Thread Synchronization and Mutual Exclusion in C++

In modern programming, especially in multithreaded programming, thread synchronization and mutual exclusion are essential tools to ensure that multiple threads can safely and effectively access shared resources. In C++, we can use various mechanisms from the standard library to achieve this goal. This article will provide a detailed introduction to the basic concepts of thread synchronization and mutual exclusion, along with code examples demonstrating how to implement them in C++.

1. Basic Concepts

1.1 Thread

A thread is the smallest unit of execution in a program. A program has at least one main thread and may create multiple worker threads to execute tasks in parallel.

1.2 Concurrency and Race Conditions

When multiple threads access the same resource simultaneously, if appropriate measures are not taken, race conditions can occur, leading to data inconsistency or program crashes. Therefore, ensuring data consistency and integrity is crucial.

1.3 Synchronization and Mutual Exclusion

• Synchronization: Refers to coordinating the work of multiple processes or threads at certain times through some mechanism to avoid conflicts.
• Mutual Exclusion: A more specific form of synchronization that ensures that only one process can access shared resources at any given time.

2. Basic Synchronization Mechanisms in C++

C++11 introduced a series of features that natively support multithreaded programming, including <span>std::mutex</span>, <span>std::lock_guard</span>, and <span>std::condition_variable</span>. Below, we will introduce each of them and their usage.

2.1 std::mutex

<span>std::mutex</span> is a basic lock object used to protect critical sections. A critical section refers to the code segment that performs read and write operations on shared resources, during which exclusive access to the resource is required to prevent inconsistencies caused by other threads accessing it simultaneously.

Example Code:

#include <iostream>
#include <thread>
#include <mutex>
std::mutex mtx; // Create a global mutex object
int shared_resource = 0; // Define a shared variable
void increment() {
    for (int i = 0; i < 10000; ++i) {
        mtx.lock();       // Lock to prevent other threads from modifying shared_resource simultaneously
        ++shared_resource; 
        mtx.unlock();     // Unlock to allow other threads to use this resource
    }
}
int main() {
    std::thread t1(increment);
    std::thread t2(increment);
    t1.join();
    t2.join();
    std::cout << "Final value: " << shared_resource << std::endl;
    return 0;
}

Notes:

• It is essential to explicitly call <span>unlock()</span> after using <span>mtx</span>. Forgetting to unlock can lead to deadlocks.

2.2 std::lock_guard

To simplify the management of mutexes, the <span>std::lock_guard</span> class can be used to automatically manage locks following the RAII principle. When the lock_guard object goes out of scope, it automatically releases the associated mutex.

Example Code:

#include <iostream>
#include <thread>
#include <mutex>
std::mutex mtx; 
int shared_resource = 0;
void increment() {
    for (int i = 0; i < 10000; ++i) {
        std::lock_guard<std::mutex> lock(mtx); // Automatically locks and unlocks
        ++shared_resource;
    }
}
int main() {
    std::thread t1(increment);
    std::thread t2(increment);
    t1.join();
    t2.join();
    std::cout << "Final value: " << shared_resource << std::endl;
    return 0;
}

Advantages:

• Using <span>lock_guard</span> eliminates the need for explicit calls to <span>unlock()</span>, significantly reducing the potential for errors and improving code safety and maintainability.

2.3 Condition Variable

A condition variable allows you to wait until a certain condition is met before continuing execution. This is commonly used in the producer-consumer model. For example, a consumer needs to wait until products are produced when there are no products available for consumption.

Example Code:

#include <iostream>
#include <thread>
#include <queue>
#include <condition_variable>
std::queue<int> queue_data;
const unsigned int max_queue_size = 10;
std::mutex queue_mutex;
std::condition_variable cond_var;
void producer() {
   for(int i=0;i<20;++i){
      {
           std::unique_lock<std::mutex> lock(queue_mutex);
          while(queue_data.size() >= max_queue_size) {
               cond_var.wait(lock);
           }
          queue_data.push(i);
          lock.unlock();
      }
      cond_var.notify_one();
    }
}
void consumer(){
   for(int i=0;i<20;++i){
      int data;
      {
           std::unique_lock<std::mutex> lock(queue_mutex);
         while(queue_data.empty()) {
               cond_var.wait(lock);
            }
                  data = queue_data.front();
         queue_data.pop();
         lock.unlock();
          }
       cond_var.notify_one();
         printf("Consumed: %d\n",data);
   }
}
int main(){
   auto p_thread=std::thread(producer);
   auto c_thread=std::thread(consumer);
   p_thread.join();
   c_thread.join();
return  0;
}

Conclusion

This article introduced the basic communication means in C++, including graphical methods for simple queue processing, complex data protection methods, and the underlying principles. Understanding these basic tools will help you build safer and more efficient multithreaded applications. In practical applications, choose the appropriate method or a combination of methods to ensure data consistency, effectively enhancing parallel processing capabilities. At the same time, be sure to consider performance overhead to make your design both accurate and efficient.