Io_uring, kTLS and Rust for zero syscall HTTPS server(blog.habets.se) |
Io_uring, kTLS and Rust for zero syscall HTTPS server(blog.habets.se) |
> The io-uring crate doesn’t help much with this. The API doesn’t allow the borrow checker to protect you at compile time, and I don’t see it doing any runtime checks either.
I've seen comments like this before[1], and I get the impression that building a a safe async Rust library around io_uring is actually quite difficult. Which is sort of a bummer.
IIRC Alice from the tokio team also suggested there hasn't been much interest in pushing through these difficulties more recently, as the current performance is "good enough".
Think about it for a second. Why do we not have this problem with "synchronous" syscalls? When you call `read` you also "pass mutable borrow" of the buffer to the kernel, but it maps well into the Rust ownership/borrow model since the syscall blocks execution of the thread and there are no ways to prevent it in user code. With poll-based async model you side-step this issues since you use the same "sync" syscalls, but which are guaranteed to return without blocking.
For a completion-based IO to work properly with the ownership/borrow model we have to guarantee that the task code will not continue execution until it receives a completion event. You simply can not do it with state machines polled in user code. But the threading model fits here perfectly! If we are to replace threads with "green" threads, user Rust code will look indistinguishable from "synchronous" code. And no, the green threads model can work properly on embedded systems as demonstrated by many RTOSes.
There are several ways of how we could've done it without making the async runtime mandatory for all targets (the main reason why green threads were removed from Rust 1.0). My personal favorite is introduction of separate "async" targets.
Unfortunately, the Rust language developers made a bet on the unproved polling stackless model because of the promised efficiency and we are in the process of finding out whether the bet plays of or not.
That's not really true. The only guarantees in Rust futures are that they are polled() once and must have their Waker's wake() called before they are polled again. A completion based future submits the request on first poll and calls wake() on completion. That's kind of the interesting design of futures in Rust - they support polling and completion.
The real conundrum is that the futures are not really portable across executors. For io_using for example, the executor's event loop is tightly coupled with submission and completion. And due to instability of a few features (async trait, return impl trait in trait, etc) there is not really a standard way to write executor independent async code (you can, some big crates do, but it's not necessarily trivial).
Combine that with the fact that container runtimes disable io_uring by default and most people are deploying async web servers in Docker containers, it's easy to see why development has stalled.
It's also unfair to mischaracterize design goals and ideas from 2016 with how the ecosystem evolved over the last decade, particularly after futures were stabilized before other language items and major executors became popular. If you look at the RFCs and blog posts back then (eg: https://aturon.github.io/tech/2016/09/07/futures-design/) you can see why readiness was chosen over completion, and how completion can be represented with readiness. He even calls out how naïve completion (callbacks) leads to more allocation on future composition and points to where green threads were abandoned.
No, this is a mistaken retelling of history. The Rust developers were not ignorant of IOCP, nor were they zealous about any specific async model. They went looking for a model that fit with Rust's ethos, and completion didn't fit. Aaron Turon has an illuminating post from 2016 explaining their reasoning: https://aturon.github.io/tech/2016/09/07/futures-design/
See the section "Defining futures":
There’s a very standard way to describe futures, which we found in every existing futures implementation we inspected: as a function that subscribes a callback for notification that the future is complete.
Note: In the async I/O world, this kind of interface is sometimes referred to as completion-based, because events are signaled on completion of operations; Windows’s IOCP is based on this model.
[...] Unfortunately, this approach nevertheless forces allocation at almost every point of future composition, and often imposes dynamic dispatch, despite our best efforts to avoid such overhead.
[...] TL;DR, we were unable to make the “standard” future abstraction provide zero-cost composition of futures, and we know of no “standard” implementation that does so.
[...] After much soul-searching, we arrived at a new “demand-driven” definition of futures.
I'm not sure where this meme came from where people seem to think that the Rust devs rejected a completion-based scheme because of some emotional affinity for epoll. They spent a long time thinking about the problem, and came up with a solution that worked best for Rust's goals. The existence of a usable io_uring in 2016 wouldn't have changed the fundamental calculus.
&mut references are exclusive and non-copyable, so the hot potato approach can even be used within their scope.
But the problem in Rust is that threads can unwind/exit at any time, invalidating buffers living on the stack, and io_uring may use the buffer for longer than the thread lives.
The borrow checker only checks what code is doing, but doesn't have power to alter runtime behavior (it's not a GC after all), so it only can prevent io_uring abstractions from getting any on-stack buffers, but has no power to prevent threads from unwinding to make on-stack buffer safe instead.
Fn(_: T) -> TWell, I think there is interest, but mostly for file IO.
