Polyphony VS Concurrent Ruby

When using green threads/fibers/coroutines, an interesting technique to make signal handling safer is to run the signal handler asynchronously on a separate fiber/green thread. That way most of the problems of dealing with signals go away, and there's basically no limitation on what you can do inside the signal handler.

I've successfully used this technique in Polyphony [1], a fiber-based Ruby gem for writing concurrent programs. When a signal occurs, Polyphony creates a special-purpose fiber that runs the signal handling code. The fiber is put at the head of the run queue, and is resumed once the currently executed fiber yields control.

[1] https://github.com/digital-fabric/polyphony

Read the release notes here: https://github.com/orgs/digital-fabric/discussions/110 The Polyphony docs: https://www.rubydoc.info/gems/polyphony The Polyphony repository: https://github.com/digital-fabric/polyphony

Polyphony is a gem for building highly-concurrent Ruby programs. It utilizes Ruby fibers to provide a high-performance safe environment for launching any number of concurrent operations. Under the hood, Polyphony employs io_uring to maximize I/O performance (libev is used on platforms other than recent Linux kernels).

Is monkey-patching inherently bad? Should its use make Polyphony illegitimate? These are the questions I'm exploring in my latest article.

how is this diff from: https://github.com/digital-fabric/polyphony

Infinite loops are great for expressing long-running concurrent operations. In this article I’ll discuss the use of infinite loops as a major construct when writing concurrent apps in Ruby using Polyphony. I’ll show how infinite loops differ from normal, finite ones; how they can be used to express long-running tasks in a concurrent environment; and how they can be stopped. Read it now!

Polyphony is a library for writing highly concurrent Ruby apps. Polyphony harnesses Ruby fibers and a powerful io_uring-based I/O runtime to provide a solid foundation for building high-performance concurrent Ruby apps.

> Curious if there’s anything public about improving ruby performance from the I/O angle mentioned in the post.

I'm currently working on Polyphony [0], a Ruby gem for writing highly-concurrent Ruby apps. It uses Ruby fibers under the hood, and does I/O using io_uring (on Linux, there is also a libev-based backend).

[0] https://github.com/digital-fabric/polyphony

After this, I took a look at the semaphore class in the popular library, concurrent-ruby to see how they implement it, and I learnt about something new: condition variables. And Ruby comes with this included!

https://github.com/ruby-concurrency/concurrent-ruby has great docs if someone is looking for alternatives.

I wonder how this would compare to using concurrent-ruby under ruby 2.7, especially in a real-world setting (where the calls are actually to external services that return and buffer data, instead of just sleep). The author says that he's felt that ruby threads "feel easy to mess up," but I've found that concurrent-ruby makes it pretty simple, and performant enough even with the GIL.

As I could not find a clear example about how to rescue exceptions from Concurrent::Promises (part of the Concurrent Ruby gem ) I read through the documentation and here are two examples: one that documents success case and one that shows what is happening when there is an error.

In a sense the GIL (or actually GVL as it's called in current ruby versions) has already been removed for ruby.

It's only the original MRI Ruby that still has it several over Ruby implementations already removed it. e.g. JRuby.

Concurrent-Ruby[1] is probably a good place to start if you want to work with GVL free ruby on JRuby. It's quite well supported and is currently used by Rails.

If you just want async or non-blocking IO I'd take a look at the Async Gem[2]. It looks pretty solid in Ruby > 3.0 and it's been invited by Matz to be part of the stdlib, which I think is a pretty good endorsement.

For MRI itself I don't think it's likely they'll ever remove the GVL. Ractors are probably a better solution for CPU concurrency in the long run, although I think they're pretty experimental currently.

1. https://github.com/ruby-concurrency/concurrent-ruby

I like how the article exposes you to tools to prove/disprove the problem. I would have hoped it introduced to tools like concurrent ruby and the use of atomics like u/Freeky already mentioned though.

Using conccurrent-ruby, how can I execute a set of promises and then get the results?

I’d highly recommend the concurrent-ruby gem that has implementations of various metaphors of concurrency, from async to promises, as well as edge features such as actors.

You may want to consider using something like concurrent-ruby that provides nice abstractions over multithreading.