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

You're reading from   Hands-On Parallel Programming with C# 8 and .NET Core 3 Build solid enterprise software using task parallelism and multithreading

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Product type Paperback
Published in Dec 2019
Publisher Packt
ISBN-13 9781789132410
Length 346 pages
Edition 1st Edition
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Author (1):
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Shakti Tanwar Shakti Tanwar
Author Profile Icon Shakti Tanwar
Shakti Tanwar
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Table of Contents (22) Chapters Close

Preface 1. Section 1: Fundamentals of Threading, Multitasking, and Asynchrony FREE CHAPTER
2. Introduction to Parallel Programming 3. Task Parallelism 4. Implementing Data Parallelism 5. Using PLINQ 6. Section 2: Data Structures that Support Parallelism in .NET Core
7. Synchronization Primitives 8. Using Concurrent Collections 9. Improving Performance with Lazy Initialization 10. Section 3: Asynchronous Programming Using C#
11. Introduction to Asynchronous Programming 12. Async, Await, and Task-Based Asynchronous Programming Basics 13. Section 4: Debugging, Diagnostics, and Unit Testing for Async Code
14. Debugging Tasks Using Visual Studio 15. Writing Unit Test Cases for Parallel and Asynchronous Code 16. Section 5: Parallel Programming Feature Additions to .NET Core
17. IIS and Kestrel in ASP.NET Core 18. Patterns in Parallel Programming 19. Distributed Memory Management 20. Assessments 21. Other Books You May Enjoy

Shared state pattern

We covered the implementation of these patterns in Chapter 5, Synchronization Primitives.

A parallel application has to deal with a shared state problem constantly. The application will have some data members that need to be protected when they're accessed in a multithreaded environment. There are many ways to deal with shared state problems, such as using Synchronization, Isolation, and Immutability. Synchronization can be achieved using the synchronization primitives provided by the .NET Framework and it can also provide mutual exclusion over a shared data member. Immutability guarantees only one state for a data member and never changes. Consequently, the same state can be shared across threads without any issues. Isolation deals with each thread having its own copy of data members.

Now, we'll summarize what we learned in this chapter.

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