr所指向的内存的访问都是原子进行的,保证了在多个进程间的同步,即使在多核cpu下.

Memory barrier: http://en.wikipedia.org/wiki/Memory_barrier

### Atomic Operations in Programming and Concurrency In concurrent programming, atomic operations play a crucial role in ensuring data integrity when multiple threads access shared resources simultaneously. An operation is considered atomic if it completes instantly from the perspective of other concurrently executing threads or processes. Atomicity guarantees that an operation will not be interrupted once started until completion. This prevents race conditions where two or more threads attempt to modify the same variable at nearly the same time leading to unpredictable outcomes[^1]. #### Usage of Atomics To handle synchronization without traditional locks, C++ provides `std::atomic` types within its standard library. These allow performing read-modify-write actions atomically: ```cpp #include <atomic> #include <thread> std::atomic<int> counter{0}; void increment_counter() { for (int i = 0; i < 1000; ++i) { counter.fetch_add(1, std::memory_order_relaxed); } } int main() { const unsigned thread_count = 10; std::vector<std::thread> threads; for (unsigned i = 0; i < thread_count; ++i) { threads.emplace_back(increment_counter); } for (auto& t : threads) { t.join(); } // Expected value should be close to 10 * 1000 = 10000 std::cout << "Counter: " << counter.load() << '\n'; } ``` The above example demonstrates how `fetch_add()` method performs addition as an indivisible action across different threads safely avoiding any potential conflicts during updates[^2]. #### Memory Ordering Constraints When working with atomics, memory ordering constraints dictate what changes become visible to other threads after an atomic operation has completed. The options range from very weak (`memory_order_relaxed`) allowing maximum performance but minimal visibility guarantees up to fully synchronized (`memory_order_seq_cst`) providing strictest consistency between all involved parties[^3]. For instance, setting appropriate barriers ensures correct program behavior even under relaxed orderings by preventing certain instructions from being reordered around these points thus preserving intended semantics despite optimizations performed by compilers or hardware architectures. #### Benefits Over Traditional Synchronization Mechanisms Using atomic variables offers several advantages over conventional locking mechanisms such as mutexes including better scalability due to reduced contention among threads accessing non-overlapping parts of state space independently alongside lower overhead costs associated with acquiring/releases compared to full-fledged mutual exclusions constructs[^4]. However, developers must carefully design algorithms taking into account possible limitations imposed by chosen levels of coarseness versus fineness regarding granularity choices made concerning protected regions since overly broad scopes could negate some benefits derived otherwise through finer control offered here instead[^5].
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