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Hands-On Concurrency with Rust

Hands-On Concurrency with Rust

By : Brian L. Troutwine
4.7 (7)
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Hands-On Concurrency with Rust

Hands-On Concurrency with Rust

4.7 (7)
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 (12 chapters)
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Sync and Send

There are two key traits that the parallel Rust programmer must understand—Send and Sync. The Send trait is applied to types that can be transferred across thread boundaries. That is, any type T: Send is safe to move from one thread to another. Rc<T>: !Send means that it is explicitly marked as being unsafe to move between threads. Why? Consider if it were marked Send; what would happen? We know from the previous chapter that Rc<T> is a boxed T with two counters in place for weak and strong references to T. These counters are the trick. Suppose we spread an Rc<T> across two threads—call them A and B—each of which created references, dropped them, and the like. What would happen if both A and B dropped the last reference to Rc<T> at the same time? We have a race between either thread to see which can deallocate...

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