If anywhere down the callstack a function needs to await something it has to become an async function. And this needs to be done to the whole callstack recursively. So over time more and more functions of every codebase turn into async functions.
Continuation passing style means passing along your continuation to your callee, and is the implementation of the async model. But normal calls do pass their continuation: the return address, pushed on the stack, is the continuation function, and the stack itself is the scope, and together they are a closure. Make the stack a first class value that can be switched, and you get to continuations - and that's what the runtime gets with green threads.
It means much harder interop because you can't have native frames on your stack. But you have the same problem with async.
With the normall call/return model, the implicit continuation in a normal call stack can only be accessed via return. Green threads do allow accessing the continuation at specific yield points (although most green thread implementations do not expose it to the user) but because the yield point are much fewer than every single call, a whole stack can be allocated and used in one go. There aren't in fact many issues with interoperability as foregin functions or even os calls can be accommodated on this stack.
Async is a tradeoff, basically the programmer is responsible of marking functions that are to be CPS transformed and that need their stack frame reified. This way no full stack is needed nor there are the performance and interoperability issues of full CPS. You end up with the blue/red functions issue though.
Note that you don't get the continuation in hand for the async-everywhere advocated by GP, only blocking operations get the continuation, and most of those are implemented by the runtime.
I’m curious if discerning which is the best type is possible to tool automatically with static or tracing analysis.
Or you go with cactus stacks which have their own set of issues.
More wasteful than writing each function twice? See C# for endless examples of libraries that have manual duplicate X() and XAsync() for every single method. If you compare the two they're almost always have the exact same body, except the async version has "async" and "await" peppered in and calls duplicate XAsync methods (which are implemented the same, except they call XAsync methods... you might be seeing a pattern here).
If I'm not mistaken most rust doesn't use separate compilation and is built from source. In this case the compiler can treat it just like normal generics and just not compile it until it's used. And even with separate compilation for, e.g. a library, a very basic LTO would trivially trim out the unused methods when compiled into a final binary. And if you don't want 2x library itself, even then you can just use an escape hatch to turn it of on the crate/impl/function level and it's still better for you than the status-quo where you have to manually add a bunch of tokens and junk that the compiler already knows how to do precisely.
If anything is wasted it's human effort because we're wasting our time doing something the computer can do better and faster.
> "annotations in the object file to describe the frame size"
Wouldn't you need this anyway for anything async, even if it's manual? This seems like an argument against async in general, not automatic async.
I think that a good compromise would be implicitly inferring the 'async-ness' of template functions instantiation (or whatever they are called in your language of choice) based on a magic continuation parameter, which would also go around the separate compilation issue (assuming the language does generic monomorphization).
The point is that only at the very top of the call stack or the very bottom should you ever need to care or think about whether code is async, because 99% of the time (every bit of code between main and syscalls... which is almost all of it) that's the only place you should need to care. This can be completely automatic because the compiler already knows where to insert await/async, it only needs to know when to use async (decided by main) and what to call at the end (decided by the syscall funcs).
If I have a sync function and I call something async, I should be able to just .wait() it, I think, and get the sync behavior.
Futhermore, in any complex asynchronous I/O app most functions will end up being tagged async. The only ones that won't are simple leaf functions that wouldn't implicitly yield, anyhow. If someone has the bad idea to, e.g., put a yield point in non-obvious leaf functions as part of some kind of hack (e.g. logging, tracing), they're gonna do it in the async/await case, too, because they're already convinced it has value. Having to a drop a few more annotations here or there won't stop them from breaking the app.
Lastly, the bugs that do occur in these sorts of cases usually have to do with unpredictable latencies violating implicit or accidental ordering assumptions. async/await doesn't mitigate that at all because latencies are just as unpredictable. The solution, as always, is to avoid these ordering dependencies by not sharing mutable state.
This defense of async/await is a red herring.
Rust has gone back and forth on this. Pre-1.0 versions of Rust had a "green threads" mode. It was removed in favor of OS threads because it wasn't worth the complexity.
