alt Hacker NewsSide question as I am following zig only losely and do Go Programming:
Zig has the feature that you can drop in your allocator from the caller. Now with 0.16 you also "bring your own IO" implementation with you.
And for my understanding this looks like the pattern Go uses with its Context package, where you pass in transitive data, cancellation signals and timers to for example stop an SQL query in server B, since a user canceled a web request in their browser before hitting server A, whilst all elements delegate the Context.
Then yesterday was total unrelated article about NUMA architecture, and I remember somewhere that the creator of Erlang mentioned (Joe Armstrong) that you cannot get around physics and it takes time to call a function between servers, therefore so not try to hide the latency between the calls.
And now to my question:
Would that in any way make sense for zig to go even more in this direction, where you pass in your allocator, IO, but now with something similar to Google Go context, but have it even more fine grained?
So that your functions could actually in their interface expose somehow the time in between CPU cores (NUMA) up to the request cancellation as Google go context is used for timeout signals, cancellation signals.
Also probably making time an external dependency as well.
So in essence , every function would be treated as a remote procedure calls, whereas remote would mean: "other cpu", other server/service
Replies
not really sure what you're asking. but time is now part of the io interface, so you can pretty easily write your own io implementation that just stubs out to the stdlib's default io content and has custom time functions if you want to try something funky. This is pretty close to what you are asking for (and in terms of functionality, equivalent). I say go for it and see what happens, report back!
What Zig is doing is called "capability passing". I don't know if the Zig team is aware of this field of work, or have independently arrived upon it, but that's what is achieved by passing IO, memory allocators, and other stuff around.
The core idea is that you create a "capability" for any action you want to track, such as using IO, allocating memory, or in your example making cross core or cross server calls. Now to perform these actions code has to have access to the capability. It's a very simple, but powerful, model.
The Effekt language formalizes this, and adds safety properties: https://effekt-lang.org/ Scala 3 also has this.
The papers are pretty readable, if you ignore the middle bits which go into the formal models.