Book Image

Rust High Performance

By : Iban Eguia Moraza
Book Image

Rust High Performance

By: Iban Eguia Moraza

Overview of this book

This book teaches you how to optimize the performance of your Rust code so that it is at the same level as languages such as C/C++. You'll understand and fi x common pitfalls, learn how to improve your productivity by using metaprogramming, and speed up your code. You will master the features of the language, which will make you stand out, and use them to greatly improve the efficiency of your algorithms. The book begins with an introduction to help you identify bottlenecks when programming in Rust. We highlight common performance pitfalls, along with strategies to detect and resolve these issues early. We move on to mastering Rust's type system, which will enable us to optimize both performance and safety at compile time. You will learn how to effectively manage memory in Rust, mastering the borrow checker. We move on to measuring performance and you will see how this affects the way you write code. Moving forward, you will perform metaprogramming in Rust to boost the performance of your code and your productivity. Finally, you will learn parallel programming in Rust, which enables efficient and faster execution by using multithreading and asynchronous programming.
Table of Contents (19 chapters)
Title Page
Copyright and Credits
Dedication
Packt Upsell
Contributors
Preface
Index

Summary


In this chapter, you have learned how to create your own macros. First, we saw the standard macros and created some that could help you develop more quickly and create more efficient code. Then, you learned about procedural macros and how to derive your own code for your structures and enumeration. Finally, you found out about two features that might be coming to stable Rust in the future, which can currently be used in nightly Rust—plugins and declarative macros.

In the two remaining chapters, we will talk about concurrency in Rust. As you will see, once our single-threaded code is fast enough, the next step toward faster execution is to compute it in parallel.