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High-Performance Programming in C# and .NET

You're reading from   High-Performance Programming in C# and .NET Understand the nuts and bolts of developing robust, faster, and resilient applications in C# 10.0 and .NET 6

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Product type Paperback
Published in Jul 2022
Publisher Packt
ISBN-13 9781800564718
Length 660 pages
Edition 1st Edition
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Author (1):
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Jason Alls Jason Alls
Author Profile Icon Jason Alls
Jason Alls
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Table of Contents (22) Chapters Close

Preface 1. Part 1: High-Performance Code Foundation
2. Chapter 1: Introducing C# 10.0 and .NET 6 FREE CHAPTER 3. Chapter 2: Implementing C# Interoperability 4. Chapter 3: Predefined Data Types and Memory Allocations 5. Chapter 4: Memory Management 6. Chapter 5: Application Profiling and Tracing 7. Part 2: Writing High-Performance Code
8. Chapter 6: The .NET Collections 9. Chapter 7: LINQ Performance 10. Chapter 8: File and Stream I/O 11. Chapter 9: Enhancing the Performance of Networked Applications 12. Chapter 10: Setting Up Our Database Project 13. Chapter 11: Benchmarking Relational Data Access Frameworks 14. Chapter 12: Responsive User Interfaces 15. Chapter 13: Distributed Systems 16. Part 3: Threading and Concurrency
17. Chapter 14: Multi-Threaded Programming 18. Chapter 15: Parallel Programming 19. Chapter 16: Asynchronous Programming 20. Assessments 21. Other Books You May Enjoy

Summary

In this chapter, we looked at how to use TPL and PLINQ to execute code in parallel. At this point, we understand that the main difference between TPL and PLINQ is that TPL does not efficiently utilize all the cores on a computer, whereas PLINQ does.

We also saw how we can view the computer’s CPU utilization. Using PLINQ enables us to utilize all the cores of a CPU efficiently to improve code performance. However, when benchmarking parallel code, we saw that it is sometimes faster than non-parallel code, while other times, it is faster. Therefore, it pays to benchmark your code to see what method works best for you.

We also reviewed a piece of code that demonstrates the use of lambda expressions for expressing both Func and Action delegates.

Finally, we looked at debugging parallel applications with a code sample that employed the Parallel Tasks window, the Tasks pane, and the Concurrency Visualizer.

In the next chapter, we will look at asynchronous programming...

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