What’s the Difference Between Multiprocessing, Multithreading, and Other Concurrency Concepts?

Honestly, it can get really confusing! I’ve been a developer for decades and still find these terms a bit ambiguous. I’d say they don’t cover all the possible scenarios out there. Most folks throw these terms around without really knowing what they mean. Don’t worry too much about the labels; just focus on understanding the techniques involved.

If you have other terms or concepts in mind, feel free to share so we can clear up any confusion!

All of these terms essentially deal with executing multiple instructions at the same time. The mechanics can differ—like using multiple CPU cores or even leveraging GPU. What's key is that you need certain programming techniques to handle these environments safely. Check out the 'concurrent computing' wiki page; it has a nice breakdown of various constructs and their applications across languages.

Here’s a quick rundown:
- **Parallel Processing**: This is when you run multiple computation streams simultaneously, requiring software that can leverage multiple processing cores.
- **Multithreading**: This is a type of parallel processing that involves multiple threads of execution within the same process.
- **Multiprocessing**: Similar to multithreading, but here you're using multiple processes that typically communicate through shared memory, signals, or sockets.
- **Concurrency**: This is about managing multiple tasks at once, but not necessarily running them at the same exact time.
- **Multiprogramming**: This is how an operating system gives the illusion that multiple programs are running at once, by rapidly switching between them even if there’s only one core. The OS scheduler manages this.

Remember, concurrency doesn’t always mean parallelism. A system can be concurrent without executing tasks in parallel, especially in cases like event-driven programming!

Instead of getting bogged down with terms, it might be more helpful to focus on how you can use concurrency practically. You can either send messages between processes or share memory.

For message passing, you create a pipe between processes to transfer data, which is great for low amounts of data and program communication. However, if you’re sharing memory, be careful about concurrent access—this is where atomic operations and mutexes come in handy to ensure safe data manipulation.

Just to clarify:
- **Concurrency** allows you to run multiple routines in the same time span, but they might not run at the exact same time—this is often done via context switching on a single core.
- **Parallelism** is a specific type of concurrency where routines actually execute simultaneously, requiring multiple CPU cores.
- **Multithreading** is a technique that achieves both concurrency and parallelism, with the potential for threads to run on separate cores or context-switch on the same core.