[swift-evolution] [Concurrency] async/await + actors
bspratling at mac.com
Sun Aug 20 13:01:27 CDT 2017
It’s good to have a formal, language supported way to manage these aspects of concurrency.
In particular, I like that it establishes the asynchronously provided values into the surrounding scope, like guard. This helps me write a clean sequence of calls with access to values which ‘skip’ a call. Often I need to make a few asynchronous calls which fetch disparate value types from disparate endpoints or frameworks and then provide them all together into some final API.
I also like that the actor model formally wraps up access to shared resources. It seems using these together, the compiler would be able to do some fundamental reasoning about whether deadlocks could occur (or preventing them entirely without expensive run-time mechanisms) and also determine if certain code paths were forgotten. One question I have is “how do we assign queues or priorities to the async methods?” I had been toying with the idea of declaring a reference to the queue on which async methods run at their definition of the method, but this actor model groups around the data which which needs coordination instead, which is possibly better.
I haven’t yet read the philosophy links, so if I’m repeating ideas, or these ideas are moot in light of something, I guess ignore me, and I’ll just feel slightly embarrassed later.
However, at the UI level we often don’t even use the GCD methods because they do not directly support cancelation and progress reporting, so we use NSOperation and NSOperationQueue instead. To me, adding a language feature which gets ignored when I build any full-featured app won’t be worth the time. Whatever is done here, we need to be cognizant that someone will implement another layer on top which does provide progress reporting and cancellation and make sure there’s a clean point of entry, much like writing the Integer protocols didn’t implement arbitrary-sized integers, but gave various implementations a common interface.
I know that data parallelism is out of scope, but GPU’s have been mentioned. When I write code which processes large amounts of data (whether that’s scientific data analysis or exporting audio or video tracks), it invariably uses many different hardware resources, files, GPU’s and others. The biggest unsolved system-level problem I see (besides the inter-process APIs mentioned) is a way to effectively “pull” data through the system, instead of the current “push”-oriented API’s. With push, we send tasks to queues. Perhaps a resource, like reading data from a 1000 files, is slower than the later stage, like using the GPU to perform optimal feature detection in each file. So my code runs fine when executed. However, later I add just a slightly slower GPU task, now my files fill up memory faster than my GPU’s drain it, and instead of everything running fine, my app exhausts memory and the entire process crashes. Sure I can create a semaphore to read only the “next" file into memory at a time, but I suppose that’s my point. Instead of getting to focus on my task of analyzing several GB’s of data, I’m spending time worrying about creating a pull asynchronous architecture. I don’t know whether formal “pull” could be in scope for this next phase, but let’s learn from the problem of the deprecated “current queue” function in GCD which created a fundamental impossibility of writing run-time safe “dispatch_sync” calls, and provide at least the hooks into the system-detected available compute resources. (If “get_current_queue” had provided a list of the stack of the queues, it would have been usable.)
Together with the preceding topic is the idea of cancellation of long-running processes. Maybe that’s because the user needs to board the train and doesn’t want to continue draining power while exporting a large video document they could export later. Or maybe it’s because the processing for this frame of the live stream of whatever is taking too long and is going to get dropped. But here we are again, expressing dependencies and cancellation, like the high level frameworks.
I’m glad someone brought up NSURLSessionDataTask, because it provides a more realistic window into the kinds of features we’re currently using. If we don’t design a system which improves this use, then I question whether we’ve made real progress.
NSBlockOperation was all but useless to me, since it didn’t provide a reference to ‘self’ when its block got called, I had to write a subclass which did so that it could ask itself if it had been cancelled to implement cancellation of long-running tasks. NSOperation also lacks a clean way to pass data from one block to those dependent on it. So there’s lots of subclasses to write to handle that in a generic way. I feel like block-based undo methods understood this when they added the separate references to weakly-held targets. That enabled me to use the framework methods out of the box.
So my point is not that these problems need to be solved at the language level, but that we aren’t spending a large amount of time designing and implementing a glorious system which will be used inside some wrapper functions like an UnsafeMutableRawPointer (is that the right name, I can’t ever remember.), and then become useless once anyone starts building any real-world app, UI or server-side. UnsafeMutableRawPointer has its place, but for the vast majority of app developers, they’ll likely never use it, and thus it doesn’t deserve years of refining.
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