This project introduces a concurrent sorted vector designed to support efficient and thread-safe concurrent write and read operations. By utilizing advanced C++ features, this solo-developed project aims to meet the demands of applications requiring real-time data processing.

• Quick Sort Performance: A key highlight is the parallel Quick Sort algorithm, which vastly outperforms std::sort. When sorting 100 Ratio objects, it completes the task in 3.75904 seconds using 7 threads, compared to the 16.3723 seconds taken by std::sort, demonstrating a 4.35x speed improvement. This performance showcases the algorithm's effective use of multi-threading.

• Concurrent Read/Write Performance: The vector's ability to efficiently manage concurrent operations is showcased by its performance under simultaneous read/write conditions. Transitioning from 1 to 6 writing threads while continuously reading from the container results in operation times dropping from 1.90929 seconds to 1.12647 seconds, illustrating its robustness in concurrent modification scenarios.

The parallel Quick Sort algorithm leverages a "bag of tasks" model to distribute sorting work among multiple threads, which is essential for reducing completion time and optimizing CPU usage.

template<typename T>
void Quicksort(T* a, unsigned begin, unsigned end, int num_threads) {
    std::vector<std::thread> threads;
    threads.reserve(num_threads);

    ThreadSafeContainer<T> bag(end - begin, num_threads);
    bag.Push(std::make_pair(a, std::make_pair(begin, end)));

    for (int i = 0; i < num_threads; ++i) {
        threads.emplace_back([&bag]() {
            QuicksortIterativeAux(bag);
        });
    }
    for (auto& t : threads) {
        t.join();
    }
}

Efficient memory management and thread safety are achieved through a combination of thread-local caching for insert operations and atomic operations for managing shared data integrity, ensuring optimal performance even under high concurrency.

The project extensively uses atomic operations and the CAS technique for managing the vector's state without traditional locking mechanisms. This atomic-based approach is crucial for the lock-free insertion process, addressing the ABA problem and ensuring data consistency among concurrent threads.

The Ratio class, equipped with built-in delays for comparison operations, plays a crucial role in evaluating the sorting algorithm's time complexity and performance. This class mimics the computational load of real-world scenarios, offering a controlled benchmark that accurately reflects the vector's capabilities in handling complex operations efficiently.

This vector is exceptionally suited for:

• Real-time Data Analytics: Facilitating quick processing and analysis of streaming data.
• Interactive Gaming: Managing dynamic entities and leaderboards in real time.
• Financial Trading: Accelerating data updates and access for trading algorithms.
• Scientific Simulations: Modeling systems with concurrent data interactions accurately and efficiently.

The concurrent sorted vector, with its parallel Quick Sort implementation and sophisticated thread safety mechanisms, represents a significant advancement in the field of high-performance computing. This project illustrates the potential for modern C++ to enhance data structure performance, particularly in applications that demand fast, concurrent processing of data.