Lära Parallel Algorithms | Advanced Concurrency Techniques

Modern C++ offers robust tools for writing concurrent and parallel code, enabling efficient use of multicore processors for better performance.

Since C++17, the Standard Library includes parallel algorithms like std::for_each, which can run in parallel using execution policies. This lets you write high-level, thread-aware code without managing threads directly.

main.cpp


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

int main()
{
    std::vector<int> data = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10};

    // Process each element in parallel: double each value
    std::for_each(std::execution::par, data.begin(), data.end(), [](int& n) 
    {
        n *= 2;
    });

    std::cout << "Processed data: ";
    for (const auto& n : data)
        std::cout << n << " ";
    std::cout << std::endl;
}

Performance

Parallel algorithms can greatly speed up large data processing by distributing work across multiple CPU cores. Sequential algorithms handle elements one at a time and don’t use multiple cores.

Determinism

Parallel execution can cause non-deterministic operation order, which may affect results if operations depend on each other. Sequential algorithms process elements in order, ensuring deterministic results.

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