Book Image

C++ High Performance - Second Edition

By : Björn Andrist, Viktor Sehr
5 (2)
Book Image

C++ High Performance - Second Edition

5 (2)
By: Björn Andrist, Viktor Sehr

Overview of this book

C++ High Performance, Second Edition guides you through optimizing the performance of your C++ apps. This allows them to run faster and consume fewer resources on the device they're running on without compromising the readability of your codebase. The book begins by introducing the C++ language and some of its modern concepts in brief. Once you are familiar with the fundamentals, you will be ready to measure, identify, and eradicate bottlenecks in your C++ codebase. By following this process, you will gradually improve your style of writing code. The book then explores data structure optimization, memory management, and how it can be used efficiently concerning CPU caches. After laying the foundation, the book trains you to leverage algorithms, ranges, and containers from the standard library to achieve faster execution, write readable code, and use customized iterators. It provides hands-on examples of C++ metaprogramming, coroutines, reflection to reduce boilerplate code, proxy objects to perform optimizations under the hood, concurrent programming, and lock-free data structures. The book concludes with an overview of parallel algorithms. By the end of this book, you will have the ability to use every tool as needed to boost the efficiency of your C++ projects.
Table of Contents (17 chapters)
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Some performance considerations

We have now covered the three major container categories: sequence containers, associative containers, and container adaptors. This section will provide you with some general performance advice to consider when working with containers.

Balancing between complexity guarantees and overhead

Knowing the time and memory complexity of data structures is important when choosing between containers. But it's equally important to remember that each container is afflicted with an overhead cost, which has a bigger impact on the performance for smaller datasets. The complexity guarantees only become interesting for sufficiently large datasets. It's up to you, though, to decide what sufficiently large means in your use cases. Here, again, you need to measure your program while executing it to gain insights.

In addition, the fact that computers are equipped with memory caches makes the use of data structures that are friendly to the cache more...