For file IO, the situation is pretty simple. We already have to implement that using spawn_blocking, and spawn_blocking has the exact same buffer challenges as io_uring does, so translating file IO to io_uring is not that tricky.
On the other hand, I don't think tokio::net's existing APIs will support io_uring. Or at least they won't support the buffer-based io_uring APIs; there is no reason they can't register for readiness through io_uring.
High throughput network usecases that don’t need/want AF_XDP or DPDK can get most of the speedup with ‘sendmmsg/recvmmsg’ and segmentation offload.
As an example this library I wrote before is cancel safe and doesn’t use lifetimes etc. for it.
It is just a PITA to get it fully right.
Probably need the buffer to come from the async library so user allocates the buffers using the async library like a sibling comment says.
It is just much easier to not use Rust and say futures should run fully always and can’t be just dropped and make some actual progress. So I’m just doing it in zig now
Have your function signature be async fn read(buffer: &mut Vec<u8>) -> Result<…>’ (you can use something more convenient like ‘&mut BytesMut’ too). If you run the future to completion (success or failure), the argument holds the same buffer passed in, with data filled in appropriately on success. If you cancel/drop the future, the buffer may point at an empty allocation instead (this is usually not an annoying constraint for most IO flows, and footgun potential is low).
The way this works is that your library “takes” the underlying allocation before starting the operation out of the variable, replacing it with the default unallocated ‘Vec<u8>’. Once the buffer is no longer used by the IO system, it puts it back before returning. If you cancel, it manages the buffer in the background to release it when safe and the unallocated buffer is left in the passed variable.
Or maybe I've misunderstood?
Your write up connected some early knowledge from when I was 11 where I was trying to set up a database/backend and was finding lots of cgi-bin online. I realize now those were spinning up new processes with each request https://en.wikipedia.org/wiki/Common_Gateway_Interface
I remember when sendfile became available for my large gaming forum with dozens of TB of demo downloads. That alone was huge for concurrency.
I thought I had swore off this type of engineering but between this, the Netflix case of extra 40ms and the GTA 5 70% load time reduction maybe there is a lot more impactful work to be done.
https://netflixtechblog.com/life-of-a-netflix-partner-engine...
https://nee.lv/2021/02/28/How-I-cut-GTA-Online-loading-times...
I am patient to wait for the benchmarks so take your time ,but I honestly love how the author doesn't care about benchmarks right now and wanted to clean the code first. Its kinda impressive that there are people who have such line of thinking in this world where benchmarks gets maxxed and whole project's sole existence is to satisfy benchmarks.
Really a breath of fresh air and honestly I admire the author so much for this. It was such a good read, loved it a lot thank you. Didn't know ktls existed or Io_uring could be used in such a way.
I can recommend writing even the BPF side of things with rust using Aya[1].
On FreeBSD, its been in the kernel / openssl since 13, and has been one runtime toggle (sysctl kern.ipc.tls.enable=1) away from being enabled. And its enabled by default in the upcoming FreeBSD-15.
We (at Netflix) have run all of our tls encrypted streaming over kTLS for most of a decade.
Rust - you need to understand: Futures, Pin, Waker, async runtimes, Send/Sync bounds, async trait objects, etc.
C++20, coroutines.
Go, goroutines.
Java21+, virtual threads
So to reimplement my foundation (with all the bugs) will not be worth it.
I will however compare Javas NIO (epoll) with the new Virtual Threads IO (without pinning).
https://github.com/axboe/liburing/wiki/io_uring-and-networki...
Also there is napi support in uring which uses polled io on sockets instead of interrupt based io from what I understand. You can see examples using it in liburing github
In my experience “oversubscribing” threads to cores (more threads than cores) provides a wall-clock time benefit.
I think one thread per core would work better without preemptive scheduling.
But then we aren’t talking about Unix.
This works fine on Linux, and common approach for trading systems where it’s fine to oversubscribe a bunch of cores for this type of stuff. The cores are mostly busy spinning and doing nothing, so it’s very inefficient in terms of actual work, but great for latency and throughput when you need it.
It's not blanket good advice for all things.
Most developers are unfamiliar with the design idioms for TPC e.g. how to properly balance and shed load between cores.
In this very specific case, it seems as though the vast majority of the webserver's work is asynchronous and event-based, so the actual webserver is never waiting on I/O input or output - once it's ready you dump it somewhere the kernel can get to it and move on to the next request if there is one.
I think this gets this specific project close to the platonic ideal of a one-thread-per-core workload if indeed you're never waiting on I/O or any syscalls, but I feel as though it should come with extreme caveats of "this is almost never how the real world works so don't go artificially limiting your application to `nproc` threads without actually testing real-world use cases first".
io_uring is very cool tech though and has been progressing at an impressive pace the last few years.
