Book Image

Advanced C++

By : Gazihan Alankus, Olena Lizina, Rakesh Mane, Vivek Nagarajan, Brian Price
5 (1)
Book Image

Advanced C++

5 (1)
By: Gazihan Alankus, Olena Lizina, Rakesh Mane, Vivek Nagarajan, Brian Price

Overview of this book

C++ is one of the most widely used programming languages and is applied in a variety of domains, right from gaming to graphical user interface (GUI) programming and even operating systems. If you're looking to expand your career opportunities, mastering the advanced features of C++ is key. The book begins with advanced C++ concepts by helping you decipher the sophisticated C++ type system and understand how various stages of compilation convert source code to object code. You'll then learn how to recognize the tools that need to be used in order to control the flow of execution, capture data, and pass data around. By creating small models, you'll even discover how to use advanced lambdas and captures and express common API design patterns in C++. As you cover later chapters, you'll explore ways to optimize your code by learning about memory alignment, cache access, and the time a program takes to run. The concluding chapter will help you to maximize performance by understanding modern CPU branch prediction and how to make your code cache-friendly. By the end of this book, you'll have developed programming skills that will set you apart from other C++ programmers.
Table of Contents (11 chapters)
7
6. Streams and I/O

Cache Friendly Code

Computer science was developed in the mid-20th century, when computers hardly existed, but nevertheless, by the 1980s, most of the useful data structures and algorithms had been discovered and refined. Algorithmic complexity analysis is a topic that anyone who learns computer science encounters – and there are well-accepted textbook definitions of the complexity of data structure operations. However, after 50 years since these things were analyzed, computers have evolved in a way that is quite different from what could have been envisaged. For example, a common "fact" is that the list data structures are faster for insertion operations than arrays. This seems like common sense because inserting an element into an array involves moving all the items after that point to new locations, whereas inserting into a list is merely a few pointer manipulations. We will test this hypothesis in the following exercise.

Exercise 10: Exploring the Effect of Caches on...