Book Image

Hands-On Parallel Programming with C# 8 and .NET Core 3

By : Shakti Tanwar
Book Image

Hands-On Parallel Programming with C# 8 and .NET Core 3

By: Shakti Tanwar

Overview of this book

In today’s world, every CPU has a multi-core processor. However, unless your application has implemented parallel programming, it will fail to utilize the hardware’s full processing capacity. This book will show you how to write modern software on the optimized and high-performing .NET Core 3 framework using C# 8. Hands-On Parallel Programming with C# 8 and .NET Core 3 covers how to build multithreaded, concurrent, and optimized applications that harness the power of multi-core processors. Once you’ve understood the fundamentals of threading and concurrency, you’ll gain insights into the data structure in .NET Core that supports parallelism. The book will then help you perform asynchronous programming in C# and diagnose and debug parallel code effectively. You’ll also get to grips with the new Kestrel server and understand the difference between the IIS and Kestrel operating models. Finally, you’ll learn best practices such as test-driven development, and run unit tests on your parallel code. By the end of the book, you’ll have developed a deep understanding of the core concepts of concurrency and asynchrony to create responsive applications that are not CPU-intensive.
Table of Contents (22 chapters)
Free Chapter
Section 1: Fundamentals of Threading, Multitasking, and Asynchrony
Section 2: Data Structures that Support Parallelism in .NET Core
Section 3: Asynchronous Programming Using C#
Section 4: Debugging, Diagnostics, and Unit Testing for Async Code
Section 5: Parallel Programming Feature Additions to .NET Core


In this chapter, we elaborated on achieving task parallelism using TPL. We started by introducing how to move sequential loops to parallel using some built-in methods provided by TPL, such as Parallel.Invoke, Parallel.For, and Parallel.ForEach. Next, we discussed how to get maximum utilization out of the available CPU resources by understanding the degree of parallelism and partitioning strategies. Then, we discussed how to cancel and break out of parallel loops using built-in constructs such as cancellation tokens, Parallel.Break, and ParallelLoopState.Stop. At the end of this chapter, we discussed various thread storage options that are available in TPL.

The TPL provides a few very exciting options that we can use to achieve data parallelism through the parallel implementation of For and ForEach loops. Along with features such as ParallelOptions and ParallelLoopState...