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

Advantages and disadvantages of parallel programming

Multithreading leads to parallelism, which has its own programming and pitfalls. Now that we have grasped the basic concepts of parallel programming, it is important to understand its advantages and disadvantages.

The following are the benefits of parallel programming:

  • Enhanced performance: We can achieve better performance since tasks are distributed across threads that run in parallel.
  • Improved GUI responsiveness: Since tasks perform non-blocking I/O, this means the GUI thread is always free to accept user inputs. This results in better responsiveness.
  • The simultaneous and parallelized occurrence of tasks: Since tasks run in parallel, we can simultaneously run different programming logic.
  • Better use of cache storage by utilizing resources and better use of CPU resources. Tasks can run on different cores, thereby ensuring...