It seems like there’s these fundamental things in OSes that we just can’t improve, or I suppose can’t without breaking too much backward compatibility, so we are forced to do this.
There's a software equivalent of the Peter Principle where software or an API becomes increasingly complex to the point where no one understands it. They then attempt to fix that by adding more functionality (complexity).
I am working on something like this for work. But with plain old C
> In order to avoid busy looping, both the kernel and the web server will only busy-loop checking the queue for a little bit (configurable, but think milliseconds), and if there’s nothing new, the web server will do a syscall to “go to sleep” until something gets added to the queue.
What a time to be alived that seconds to recompile is consider horrible devex.
every HTTP session was commonly a forked
copy of the entire server in the CERN
and Apache lineage!
The same model is possible in Apache httpd 2.x with the "prefork" mpm.
Depends on the workload.
Normally you would go read() -> write() so:
1. Disk -> page cache (DMA)
2. Kernel -> user copy (read)
3. User -> kernel copy (write)
4. Kernel -> NIC (DMA)
sendfile():
1. Disk -> page cache (DMA)
No user space copies, kernel wires those pages straight to the socket
2. Kernel -> NIC (DMA)
So basically, it eliminates 1-2 memory copies along with the associated cache pollution and memory bandwidth overhead. If you are running high QPS web services where syscall and copy overheads dominate, for example CDNs/static file serving the gains can be really big. Based on my observations this can mean double digit reductions in CPU usage and up to ~2x higher throughput.
sendfile effectively turns your user space file server into a control plane, and moves the data plane to where the data is eliminating copies between address spaces. This can be made congruent with I/O completions (i.e. Ethernet+IP and block) and made asynchronous so the entire thing is pumping data between completion events. Watch the Netflix video the author links in the post.
There is an inverted approach where you move all this into a single user address space, i.e. DPDK, but it's the same overall concept just a different who.
In any event it's essentially a stack frame so it's not a failure of zero-overhead, the stack frame will need to be somewhere.
Go: goroutines are not async. And you can't understand goroutines without understanding channels. And channels are weirdly implemented in Go, where the semantics of edge cases, while well defined, are like rolling a D20 die if you try to reason from first principles.
Go doesn't force you to understand things. I agree with that. It has pros and cons.
I see what you mean but "cheap threads" is not the same thing as async. More like "current status of massive concurrency". Except that's not right either. tarweb, the subject of the blog post in question, is single threaded and uses io_uring as an event loop. (the idea being to spin up one thread per CPU core, to use full capacity)
So it's current status of… what exactly?
Cheap threads have a benefit over an async loop. The main one being that they're easier to reason about. It also has drawbacks. E.g. each thread may be light weight, but it does need a stack.
Sure they are. The abstraction they provide is a synchronous API, but it's accomplished using an async runtime.
Without load the overhead of calling (effectively) sleep() is, while technically true, not relevant.
But sure, you can tweak the busyloop timers and burn 100% CPU on kernel and user side indefinitely if you want to avoid that sleep-when-idle syscall. It's just… not a good idea.
First, there are some tricks required to actually make it work at all, then there is a problem that you'll need a core not only for userland, but also inside the kernel, both of them per-application.
Sharing a kernel spinning thread across multiple applications is also possible but requires further efforts (you need to share some parent ring across processes, which need to be related).
Overall I feel that it doesn't really deliver on the no-system-call idea, certainly not out of the box. You might have a more straightforward experience with XDP, which coincidentally gives you a lot more access and control as well if you need it.
> This means that a busy web server can serve all of its queries without even once (after setup is done) needing to do a syscall. As long as queues keep getting added to, strace will show nothing.
For comparison a read/write over a TCP socket on loopback between two process is a few microseconds using BSD sockets API.
No? What they're saying is the busy loop will spin until an event occurs, for at most x ms. And if it does park the thread (the only syscall required), it can be immediately woken up on the first event too. Only if multiple events occurred since the last call would you receive them together. This normally happens only under high load, when event processing takes enough time to have a buildup of new events in the background. Increased latency is the intended outcome on high loads.
To be fair, it was a while ago I read the io-uring paper. But I distinctly recall the mix of poll and park behavior, plus configurable wait conditions. Please correct me if I'm wrong (someone here certainly knows).
For workloads that are a mix of IO and non-trivial CPU work, it can still work but is much, much harder to get right.
Evented I/O works out pretty well in practice for the I and D cache, especially if you can affine and allocate things as the article states, and do similar natural alignments inside the kernel (i.e. RSS/consistent hashing).
