Welcome to an exciting new chapter in your journey through C++ concurrency! In the previous lesson, we dove into the critical realm of deadlocks and how to avoid them. With that knowledge, you're now equipped to handle one of the common pitfalls in concurrency. In this lesson, we’re turning our focus toward an essential tool in lock-free programming: the Compare-and-Swap (CAS) operation.

In this unit, we will unravel the intricacies of CAS operations and their importance in developing lock-free programs:

• Introduction to Compare-and-Swap (CAS): You will learn how CAS is used to achieve atomic operations without the need for locks. CAS is a powerful technique that safely updates a shared resource by comparing its current value to a specified value and swapping it with a new value if they match.

• Code Example: Implementing a Complex Counter with CAS: Let's get a hands-on look with a code example demonstrating how CAS can be used to modify a shared resource safely:

C++
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1#include <atomic>
2#include <iostream>
3#include <thread>
4#include <vector>
5
6class LockFreeComplexCounter {
7public:
8    LockFreeComplexCounter() : count_(0) {}
9
10    void complexOperation() {
11        long long expected = count_.load();
12        while (!count_.compare_exchange_weak(expected, computeNewValue(expected))) {
13            expected = count_.load();
14        }
15    }
16
17    long long getCount() const {
18        return count_.load();
19    }
20
21private:
22    long long computeNewValue(long long currentValue) const {
23        return currentValue + (currentValue % 100) + 1;
24    }
25
26    std::atomic<long long> count_;
27};
28
29int main() {
30    LockFreeComplexCounter counter;
31    const int num_threads = 10;
32    const int operations_per_thread = 100;
33
34    std::vector<std::thread> threads;
35    for (int i = 0; i < num_threads; ++i) {
36        threads.emplace_back([&counter, operations_per_thread] {
37            for (int i = 0; i < operations_per_thread; ++i) {
38                counter.complexOperation();
39            }
40        });
41    }
42
43    for (auto& t : threads) {
44        t.join();
45    }
46
47    std::cout << "Final count after complex operations: " << counter.getCount() << std::endl;
48    return 0;
49}

The provided code demonstrates the use of Compare-and-Swap (CAS) operations to implement a lock-free complex counter. Here's a breakdown of its key components:

• LockFreeComplexCounter Class: This class encapsulates the logic for a counter that uses CAS to perform a complex operation on a shared resource.

• complexOperation Method: The core of the CAS operation occurs here. The method attempts to update the count_ by repeatedly calling compare_exchange_weak. It checks if the current value (expected) matches the actual value stored in count_. If they match, it computes a new value using the computeNewValue method and swaps it in. If the values don’t match, it loads the latest value of count_ and retries.

• computeNewValue Method: It encapsulates the logic for calculating the next value of the counter based on the current value. In this example, the new value is computed as the current value plus the remainder of the current value divided by 100, plus one.

• std::atomic Count_: This is an atomic variable that holds the count. It provides a mechanism for atomic operations on the count_, ensuring thread safety without using locks.

• Usage in main: Ten threads are launched, each performing 100 operations on the counter. They call the complexOperation, showcasing how CAS enables concurrent modifications without locks.

By utilizing CAS, the code ensures that multiple threads can modify the count_ concurrently, minimizing wait times and potential bottlenecks associated with lock-based mechanisms. This demonstrates a powerful technique for achieving atomic operations in a multithreaded environment efficiently.

Understanding and utilizing CAS operations can significantly enhance the efficiency and performance of your multithreaded programs. Unlike traditional locking mechanisms that can introduce complexities and bottlenecks, CAS allows for lock-free programming, where threads can safely operate on shared resources without waiting for locks. This can lead to faster, more responsive applications, particularly in high-performance environments.

Embracing CAS operations empowers you with a modern approach to concurrency, equipping you to tackle complex problems with confidence and precision. Ready to dive in and see how CAS can revolutionize your approach to concurrency? Let’s move on to the practice section and start experimenting with lock-free programming!