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

The speculative processing pattern

The speculative processing pattern is another parallel programming pattern that relies on high throughput to reduce latency. This is very useful in scenarios where there are multiple ways of performing a task but the user doesn't know which way will return the results fastest. This approach creates a task for each possible method, which is then executed across processors. The task that finishes first is used as output, ignoring the others (which may still complete successfully but are slow).

The following is a typical SpeculativeInvoke representation. It accepts an array of Func<T> as parameters and executes them in parallel until one of them returns:

public static T SpeculativeInvoke<T>(params Func<T>[] functions)
return SpeculativeForEach(functions, function => function());

The following method executes each action...