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
1
Section 1: Fundamentals of Threading, Multitasking, and Asynchrony
6
Section 2: Data Structures that Support Parallelism in .NET Core
10
Section 3: Asynchronous Programming Using C#
13
Section 4: Debugging, Diagnostics, and Unit Testing for Async Code
16
Section 5: Parallel Programming Feature Additions to .NET Core

Measuring the performance of async code

Async code can improve the performance and responsiveness of applications, but there are trade-offs. In the case of GUI-based applications, such as Windows Forms or WPF, if a method is taking a long time, it makes sense to make it async. For server applications, however, you need to measure the trade-off between the extra memory utilized by the blocked threads and the extra processor overhead required to make methods asynchronous.

Consider the following code, which creates three tasks. Each task runs asynchronously, one after another. As one method finishes, it goes on to execute another task asynchronously. The total time taken to finish the method can be calculated using Stopwatch:

public static void Main(string[] args)
{
MainAsync(args).GetAwaiter().GetResult();
Console.ReadLine();
}
public static async Task MainAsync(string[] args...