Which makes me sceptical for the argument for kTLS which is stated in the article; what benefit does offloading your crypto to the kernel provider (possibly making it more brittle). I've seen the author of haproxy say that performance he's seen has been only marginal, but did point out it was useful in that you can strace your process and see plaintext instead of ciphertext which is nice.
[1]: https://blog.tjll.net/reverse-proxy-hot-dog-eating-contest-c...
Has Ron Minnich's port of "Nix" (not NixOS as you may know it), to 9front.
The entire point of this is to disallow the kernel pre-empting and switching out CPU cores that should be dedicated to an "application". (Application Cores).
One could imagine this arrangement plus io_uring would be awfully nice.
And yes, for now async Rust is full of unnecessary Arc<T> and is very poorly made.
If you are forking from a language/ecosystem that is extremely thread-friendly, (e.g. Go, Java, Erlang) fork is more risky. This is because such runtimes mean a high likelihood of there being threads doing fork-unsafe things at the moment of fork().
If you are forking from a language/ecosystem that is thread-unfriendly, fork is less risky. That isn't to say "it's always safe/low risk to run fork() in e.g. Python, Ruby, Perl", but in those contexts it's easier to prove/test invariants like "there are no threads running/so-and-so lock is not held at the point in my program when I fork", at which point the risks of fork(2) are much reduced.
To be clear, "reduced" is not the same as "gone"! You still have to reason about explicitly taken locks in the forking thread, file descriptors, signal handlers, and unexpected memory growth due to CoW/GC interactions. But that's a lot more tractable than the Java situation of "it's tricky to predict how many Java threads are active when I want to fork, and even trickier to know if there are any JNI/FFI-library-created raw pthreads running, the GC might be threaded, and checking for each of those things is still racy with my call to fork(2)".
You still have to make sure that that fork-safety invariants are true. But the effort to do that is extremely different depending on language platform.
Rust/C/C++ don't cleanly fit into either of those two (already mushy/subjective) categorizations, though. Whether forking is feasible in a given Rust/C/C++ codebase depends on what the code does and requires a tricky set of judgement calls and at-a-distance knowledge going forward to make sure that the codebase doesn't become fork-unsafe in harmful ways.
One place you might see something like it is if an API takes ownership, but returns it on error; you see the error side carry the resource you gave it, so you could try again.
Fn(_: &mut T)
?What is different?
After Rust has raised the level of quality and expectations to such great level, async feels like 3 steps back with all those arguments "you are holding it wrong", footguns, and piles of hacks. And this sentiment is shared by many others. It's really disappointing to see how many resources are getting sunk into the flawed async model by both the language and the ecosystem developers.
>go build it then
I did build it and it's in the process of being adopted into a proprietary database (theoretically a prime use-case for async Rust). Sadly, because I don't have ways to change the language and the compiler, it has obvious limitations (and generally it can be called unsound, especially around thread locals). It works for our project only because we have a tightly controlled code base. In future I plan to create a custom "green-thread" fork of `std` to ease limitations a bit. Because of the limitations (and the proprietary nature of the project) it is unlikely to be published as an open source project.
Amusingly, during online discussions I've seen other unrelated people who done similar stuff.
Is this really better than what we have now? I don't think async is perfect, but I can see what tradeoffs they are currently making and how they plan to address most if not all of them. "General" unsoundness seems like a rather large downside.
> In future I plan to create a custom "green-thread" fork of `std` to ease limitations a bit
Can you go more in-depth into these limitations and which would be alleviated by having first class support for your approach in the compiler/std?
Depends on the metric you use. Memory-wise it's a bit less efficient (our tasks usually are quite big, so relative overhead is small in our case), runtime-wise it should be on par or slightly ahead. From the source code perspective, in my opinion, it's much better. We don't have the async/await noise everywhere and after development of the `std` fork we will get async in most dependencies as well for "free" (we still would need to inspect the code to see that they do not use blocking `libc` calls for example). I always found it amusing that people use "sync" `log`-based logging in their async projects, we will not have this problem. The approach also allows migration of tasks across cores even if you keep `Rc` across yield points. And of course we do not need to duplicate traits with their async counterparts and Drop implementations with async operations work properly out of the box.
>Can you go more in-depth into these limitations and which would be alleviated by having first class support for your approach in the compiler/std?
The most obvious example is thread locals. Right now we have to ensure that code does not wait on completion while having a thread local reference (we allow migration of tasks across workers/cores by default). We ban use of thread locals in our code and assume that dependencies are unable to yield into our executor. With forked `std` we can replace the `thread_local!` macro with a task-local implementation which would resolve this issue.
