Concurrency

This section covers concurrent and parallel programming.

Recipe	Crates	Categories
Spawn, join
Scoped threads
Rayon - parallel processing
Parallel iteration
Parallel sorting
Custom parallel tasks

Recipe	Crates	Categories
Mutate the elements of an array in parallel
Test in parallel if any or all elements of a collection match a given predicate
Search items using given predicate in parallel
Sort a vector in parallel
Map-reduce in parallel
Generate jpg thumbnails in parallel

Recipe	Crates	Categories
Spawn a short-lived thread
Create a parallel pipeline
Pass data between two threads
Maintain global mutable state
Calculate SHA256 sum of *.iso files concurrently
Draw fractal dispatching work to a thread pool
Channels
crossbeam-channel
crossbeam-channel
flume
tokio
postage

Recipe	Crates	Categories
Multiple producers, single consumer
Crossbeam_channel

Parallelism

• True simultaneous execution of multiple tasks on multiple cores or processors.

• Mechanism: uses operating system threads.

• Important for CPU-heavy computations.

• Often requires explicit management of threads and thread pools.

• Requires careful synchronization to prevent data races (using mechanisms like Mutexes or atomics).

• Overhead due to thread creation and switching.

Key constructs in Rust:

• Threads are independent units of execution that can be spawned using e.g. std::thread::spawn.
• Mutexes e.g. std::sync::Mutex protect shared data from race conditions.
• Channels e.g. std::sync::mpsc allow threads to communicate and exchange data.

Here are the topics we’ll cover:

• Multithreading⮳
• Message passing⮳
• Shared-state concurrency⮳
• Concurrent data structures⮳

See Also