Book Image

Hands-On Concurrency with Rust

By : Brian L. Troutwine
Book Image

Hands-On Concurrency with Rust

By: Brian L. Troutwine

Overview of this book

Most programming languages can really complicate things, especially with regard to unsafe memory access. The burden on you, the programmer, lies across two domains: understanding the modern machine and your language's pain-points. This book will teach you to how to manage program performance on modern machines and build fast, memory-safe, and concurrent software in Rust. It starts with the fundamentals of Rust and discusses machine architecture concepts. You will be taken through ways to measure and improve the performance of Rust code systematically and how to write collections with confidence. You will learn about the Sync and Send traits applied to threads, and coordinate thread execution with locks, atomic primitives, data-parallelism, and more. The book will show you how to efficiently embed Rust in C++ code and explore the functionalities of various crates for multithreaded applications. It explores implementations in depth. You will know how a mutex works and build several yourself. You will master radically different approaches that exist in the ecosystem for structuring and managing high-scale systems. By the end of the book, you will feel comfortable with designing safe, consistent, parallel, and high-performance applications in Rust.
Table of Contents (18 chapters)
Title Page
Copyright and Credits
Dedication
Packt Upsell
Contributors
Preface
Index

Embedding Rust


So far, we've seen how to embed C and Lua into Rust. But, what if you want to combine Rust into other programming languages? Doing so is a very handy technique for improving runtime performance in interpreted languages, making memory-safe extensions where once you might have been using C or C++. If your target high-level language has difficulty with concurrency embedding, Rust is a further win. Python programs suffer in this regard—at least those implemented on CPython or PyPy—because of the Global Interpreter Lock, an internal mutex that locks objects' bytecode. Offloading computation of large blocks of data into a Rust + Rayon extension, for example, can be both straightforward to program and improve computation speed.

Well, great. How do we make this sort of thing happen? Rust's approach is simple: if you can embed C, you can embed Rust.

Into C

Let's embed some Rust into C. The quantiles library (https://crates.io/crates/quantiles)—discussed in Chapter 4, Sync and Send – the...