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What are the lock-free programming techniques in C++?

Jun 05, 2024 pm 03:35 PM
c++ Lock-free programming

Lock-free programming is a multi-threaded programming paradigm that avoids the use of lock mechanisms to improve concurrency. Lock-free programming techniques in C++ include: Atomic operations: Provides uninterruptible basic operations such as atomic types and operations such as fetch_add. Lock-free data structures: Data structures that do not use locks to control concurrent access, such as CAS queues, lock-free stacks, and CAS-based linked lists. Lock-free hash map: Use cuckoo hash map or chain address hash map to achieve lock-free key-value pair storage and retrieval.

What are the lock-free programming techniques in C++?

Lock-free programming technology in C++

Introduction

Lock-free programming Is a paradigm of multi-threaded programming that does not rely on a lock mechanism to synchronize threads. This allows programs to avoid deadlocks and improve concurrency. This article will explore the lock-free programming techniques available in C++.

Atomic operations

Atomic operations are basic operations that cannot be interrupted. C++11 introduces the atomic library, which provides a series of atomic types and operations, such as:

std::atomic<int> counter;
counter.fetch_add(1);
int value = counter.load();
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Lock-free data structure

Lock-free data structure does not require locks Control concurrent access. Some common lock-free data structures include:

  • CAS Queue (Concurrent Queue): Queue based on compare-and-swap (CAS) operation.
  • Lock-free Stack: A stack implemented using atomic swap operations.
  • Linked List: CAS-based linked list, providing thread-safe insertion and deletion operations.

Lock-free hash map

Lock-free hash map is a type of lock-free data structure that allows keys to be stored and retrieved in a lock-free manner value pair. Common lock-free hash map implementations include:

  • cuckoo Hash Map: Use two hash tables to eliminate write-time conflicts.
  • Chain address method hash mapping: Use a linked list to handle conflicts.

Practical Case

Consider the following example of using a CAS queue to implement the producer-consumer pattern:

#include <atomic>
#include <queue>
#include <thread>

std::atomic_bool producer_done{false};
std::queue<int> queue;

void producer() {
    for (int i = 0; i < 1000; i++) {
        while (!queue.empty())
            std::this_thread::yield();
        queue.push(i);
    }
    producer_done = true;
}

void consumer() {
    while (!producer_done || !queue.empty()) {
        int value;
        if (queue.pop(value))
            std::cout << value << std::endl;
    }
}

int main() {
    std::thread producer_thread(producer);
    std::thread consumer_thread(consumer);
    producer_thread.join();
    consumer_thread.join();
    return 0;
}
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In this example, Producer threads use CAS queues to insert data into the queue in a lock-free manner, while consumer threads read data from the queue in a lock-free manner.

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