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Parallel Programming and Concurrency with C# 10 and .NET 6

You're reading from   Parallel Programming and Concurrency with C# 10 and .NET 6 A modern approach to building faster, more responsive, and asynchronous .NET applications using C#

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Product type Paperback
Published in Aug 2022
Publisher Packt
ISBN-13 9781803243672
Length 320 pages
Edition 1st Edition
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Author (1):
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Alvin Ashcraft Alvin Ashcraft
Author Profile Icon Alvin Ashcraft
Alvin Ashcraft
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Table of Contents (18) Chapters Close

Preface 1. Part 1:Introduction to Threading in .NET
2. Chapter 1: Managed Threading Concepts FREE CHAPTER 3. Chapter 2: Evolution of Multithreaded Programming in .NET 4. Chapter 3: Best Practices for Managed Threading 5. Chapter 4: User Interface Responsiveness and Threading 6. Part 2: Parallel Programming and Concurrency with C#
7. Chapter 5: Asynchronous Programming with C# 8. Chapter 6: Parallel Programming Concepts 9. Chapter 7: Task Parallel Library (TPL) and Dataflow 10. Chapter 8: Parallel Data Structures and Parallel LINQ 11. Chapter 9: Working with Concurrent Collections in .NET 12. Part 3: Advanced Concurrency Concepts
13. Chapter 10: Debugging Multithreaded Applications with Visual Studio 14. Chapter 11: Canceling Asynchronous Work 15. Chapter 12: Unit Testing Async, Concurrent, and Parallel Code 16. Assessments 17. Other Books You May Enjoy

Introduction to parallelism

While exploring the history of threading in C# and .NET, we learned that parallelism was introduced to developers in .NET Framework 4.0. In this section, the aspects that will be explored are exposed in the TPL through the System.Threading.Tasks.Parallel class. In addition, we will cover some of the basics of PLINQ through examples. These data parallelism concepts will be covered in greater detail with real-world examples in Chapter 6, Chapter 7, and Chapter 8.

At a high level, parallelism is the concept of executing multiple tasks in parallel. These tasks could be related to one another, but this is not a requirement. In fact, related tasks running in parallel run a greater risk of encountering synchronization issues or blocking one another. For example, if your application loads order data from an orders service and user preferences and application state from an Azure blob store, these two processes can be run in parallel without having to worry about...

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