How to optimize the performance of multi-threaded programs in C++?

Effective techniques for optimizing C++ multi-threaded performance include: limiting the number of threads to avoid resource contention. Use lightweight mutex locks to reduce contention. Optimize the scope of the lock and minimize the waiting time. Use lock-free data structures to improve concurrency. Avoid busy waiting and notify threads of resource availability through events.

Guidelines for optimizing the performance of multi-threaded programs in C++

In multi-threaded programs, performance optimization is crucial because it The overall efficiency of the program can be significantly improved. This article explores effective techniques for optimizing the performance of multithreaded programs in C++ and provides practical examples to demonstrate the effects of each technique.

1. Limit the number of threads

Creating too many threads will compete for system resources and lead to performance degradation. Determine the optimal number of threads your application requires and adjust it as needed.

2. Use lightweight mutex locks

Mutex locks are used to protect shared resources, but they may cause performance overhead. Using lightweight mutexes, such as std::recursive_mutex, can reduce contention and improve performance.

3. Optimize the lock scope

Try to limit the lock scope to the minimum necessary part. This will reduce the time threads wait for the lock to be released, thus improving concurrency.

4. Use lock-free data structures

Some data structures, such as std::atomic, allow concurrent access without locking. These structures provide better performance when sharing large amounts of data.

5. Avoid busy waiting

Busy waiting involves constantly checking the status of a resource while waiting for it. This wastes CPU time and reduces overall performance. Use events or semaphores to notify threads when resources are available to avoid busy waits.

Practical case:

Consider a program that needs to process a large file list concurrently. We can use the following optimization techniques:

• Create a separate thread for each file and limit the number of threads to avoid contention.
• Use std::recursive_mutex to protect the file list.
• Limit the scope of the lock to the smallest scope required to process each file.
• Use std::atomic to track the number of files processed.
• Use events to notify threads that all files have been processed.

By implementing these optimizations, we managed to significantly improve the performance of the program, allowing it to process the same number of files faster.

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