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

Aggregation

Aggregation is another common design pattern that's used in parallel applications. In parallel programs, the data is divided into units so that it can be processed across cores by a number of threads. At some point, there is a need to combine data from all the relevant sources before it can be presented to the user. This is where aggregation comes into the picture.

Now, let's explore the need for aggregation and what is provided by PLINQ.

A common use case of aggregation is as follows. Here, we are trying to iterate a set of values, perform some operations, and return the result to the caller:

var output = new List<int>();
var input = Enumerable.Range(1, 50);
Func<int,int> action = (i) => i * i;
foreach (var item in input)
{
var result = action(item);
output.Add(result);
}

The problem with the preceding code is that the output isn't...