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Hands-On High Performance Programming with Qt 5

Hands-On High Performance Programming with Qt 5

By : Marek Krajewski
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Hands-On High Performance Programming with Qt 5

Hands-On High Performance Programming with Qt 5

5 (2)
By: Marek Krajewski

Overview of this book

Achieving efficient code through performance tuning is one of the key challenges faced by many programmers. This book looks at Qt programming from a performance perspective. You'll explore the performance problems encountered when using the Qt framework and means and ways to resolve them and optimize performance. The book highlights performance improvements and new features released in Qt 5.9, Qt 5.11, and 5.12 (LTE). You'll master general computer performance best practices and tools, which can help you identify the reasons behind low performance, and the most common performance pitfalls experienced when using the Qt framework. In the following chapters, you’ll explore multithreading and asynchronous programming with C++ and Qt and learn the importance and efficient use of data structures. You'll also get the opportunity to work through techniques such as memory management and design guidelines, which are essential to improve application performance. Comprehensive sections that cover all these concepts will prepare you for gaining hands-on experience of some of Qt's most exciting application fields - the mobile and embedded development domains. By the end of this book, you'll be ready to build Qt applications that are more efficient, concurrent, and performance-oriented in nature
Table of Contents (14 chapters)
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Profiling to Find Bottlenecks

As we already described in Chapter 1, Understanding Performant Programs, performance bottlenecks are not distributed evenly in code. Applying the Pareto principle to performance optimization, we could say that 80% of a program's execution time is spent on 20% of the code (and, as we've seen, Donald Knuth believed this to be an even lower figure). Regardless of the exact proportions, the basic insight is the same—code optimization efforts are most effectively spent on that critical x percent of the code that is responsible for most of the program's execution time.

We saw in the previous chapter that today's hardware platforms have grown to be so complicated that the ancient adage about programmers being notoriously bad at estimating bottlenecks in their own code has now been reinforced more than ever—not only do we...

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