Parallel processing is an important technique in modern programming to improve the efficiency of tasks. In this blog post, we will explore the usage of the std::jthread class, introduced in C++20, for parallel file processing.

What is std::jthread?

std::jthread is a new addition to the C++ standard library in C++20. It is a lightweight wrapper around the std::thread class that provides a safe and easy way to manage thread lifetimes and join them automatically. The j in std::jthread stands for “joinable”.

Parallel File Processing

File processing is a common task in many applications. Whether it’s reading logs, processing large datasets, or performing data analysis, file processing can be time-consuming. Parallelizing this task can greatly reduce the execution time by utilizing multiple threads.

Let’s illustrate how to use std::jthread for parallel file processing with an example.

#include <iostream>
#include <fstream>
#include <vector>
#include <string>
#include <filesystem>
#include <algorithm>
#include <execution>
#include <chrono>

void processFile(const std::filesystem::path& filePath) {
    std::ifstream file(filePath);
    // Process the file here
    // ...
}

void processFilesInParallel(const std::vector<std::filesystem::path>& filePaths) {
    std::vector<std::jthread> threads;
    
    for (const auto& filePath : filePaths) {
        threads.emplace_back([filePath] {
            processFile(filePath);
        });
    }
    
    // Wait for all the threads to finish
    for (auto& thread : threads) {
        thread.join();
    }
}

int main() {
    std::vector<std::filesystem::path> filesToProcess;
    // Populate filesToProcess with the paths of files to process
    
    auto startTime = std::chrono::steady_clock::now();
    processFilesInParallel(filesToProcess);
    auto endTime = std::chrono::steady_clock::now();
    
    auto executionTime = std::chrono::duration_cast<std::chrono::milliseconds>(endTime - startTime);
    std::cout << "Parallel file processing took " << executionTime.count() << " milliseconds.\n";
    
    return 0;
}

In this example, the processFilesInParallel function takes a vector of file paths and creates a std::jthread for each file. Each thread calls the processFile function to process the individual file concurrently.

Once all the threads are created, we simply join each thread to wait for them to finish. The join operation ensures that the main thread waits for all the worker threads to complete before proceeding.

By utilizing parallel processing with std::jthread, we can distribute the file processing across multiple threads and potentially speed up the execution time significantly, especially when dealing with a large number of files.

Conclusion

Parallel file processing is a powerful technique to improve the performance of tasks that involve reading or processing multiple files. With the introduction of std::jthread in C++20, managing and joining threads becomes easier and safer. By utilizing this new feature, you can harness the power of parallelism to process files more efficiently.

#cpp #parallelprocessing