Not really. I’ve observed async code often is written in such a way that it doesn’t maximize how much concurrency can be expressed (eg instead of writing “here’s N I/O operations to do them all concurrently” it’s “for operation X, await process(x)”). However, in a threaded world this concurrency problem gets worse because you have no way to optimize towards such concurrency - threads are inherently and inescapably too heavy weight to express concurrency in an efficient way.
This is is not a new lesson - work stealing executors have long been known to offer significantly lower latency with more consistent P99 than traditional threads. This has been known since forever - in the early 00s this is why Apple developed GCD. Threads simply don’t provide any richer information it needs in the scheduler to the kernel about the workload and kernel threads are an insanely heavy mechanism for achieving fine grained concurrency and even worse when this concurrency is I/O or a mixed workload instead of pure compute that’s embarrassingly easily to parallelize.
Do all programs need this level of performance? No, probably not. But it is significantly more trivial to achieve a higher performance bar and in practice achieve a latency and throughput level that traditional approaches can’t match with the same level of effort.
You can tell async is directionally kind of correct in that io_uring is the kernel’s approach to high performance I/O and it looks nothing like traditional threading and syscalls and completion looks a lot closer to async concurrency (although granted exploiting it fully is much harder in an async world because async/await is an insufficient number of colors to express how async tasks interrelate)
But as you observed, async/await fails to express concurrency any better. It’s also a thread, it’s just a worse implementation.
Your premise is wrong. There are many counterexamples to this.
Sure, but once you involve the kernel and OS scheduler things get 3 to 4 orders of magnitude slower than what they should be.
The last time I was working on our coroutine/scheduling code creating and joining a thread that exited instantly was ~200us, and creating one of our green threads, scheduling it and waiting for it was ~400ns.
You don't need to wait 10 years for someone else to design yet another absurdly complex async framework, you can roll your own green threads/stackful coroutines in any systems language with 20 lines of ASM.
2. Unchecked array operations are a lot faster. Manual memory management is a lot faster. Shared memory is a lot faster.
Usually when you see someone reach for sharp and less expressive tools it’s justified by a hot code path. But here we jump immediately to the perf hack?
3. How many simultaneous async operations does your program have?
For example, if you don't explicitly call the java.awt.Toolkit.sync() method after updating the UI state (which according to the docs "is useful for animation"), Swing will in my experience introduce seemingly random delays and UI lag because it just doesn't bother sending the UI updates to the window system.
I thought it was because they could copy chromium.
Which inputs are getting latency? The keyboard? The files?
> the non blocking nature
But God help you if you have to change the code. Async threads are a way to organize it and make it workable for humans.
Absolutely not
When it comes time to test your concurrent processing, to ensure you handle race conditions properly, that is much easier with callbacks because you can control their scheduling. Since each callback represents a discrete unit, you see which events can be reordered. This enables you to more easily consider all the different orderings.
Instead with threads it is easy to just ignore the orderings and not think about this complexity happening in a different thread and when it can influence the current thread. It isn't simpler, it is simplistic. Moreover, you cannot really change the scheduling and test the concurrent scenarios without introducing artificial barriers to stall the threads or stubbing the I/O so you can pass in a mock that you will then instrument with a callback to control the ordering...
The problem with callbacks is that the call stack when captured isn't the logical callstack unless you are in one of the few libraries/runtimes that put in the work to make the call stacks make sense. Otherwise you need good error definitions.
You can of course mix the paradigms and have the worst of both worlds.
There is one hill I'll die on, as far as programming languages go, which is that more people should study Céu's structured synchronous concurrency model. It specifically was designed to run on microcontrollers: it compiles down to a finite state machine with very little memory overhead (a few bytes per event).
It has some limitations in terms of how its "scheduler" scales when there are many trails activated by the same event, but breaking things up into multiple asynchronous modules would likely alleviate that problem.
I'm certain a language that would suppprt the "Globally Asynchronous, Locally Synchronous" (GALS) paradigm could have their cake and eat it too. Meaning something that combines support for a green threading model of choice for async events, with structured local reactivity a la Céu.
F'Santanna, the creator of Céu, actually has been chipping away at a new programming language called Atmos that does support the GALS paradigm. However, it's a research language that compiles to Lua 5.4. So it won't really compete with the low-level programming languages there.
If your threads are "free" you can just run 400 copies of a synchronous code and blocking in one just frees the thread to work on other. async within same goroutine is still very much opt in (you have to manually create goroutine that writes to channel that you then receive on), it just isn't needed where "spawn a thread for each connecton" costs you barely few kb per connection.
except when a RAM fetch is so expensive a load is basically an async call - and it's a single machine code instruction at the same time
Every explanation of the feature starts with managing callback hell.
Threads offer concurrent execution, async (futures) offer concurrent waiting. Loosely speaking, threads make sense for CPU bound problems, while async makes sense for IO bound problems.
For problems that aren't overly concerned with performance/memory, yes. You should probably reach for threads as a default, unless you know a priori that your problem is not in this common bucket.
Unfortunately there is quite a lot of bookkeeping overhead in the kernel for threads, and context switches are fairly expensive, so in a number of high performance scenarios we may not be able to afford kernel threading
But what you said about kernel implementation is true. But are we really saying that the primary motivation for async/await is performance? How many programmers would give that answer? How many programs are actually hitting that bottleneck?
Doesn’t that buck the trend of every other language development in the past 20 years, emphasizing correctness and expressively over raw performance?
Of course - what else would it be? The whole async trend started because moving away from each http request spawning (or being bound to) an OS thread gave quite extreme improvements in requests/second metrics, didn't it?
What I question is whether 1. Most programs resemble that, so that they make it an invasive feature of every general purpose language. 2. Whether programmers are making a conscious choice because they ruled out the perf overhead of the simpler model we have by default.
The original motivation for not using OS threads was indeed performance. Async/await is mostly syntax sugar to fix some of the ergonomic problems of writing continuation-based code (Rust more or less skipped the intermediate "callback hell" with futures that Javascript/Python et al suffered through).
It's all nuanced and what to choose requires careful evaluation.
Most stacks are tiny and have bounded growth. Really large stacks usually happen with deep recursion, but it's not a very common pattern in non-functional languages (and functional languages have tail call optimization). OS threads allocate megabytes upfront to accommodate the worst case, which is not that common. And a tiny stack is very fast to copy. The larger the stack becomes, the less likely it is to grow further.
>cannot have pointers to stack objects
In Go, pointers that escape from a function force heap allocation, because it's unsafe to refer to the contents of a destroyed stack frame later on in principle. And if we only have pointers that never escape, it's relatively trivial to relocate such pointers during stack copying: just detect that a pointer is within the address range of the stack being relocated and recalculate it based on the new stack's base address.
Yes, you're not getting Rust performance (tho good part of it is their own compiler vs using all LLVM goodness) but performance is good enough and benefits for developers are great, having goroutines be so cheap means you don't even need to do anything explicitly async to get what you want
Now the languages that don't offer choice is another matter.
I also want to address something that I've seen in several sub-threads here: Rust's specific async implementation. The key limitation, compared to the likes of Go and JS, is that Rust attempts to implement async as a zero-cost abstraction, which is a much harder problem than what Go and JS does. Saying some variant of "Rust should just do the same thing as Go", is missing the point.