After reading the previous chapters, it should no longer come as a surprise that the way we handle memory can have a huge impact on the performance. The CPU spends a lot of time shuffling data between the CPU registers and the main memory (loading and storing data to and from the main memory). As shown in Chapter 4, Data Structures, the CPU uses memory caches to speed up the access of memory, and the programs need to be cache-friendly in order to run quickly. This chapter will reveal more aspects of how computers work with memory so that we know which things must be considered when tuning memory usage. We will discuss automatic memory allocation and dynamic memory management, and look at the life cycle of a C++ object. Sometimes there are hard memory limits that force us to keep our data representation compact, and sometimes we have plenty of memory available...
C++ High Performance
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C++ High Performance
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Overview of this book
C++ is a highly portable language and can be used to write both large-scale applications and performance-critical code. It has evolved over the last few years to become a modern and expressive language. This book will guide you through optimizing the performance of your C++ apps by allowing them to run faster and consume fewer resources on the device they're running on without compromising the readability of your code base.
The book begins by helping you measure and identify bottlenecks in a C++ code base. It then moves on by teaching you how to use modern C++ constructs and techniques. You'll see how this affects the way you write code. Next, you'll see the importance of data structure optimization and memory management, and how it can be used efficiently with respect to CPU caches. After that, you'll see how STL algorithm and composable Range V3 should be used to both achieve faster execution and more readable code, followed by how to use STL containers and how to write your own specialized iterators.
Moving on, you’ll get hands-on experience in making use of modern C++ metaprogramming and reflection to reduce boilerplate code as well as in working with proxy objects to perform optimizations under the hood. After that, you’ll learn concurrent programming and understand lock-free data structures. The book ends with an overview of parallel algorithms using STL execution policies, Boost Compute, and OpenCL to utilize both the CPU and the GPU.
Table of Contents (13 chapters)
Preface
Free Chapter
A Brief Introduction to C++
Modern C++ Concepts
Measuring Performance
Data Structures
A Deeper Look at Iterators
STL Algorithms and Beyond
Memory Management
Metaprogramming and Compile-Time Evaluation
Proxy Objects and Lazy Evaluation
Concurrency
Parallel STL
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