Deciphering Concurrency: What Makes It So Significant in the Definition

Concurrency is an essential concept in modern software development. As computers continue to evolve, and multi-core processors become more common, there is an ever-growing need to design and write programs that can efficiently utilize such hardware. In this article, we’ll define concurrency, explore how it works, and discuss the benefits of using concurrency in software development. We’ll also cover several use cases, best practices, and recommend some books for further reading. By the end of this glossary page, you’ll have a solid understanding of what concurrency is and why it’s an important aspect of software development.

“Concurrency is a concept in which several things are happening simultaneously, allowing us to efficiently manage complexity and resources, … It is not a luxury anymore, but a necessity.” – Sir Tim Berners-Lee

What is concurrency? Definition of Concurrency

Concurrency refers to the execution of multiple tasks or processes simultaneously so that they overlap in time. In other words, concurrency is the composition of independently executing processes with a potentially overlapping time span. In the context of software development, concurrency can be achieved through multithreading (i.e., multiple threads of execution within a single program) or multiprocessing (i.e., running multiple processes on one or more CPUs).

ℹ️ Synonyms: Parallelism, simultaneousness, co-occurrence, concurrency, concurrency control.

How it Works

In a concurrent system, tasks are divided into smaller subtasks that can be executed independently. These subtasks are then scheduled to run on the available resources (e.g., CPU cores) either simultaneously or in an interleaved manner. The scheduler (either part of the operating system or a separate component) is responsible for managing the execution of these concurrent subtasks.

Concurrency can be implemented using various techniques, such as starting multiple threads within a single process or running multiple processes on one or more processors. Another approach is through asynchronous programming, where tasks are initiated without waiting for the results, allowing other tasks to be executed concurrently. Depending on the scenario, certain concurrency models (e.g., parallelism, message passing, data parallelism) may be more suitable than others.

Benefits of Using Concurrency

• Improved performance: By executing tasks concurrently, software applications can make better use of multiple processor cores, leading to improved performance and more efficient use of hardware resources.
• Better responsiveness: A concurrent application can continue processing user input or handling network requests while other tasks are being executed in the background, ensuring that the application remains responsive even during heavy load conditions.
• Flexibility: Concurrency allows developers to better manage resource allocation and task prioritization, making it easier to adapt to changing system requirements or user demands.
• Scalability: Concurrent systems can be easily scaled by adding more processing units or processors, enabling applications to handle increasing workloads without significant modifications to the underlying codebase.

Concurrency Use Cases

Concurrency is a versatile concept that can be applied to various software development scenarios, including:

Parallel computation:

Tasks that can be broken down into smaller, independent subtasks are well-suited for concurrent execution. This is particularly useful in applications that require extensive computations or data processing, such as scientific simulations, signal processing, or image rendering.

Web servers and service-oriented applications:

Concurrency helps manage resource allocation among multiple clients, allowing for more efficient handling of incoming requests, efficient data retrieval, and improved response times.

Graphical user interfaces (GUIs):

In desktop applications, concurrency allows developers to offload time-consuming tasks (e.g., file I/O or network communication) to separate threads, ensuring that the GUI remains responsive to user input.

Code Examples

import threading
import time

def worker_function(num):
    print(f"Worker {num} has started")
    time.sleep(2)
    print(f"Worker {num} has finished")

# Create two threads
worker1 = threading.Thread(target=worker_function, args=(1,))
worker2 = threading.Thread(target=worker_function, args=(2,))

# Start both threads
worker1.start()
worker2.start()

# Wait for both threads to finish
worker1.join()
worker2.join()

print("Both workers have finished.")

Best Practices

When implementing concurrency, it’s essential to follow best practices to avoid potential pitfalls, such as race conditions, deadlocks, or livelocks. Some of these best practices include using appropriate synchronization mechanisms (e.g., locks, semaphores, or message passing) to protect shared resources, carefully designing the program’s control flow to avoid overlapping or colliding subtasks, and properly testing and fine-tuning the application’s performance under concurrent execution. Additionally, it’s crucial to stay up-to-date with the latest frameworks, libraries, and tools that support concurrent programming, as they can streamline the development process and help in following best practices.

Most Recommended Books About Concurrency

If you’re interested in deepening your understanding of concurrency and concurrent programming, consider reading the following books:

• Concurrency in C# Cookbook by Stephen Cleary: This book provides practical recipes and tips for working with concurrency in C# applications, including the use of asynchronous programming with the async and await keywords.
• Java Concurrency in Practice by Brian Goetz, Tim Peierls, Joshua Bloch, Joseph Bowbeer, David Holmes, and Doug Lea: This book offers a comprehensive guide to mastering the complexities of concurrent programming in Java, covering topics such as synchronization, performance optimization, and best practices.
• The Art of Multiprocessor Programming by Maurice Herlihy and Nir Shavit: This book presents a broad range of concepts and algorithms for parallel and concurrent programming, along with practical examples to demonstrate their application in real-world scenarios.

Conclusion

Concurrency is an integral part of modern software development, enabling applications to better utilize multi-core processors and respond to user input or network requests more efficiently. By understanding the basic principles of concurrency and following best practices, developers can create responsive, scalable, and high-performing software solutions. To further your understanding of concurrency and concurrent programming techniques, consider reading some of the recommended books and keeping up-to-date with the latest advances in this field.

Tags: concurrency, deadlock, efficiency, multithreading, parallelism.