Implementing multithreading and concurrency in modernized C++ code

11 Oct 2023

Multithreading

In today’s era of computing, harnessing the power of multiple cores and achieving efficient parallelization is essential for developing high-performance software. One of the best ways to achieve this in C++ is through multithreading and concurrency. In this blog post, we will explore how to implement multithreading and concurrency in modernized C++ code to make the most of today’s hardware.

Introduction
What is Multithreading and Concurrency?
The Standard C++ Thread Library
Creating and Managing Threads
Synchronization and Thread Safety
Parallel Algorithms in C++17
Conclusion

Introduction

Multithreading refers to the ability of an application to perform multiple tasks concurrently. Each task runs independently and can have its own program counter, stack, and other resources. Concurrency, on the other hand, is a broader concept that encompasses managing and coordinating multiple tasks to achieve efficient execution.

Modernized C++ (C++11 and later versions) introduced many features and libraries to support multithreading and concurrency, making it easier and safer to develop parallel applications.

What is Multithreading and Concurrency?

Multithreading allows different parts of a program to execute simultaneously, taking advantage of multiple CPU cores. By dividing a task into smaller subtasks and distributing them among threads, we can achieve faster execution and better utilization of available resources.

Concurrency, on the other hand, focuses on managing and coordinating multiple tasks, even if they do not run simultaneously. It involves synchronization, communication between threads, and avoiding race conditions. Concurrency is essential when dealing with shared resources or critical sections of code.

The Standard C++ Thread Library

Starting from C++11, the standard library provides a powerful set of classes and functions for working with threads and concurrency. The threading-related classes are defined in the <thread> header.

Some key classes provided by the standard C++ thread library are:

std::thread: Represents a single thread of execution.
std::mutex: Provides mutual exclusion, allowing exclusive access to shared resources through lock and unlock operations.
std::condition_variable: Allows threads to synchronize their execution and wait for specific conditions.
std::atomic: Provides atomic operations on shared variables, ensuring thread safety.

Creating and Managing Threads

To create a new thread, we can instantiate an std::thread object and pass a callable object to its constructor. The callable object can be a function pointer, a function object, or a lambda expression. Here’s an example of creating and executing a thread:

#include <iostream>
#include <thread>

void threadFunction()
{
    std::cout << "Hello from thread!" << std::endl;
}

int main()
{
    std::thread myThread(threadFunction);
    myThread.join(); // Wait for the thread to complete

    std::cout << "Back in main thread." << std::endl;
    return 0;
}

In the above code, we define a function threadFunction that will be executed by the new thread. We then create a new std::thread object myThread and pass threadFunction as an argument to its constructor. Finally, we call join() on the thread object to wait for the thread to complete its execution.

Synchronization and Thread Safety

When working with multiple threads and shared resources, synchronization is crucial to avoid race conditions, data races, and other concurrency issues. The standard C++ library provides various mechanisms for synchronization, such as std::mutex and std::condition_variable.

Using a mutex, we can ensure that only one thread can access a shared resource at a time. Here’s an example that demonstrates the use of a mutex for thread-safe access:

#include <iostream>
#include <thread>
#include <mutex>

std::mutex mtx;

void threadFunction()
{
    std::lock_guard<std::mutex> lock(mtx); // Locks the mutex
    std::cout << "Hello from thread!" << std::endl;
} // Automatically unlocks the mutex when lock goes out of scope

int main()
{
    std::thread myThread(threadFunction);
    myThread.join();

    std::cout << "Back in main thread." << std::endl;
    return 0;
}

In the above code, we use an std::mutex object mtx to protect the critical section, which is the std::cout statement. By using std::lock_guard<std::mutex>, we ensure that the mutex is locked when executing the critical section and automatically unlocked when the lock object goes out of scope.

Parallel Algorithms in C++17

Starting from C++17, the standard library provides parallel versions of some algorithms in the <algorithm> header. These parallel algorithms can automatically execute in parallel, utilizing multiple threads to speed up the computation.

For example, the std::for_each algorithm can be executed in parallel using std::execution::par as the execution policy:

#include <iostream>
#include <vector>
#include <algorithm>
#include <execution>

int main()
{
    std::vector<int> vec = {1, 2, 3, 4, 5};

    std::for_each(std::execution::par, vec.begin(), vec.end(), [](int num) {
        std::cout << num << " ";
    });

    return 0;
}

In the above code, std::execution::par is used as the execution policy to indicate parallel execution. This enables the algorithm to execute on multiple threads, taking advantage of available cores.

Conclusion

Multithreading and concurrency are powerful techniques for achieving efficient parallel execution in modern C++ code. By using the standard C++ thread library and features introduced in C++11 and later versions, developers can easily implement parallelism, synchronize access to shared resources, and make use of parallel algorithms. Understanding and utilizing these techniques can significantly improve the performance of C++ applications in today’s multi-core systems.

We hope this blog post has provided you with a solid foundation for implementing multithreading and concurrency in your modern C++ code. Happy coding!

#C++ #Multithreading

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