Book Image

Parallel Programming and Concurrency with C# 10 and .NET 6

By : Alvin Ashcraft
Book Image

Parallel Programming and Concurrency with C# 10 and .NET 6

By: Alvin Ashcraft

Overview of this book

.NET has included managed threading capabilities since the beginning, but early techniques had inherent risks: memory leaks, thread synchronization issues, and deadlocks. This book will help you avoid those pitfalls and leverage the modern constructs available in .NET 6 and C# 10, while providing recommendations on patterns and best practices for parallelism and concurrency. Parallel, concurrent, and asynchronous programming are part of every .NET application today, and it becomes imperative for modern developers to understand how to effectively use these techniques. This book will teach intermediate-level .NET developers how to make their applications faster and more responsive with parallel programming and concurrency in .NET and C# with practical examples. The book starts with the essentials of multi-threaded .NET development and explores how the language and framework constructs have evolved along with .NET. You will later get to grips with the different options available today in .NET 6, followed by insights into best practices, debugging, and unit testing. By the end of this book, you will have a deep understanding of why, when, and how to employ parallelism and concurrency in any .NET application.
Table of Contents (18 chapters)
Part 1:Introduction to Threading in .NET
Part 2: Parallel Programming and Concurrency with C#
Part 3: Advanced Concurrency Concepts

Common pitfalls with parallelism

When working with the TPL, there are some practices to avoid in order to ensure the best outcomes in your applications. In some cases, parallelism used incorrectly can result in performance degradation. In other cases, it can cause errors or data corruption.

Parallelism is not guaranteed

When using one of the parallel loops or Parallel.Invoke, the iterations can run in parallel, but they are not guaranteed to do so. The code in these parallel delegates should be able to run successfully in either scenario.

Parallel loops are not always faster

We discussed this earlier in this chapter, but it is important to remember that parallel versions of for and foreach loops are not always faster. If each loop iteration runs quickly, the overhead of adding parallelism can slow down your application.

This is important to remember when introducing any threading to applications. Always test your code before and after introducing concurrency or parallelism...