Chapter 22: Concurrency with Operating System Threads

Concurrency enables software to handle multiple tasks by allowing them to make progress independently, often improving responsiveness and throughput. This is crucial for modern applications, such as servers managing multiple client connections or computational tools utilizing multi-core processors for faster results. However, traditional languages like C and C++ present significant challenges in concurrent programming, primarily due to the risks of data races and deadlocks. These issues often manifest as difficult-to-reproduce runtime errors or undefined behavior, demanding meticulous programmer discipline and extensive debugging.

Rust confronts these challenges head-on through its ownership and type system, enabling what the community often calls fearless concurrency. By enforcing strict rules about data access at compile time, Rust eliminates data races—a major category of concurrency bugs—in safe code. This chapter delves into Rust’s approach to concurrency using operating system (OS) threads. We will cover thread creation and management, synchronization primitives (Mutex, RwLock, Condvar, atomics), strategies for sharing data between threads (Arc, scoped threads), message passing via channels, data parallelism facilitated by the Rayon library, and a brief introduction to SIMD for instruction-level parallelism. The discussion of async tasks, another concurrency model in Rust suited for I/O-bound workloads, will be deferred to a subsequent chapter. Throughout this chapter, we will draw comparisons to C and C++ concurrency models to highlight Rust’s safety mechanisms and how they differ.