Measuring the performance of algorithms using std::chrono

20 Oct 2023

When developing software, it is often important to measure the performance of algorithms to determine their efficiency. In C++, we can use the std::chrono library to accurately measure the execution time of our code. In this blog post, we will explore how to use std::chrono to measure the performance of algorithms.

What is std::chrono?

std::chrono is a library in C++ that provides functionalities for dealing with time and date. It was introduced in the C++11 standard and offers a high-resolution clock to measure time durations accurately.

Timing an Algorithm

To measure the performance of an algorithm using std::chrono, we need to record the start and end points of its execution. Here’s an example of how to measure the execution time of an algorithm:

#include <iostream>
#include <chrono>

int main() {
    // Start the timer
    auto start = std::chrono::steady_clock::now();

    // Call your algorithm here
    yourAlgorithm();

    // End the timer
    auto end = std::chrono::steady_clock::now();

    // Compute the duration in milliseconds
    auto duration = std::chrono::duration_cast<std::chrono::milliseconds>(end - start);

    // Output the execution time
    std::cout << "Execution time: " << duration.count() << " milliseconds" << std::endl;

    return 0;
}

In the above code, we use std::chrono::steady_clock to get the current time at the start and end of the algorithm execution. We then compute the duration using std::chrono::duration_cast and print the execution time in milliseconds.

Microbenchmarking

Microbenchmarking is the process of repeatedly executing a piece of code to measure its average execution time. This can help identify any variations or anomalies in performance due to external factors, such as CPU load or background tasks.

To perform microbenchmarking, we can wrap the algorithm execution in a loop and repeat it multiple times. Here’s an example:

// ...

const int iterations = 100;
auto totalDuration = std::chrono::milliseconds::zero();

for (int i = 0; i < iterations; ++i) {
    auto start = std::chrono::steady_clock::now();
    yourAlgorithm();
    auto end = std::chrono::steady_clock::now();
    totalDuration += std::chrono::duration_cast<std::chrono::milliseconds>(end - start);
}

std::cout << "Average execution time: " << totalDuration.count() / iterations << " milliseconds" << std::endl;

// ...

In this example, we execute the algorithm iterations number of times and calculate the total duration of all executions. Finally, we compute the average execution time by dividing the total duration by the number of iterations.

Conclusion

By using std::chrono, we can accurately measure the performance of algorithms and make informed decisions about their efficiency. The ability to time our code allows us to optimize critical sections and improve overall application performance.

Remember to perform microbenchmarking to get a more accurate picture of the algorithm’s performance. However, keep in mind that the execution time may vary due to external factors, so it’s essential to understand the limitations of the measurement.

Start measuring your algorithms’ performance with std::chrono today and optimize your code for better efficiency!

#references

std::chrono - cppreference.com
Timing Code with std::chrono #cpp #performance