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

Disadvantages of parallel programming with PLINQ

In most cases, PLINQ performs much faster than its non-parallel counterpart LINQ. However, there is some performance overhead, which is related to partitioning and merging while parallelizing the LINQ. The following are some of the things we need to consider while using PLINQ:

  1. Parallel is not always faster: Parallelization is an overhead. Unless your source collection is huge or it has compute-bound operations, it makes more sense to execute the operations in sequence. Always measure the performance of sequential and parallel queries to make an informed decision.
  2. Avoid I/O operations that involve atomicity: All I/O operations that involve writing to a filesystem, database, network, or shared memory location should be avoided inside PLINQ. This is because these methods are not thread-safe, so using them may lead to exceptions. A...