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What you will learn

Understand the significance of high performance in applications

Identify different performance concerns for all the mainly used architectures and designs

Acquaint yourself with the commonly used MVC and MVVM patterns

Understand the fundamentals of CLR

Learn more about Task Parallel Library and concepts such as Thread Pool Tuning and parameter injection

Use PLINQ programming to achieve parallelism

Design Big Data solutions for handling datasets optimally

Choose highperformance querying strategies to retrieve and manipulate data

Execute tests on applications for performance analysis

What do you get with eBook?

Instant access to your Digital eBook purchase

Download this book in EPUB and PDF formats

Access this title in our online reader with advanced features

DRM FREE - Read whenever, wherever and however you want

AI Assistant (beta) to help accelerate your learning

Frequently bought together

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Learning .NET High-Performance Programming

Can$73.99

Total Can$ 223.97

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Cliente Nov 24, 2015

A complete guide for dummies and experienced developers that need a "good-programming" reference book. Useful for managers and architets too

Amazon Verified review

Jason Down Sep 28, 2015

Disclaimer: I was given a free electronic review copy of this book.This book begins with an interesting perspective on design consideration and requirements for various types of applications and performance aspects (latency vs. throughput vs. resource usage etc.). There are a few case studies that bring some substance to these concepts.In Chapter 2, the book moves on to an overview of different architectures and patterns and performance considerations in relation to them. I found this section to be quite informative and interesting. A lot of ground is covered however, so some of the information seems a little too shallow.Chapter 3 moves on to the .Net CLR (Common Language Runtime) internals as they relate to performance. This includes topics such as memory management, garbage collection, threading and exception handling. You get a lot of code samples in an attempt to show how these things work. Again, a lot of ground is covered, so some samples feel rushed and not fully explained (especially if you are new to any of these concepts). To the author's credit, there are often links provided for further explanation.Chapters 4 and 5 cover asynchronous programming (various models and patterns) and parallel programming. I found these two chapters to be the most interesting and in-depth. There was a whirlwind of code samples which seemed to be more complete than in the previous sections.Chapters 6-8 go into programming for math/engineering (data type performance, real time applications, Fourier transformations), database querying (ADO.NET vs. Entity Framework) and programming for big data (grid computing and an overview of Microsoft Azure). Except for a few useful nuggets of wisdom, I found these chapters to be too much of a general overview and less interesting.The book ends with an overview of code performance analysis, profiling and testing. This chapter was also a little brief, although I found the information about the tools in Visual Studio to be interesting.Overall, I think the book is worth the read because some chapters are great. However, the book as a whole seems to be more of a general introduction and overview to performance programming. It tries to cover too much material for its size. Either more pages should be added or some of the weaker chapters should be pulled in order to focus on the more interesting and important topics.

Damir Arh Sep 05, 2015

Unfortunately the book didn't meet my expectations. I was expecting in-depth content, describing the good and bad practices in different scenarios supported by measurements, pitfalls to be aware of, options to consider. Instead I only got a high-level overview of several performance related aspects, at best.The introductory chapters are very generic and subjective with very little to support the author's point of view. The remainder of the book covers a broad selection of topics, all of them related to performance in one way or another: Common Language Runtime internals, parallelism and asynchronicity, data access, distributed computing. As a consequence, the author only manages to mention what needs to be considered when thinking about performance, but gives very little guidance or useful advice. Occasional inaccuracies in text and errors in samples decrease the value even further. On top of that, the author's use of English language can make the book more difficult to read.I really can't recommend the book to anyone, at least not for the full price. At a discount, it might be of limited use to someone, who's just starting to learn about performance, before moving on to more advanced resources. It should still be read with a grain of salt, though.

Learning .NET High-Performance Programming: Learn everything you need to know about performance-oriented programming for the .NET Framework

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