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Rust High Performance

Rust High Performance

By : Eguia Moraza
3 (3)
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Rust High Performance

Rust High Performance

3 (3)
By: 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 (13 chapters)
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Concurrency in Rust


For a long time, it has not made sense to perform all tasks sequentially in a computer. Of course, sometimes you need to perform some tasks before others, but in most real-world applications, you will want to run some tasks in parallel.

You might, for example, want to respond to HTTP requests. If you do one after the other, the overall server will be slow. Especially when you get many requests per second and some of them take time to complete. You probably want to start responding to others before you finish with the current one.

Furthermore, we now have multiple processors in almost any computer or server, even in most mobile phones. This means that not only can we process other tasks in parallel while our main task is idle, we can really use one processor for each task by using threads. This is a feature that we must use to our advantage when developing high-performance applications.

The main issue with concurrency is that it's hard. We are not used to thinking in parallel...

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