Go is a language in which "all functions are async" and it's pretty cool. But it needs a runtime, and interop with C / C++ has some real overhead related to switching to a C-style stack. Rust did not want to make those compromises, it wanted to be appropriate for bare-metal or kernel programming, and for libraries used by big high-performance C++ applications. In these cases, Go's model does not work well.
I personally use Go a lot, it's great for network services and command-line tools, and that's mostly what I do.
I don't think there's anything about Go's concurrency model that precludes bare metal; I think it's just that the maintainers didn't want to support a bare metal runtime. In fact, I recall at least one other project that modified Go's runtime to support exactly this. I'm also not sure how much of the C interop overhead is due to the different stack models and how much is due to GC concerns or other things. But generally I agree with you--in practice Rust is well suited for these types of tasks and Go is not.
Async has come to signify a very specific implementation strategy (i.e. stackless coroutines). Go definitely went in another direction.
In practice, most of your threads are in one form of wait loop or another and you've just got polling both inside the threads and with the scheduler.
Have a look at Erlang if you want a better model :) the erlang "processes" (different to os processes) can intelligently only wake up when there is work for them to do.
For a language to efficiently use cores, it really needs to include it's own scheduling.
There are also costs in setting and checking those locks etc. Sure, you can build solutions to optimise a broken model, which we've done over decades (with quite a bit of success!), but it doesn't make the model less broken.
Sure you do, there is noticable memory and ctx switching overhead(for large no. of them ofc) in stackful coroutines.
Erlang works the same way. The VM scheduler will only context switch on a function call. for or while loops don't exist in Erlang which means there is no risk of blocking the scheduler.
The reason that m:n threading went out of style is that, for CPU bound tasks (where you want to run exactly as many threads as there are CPUs), it is just useless overhead, while for the hundreds of thiusands of IO bound threads scenarios, the cost of stack switching is dominated by cache misses anyway, and the cost of calling into the kernel is amortized by the fact that IO requires a call inti elevated privileges anyway. At the sametime kernel threads scheduling has become very fast and userspace threads, which requirea whole stack of their own are not significantly more lightweight than kernel threads.
The modern async model is a compromise. On one side, the 'threads' consist of a single stack frame are very light weight, on the other side there is no generic userspace scheduler, but scheduling is fully controlled by the application.
You can build threading on top of it but also all kind of other abstractions.
Making every function call asynchronous is likely to make most programs a lot slower.
If we did the whole problem async (async by default as I interpret it) it would require so much bookkeeping to keep causality that would make it unreasonably difficult. For things that require causality like that, we are lucky that the default mode of computation is synchronous because it fits my problem domain perfectly.
That's why I say "not everything is web" because while async maps well to problems like a server-client type application, it doesn't map well to all problems like my problem for example. Also, as someone else said, sync is easier to reason about for problems that don't require a lot of parallelism.
At best, some of your CPUs would be able to run calculations for two especially fast-to-compute pieces of volume space, while some other CPUs would be busy computing a particularly gnarly block of the volume space.
For those CPU bound jobs that do not fit in the classical openmp style scheduling, more dynamic async style scheduling might be appropriate (cilk style work stealing for example) but the async granularity is hardly ever the function boundary.
Which doesn't mean it's bad. I'm excited about tokio and rust's async story. But I love that I get to choose.
Just dealt with that in a .NET app that uses a 3rd party SDK that heavily uses async/wait. I had to build a whole layer of state management to just handle shutdowns. Simple threading would have been much easier.
It's different with server side code. There async/await is very nice.
[1] https://developer.mozilla.org/en-US/docs/Web/JavaScript/Refe...
In a browser on or server side it's different.
https://docs.rs/tokio-threadpool/0.1/tokio_threadpool/fn.blo...
And it’ll likely pull in some nice features from academia like, building a dependency graph of async statements so it can automatically reorder async statements to get optimal concurrency.
And the reordering of statements exists too. It's called ApplicativeDo[0] and is heavily used at Facebook[1]
[0] https://www.microsoft.com/en-us/research/wp-content/uploads/...
According to a famous quote, the source of which escapes me, "await does not wait for anything, and async is not asynchronous." (This could be specific to C# though.)