▶Book Description
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.
▶What You Will Learn
- Benefits of modern C++ constructs and techniques
- Identify hardware bottlenecks, such as CPU cache misses, to boost performance
- Write specialized data structures for performance-critical code
- Use modern metaprogramming techniques to reduce runtime calculations
- Achieve efficient memory management using custom memory allocators
- Reduce boilerplate code using reflection techniques
- Reap the benefits of lock-free concurrent programming
- Perform under-the-hood optimizations with preserved readability using proxy objects
- Gain insights into subtle optimizations used by STL algorithms
- Utilize the Range V3 library for expressive C++ code
- Parallelize your code over CPU and GPU, without compromising readability
▶Key Features
- Explore concurrent programming in C++
- Identify memory management problems
- Use SIMD and STL containers for performance improvement
▶Who This Book Is For
This book expects you to have a basic knowledge of C++ and computer architecture and a genuine interest in evolving your skills. Hopefully, by the time you finish this book, you will have gained a few insights into how you can improve your C++ applications, both performance-wise and syntactically. On top of that, we also hope that you will have a few aha moments.
▶What this book covers
- Chapter 1, A Brief Introduction to C++, introduces some important properties of C++ such as zero-cost abstractions, value semantics, const correctness, explicit ownership, and error handling. It also discusses the drawbacks of C++.
- Chapter 2, Modern C++ Concepts, outlines automatic type deduction using auto, lambda functions, move semantics, std::optional, and std::any.
- Chapter 3, Measuring Performance, discusses asymptotic complexity and big O notation, practical performance testing, and how to profile your code to find hotspots.
- Chapter 4, Data Structures, takes you through the importance of structuring the data so that it can be accessed quickly. STL containers such as std::vector, std::list, std::unordered_map, and std::priority_queue are introduced. Finally, we describe how to iterate over parallel arrays.
- Chapter 5, A Deeper Look at Iterators, dives into the concept of iterators, and shows how iterators can go beyond just referring to objects in containers.
- Chapter 6, STL Algorithms and Beyond, shows the obvious, and the not so obvious, advantages of STL algorithms over hand rolled for loops. It also takes a look at the limitations of STL algorithms and how the new Ranges library overcomes these limits.
- Chapter 7, Memory Management, focuses on safe and efficient memory management. This includes memory ownership, RAII, smart pointers, stack memory, dynamic memory, and custom memory allocators.
- Chapter 8, Metaprogramming and Compile-Time Evaluation, explains metaprogramming concepts such as constexpr, heterogeneous containers, type_traits, std::enable_if, and std::is_detected. It also gives practical examples of metaprogramming use cases, such as reflection.
- Chapter 9, Proxy Objects and Lazy Evaluation, explores how proxy objects can be used to perform under-the-hood optimizations while preserving clean syntax. Additionally, some creative uses of operator-overloading are demonstrated.
- Chapter 10, Concurrency, covers the fundamentals of concurrent programming, including parallel execution, shared memory, data races, and deadlocks. It also includes an introduction to the C++ thread support library, the atomic library, and the C++ memory model.
- Chapter 11, Parallel STL, starts by showing the complexity of writing parallel algorithms. It then demonstrates how to utilize STL algorithms in a parallel context using the parallel extensions for STL and Boost Compute.
