Why do we need concurrency?

We need concurrency for several reasons, primarily to enhance the performance, responsiveness, and resource utilization of programs and systems. Here's why concurrency is essential:

1. Better CPU Utilization

Concurrency allows programs to make better use of the CPU by overlapping the execution of tasks. Modern processors often have multiple cores, and running tasks concurrently helps maximize CPU utilization.

• Example: A web server can handle multiple client requests simultaneously by processing some requests while waiting for others to complete I/O operations.

2. Improved Responsiveness

Concurrency enables programs to remain responsive by performing tasks in the background. For example, in GUI applications, the user interface (UI) can remain responsive to user inputs while background tasks, such as data processing or file uploads, continue without freezing the interface.

• Example: A text editor saving a document in the background while still allowing you to type.

3. Handling Multiple Tasks Simultaneously

Concurrency allows you to handle multiple tasks that can occur at the same time, even if they are unrelated. This is especially important in systems that need to handle high throughput, such as web servers, database systems, and networked applications.

• Example: An operating system running multiple applications (like a browser, a text editor, and a media player) concurrently.

4. Faster Execution of Independent Tasks

When tasks do not depend on each other, concurrency enables them to be executed in overlapping time frames. This reduces the total runtime compared to sequential execution.

• Example: Downloading files while playing music. These operations can run concurrently since they don’t depend on each other.

5. Improved Performance in I/O-bound and CPU-bound Operations

Concurrency allows a program to continue executing while waiting for I/O operations (such as reading from a disk or waiting for a network response) to complete, instead of blocking the entire process. Similarly, for CPU-bound tasks, concurrency helps distribute work across multiple processors.

• Example: A web scraper can fetch data from multiple websites concurrently, significantly speeding up the process.

6. Scalability

In distributed and cloud-based systems, concurrency allows for scalable handling of tasks. This is particularly important for modern applications, which need to scale to serve many users simultaneously.

• Example: A cloud-based system that scales up to handle thousands of users concurrently, like Netflix or Amazon, allows more efficient use of server resources.

Conclusion

Concurrency is necessary for efficiently utilizing system resources, improving performance, and creating responsive programs. It allows multiple tasks to progress at the same time, making applications faster and more capable of handling multiple operations simultaneously.