Another source of potential unsoundness is reuse of parent task stack for sub-task stacks in our implementation of `select!`/`join!` (we have separate variants which allocate full stacks for sub-tasks which are used for "fat" sub-tasks). Right now we have to provide stack size for sub-tasks manually and check that the value is correct using external tools (we use raw syscalls for interacting with io-uring and forbid external shared library calls inside sub-tasks). This could be resolved with the aforementioned special async ABI and tracking of maximum stack usage bound.
Finally, our implementation may not work out-of-box on Windows (I read that it has protections against messing with stack pointer on which we rely), but it's not a problem for us since we target only modern Linux.
UDP is a whole another kettle of fish, get's very complicated to go above 10gbit/s or so. This is a big part of why QUIC really struggles to scale well for fat pipes [1]. sendmmsg/recvmmsg + UDP GRO/GSO will probably get you to ~30gbit/s but beyond that is a real headache. The issue is that UDP is not stream focused so you're making a ton of little writes and the kernel networking stack as of today does a pretty bad job with these workloads.
FWIW even the fastest QUIC implementations cap out at <10gbit/s today [2].
Had a good fight writing a ~20gbit userspace UDP VPN recently. Ended up having to bypass the kernels networking stack using AF_XDP [3].
I'm available for hire btw, if you've got an interesting networking project feel free to reach out.
1. https://arxiv.org/abs/2310.09423
2. https://microsoft.github.io/msquic/
3. https://github.com/apoxy-dev/icx/blob/main/tunnel/tunnel.go
Another thing to consider: Google’s load balancers are all bespoke SDN and they almost certainly speak HTTP1/2 between the load balancers and the application servers. So Linux network stack constraints are probably not relevant for the YouTube frontend serving HTTP3 at all.
This is exactly what I meant when I wrote about the indirect influence from other languages. People may dress it up as much as they want, but it's clear that polling was the most important model at the time (outside of the Windows world) and a lot of design consideration was put into being compatible with it. The Rust async model literally uses the polling terminology in its most fundamental interfaces!
>this approach nevertheless forces allocation at almost every point of future composition
This is only true in the narrow world of modeling async execution with futures. Do you see heap allocations in Go on each equivalent of "future composition" (i.e. every function call)? No, you do not. With the stackfull models you allocate a full stack for your task and you model function calls as plain function calls without any future composition shenaniganry.
Yes, the stackless model is more efficient memory-wise and allows for some additional useful tricks (like sharing future stacks in `join!`). But the stackfull model is perfectly efficient for 95+% of use cases, fits better with the borrow/ownership model, does not result in the `.await` noise, does not lead to the horrible ecosystem split (including split between different executors), and does not need the language-breaking hacks like `Pin` (see the `noalias` exception made for it). And I believe it's possible to close the memory efficiency gap between the models with certain compiler improvements (tracking maximum stack usage bound for functions and introducing a separate async ABI with two separate stacks).
>The existence of a usable io_uring in 2016 wouldn't have changed the fundamental calculus.
IIRC the first usable versions of io-uring very released approximately during the time when the Rust async was undergoing stabilization. I am really confident that if the async system was designed today we would've had a totally different model. Importance of completion-based models has only grown since then not only because of the sane async file IO, but also because of Spectre and Meltdown.
The existence of advantages doesn't change anything here. The problems is that the disadvantages made this approach a non-starter, despite a lot of effort to make it work. Tradeoffs exist in language design, and the approaches were judged accordingly. What works for Go doesn't necessarily work for Rust, because they target different domains.
> I am really confident that if the async system was designed today we would've had a totally different model
No, without solving the original problems, the outcome would be the same. The Rust devs at the time were well aware of io_uring.
Async is really about the surface syntax and ergonomics, not the implementation.
Goroutines are an unusual case, in that they don't have cooperative concurrency--they're pre-emptive--but the Go runtime does perform I/O using concurrent multiplexers under the hood.
So goroutines are kind of both: computation execution and code semantics look like pthreads, but I/O operations look like NodeJS on the backend.
Now, I'm not sure what "async runtime" means in the GP. If they're referring to I/O multiplexers, then they should say that. If they're referring to something else, then I'm not familiar with other uses of that term that would accurately apply to Golang.
Async and threads are a lot closer than most people think. An OS is mainly a queue for swapping between async operations, and a collection of abstracted services that the async operations can request, like network or disk i/o.
https://journal.stuffwithstuff.com/2015/02/01/what-color-is-...
Like, do you need async runtimes to do epoll async in Rust? No. Ok, so that excludes many definitions. Do you need coroutines in C++ to do aio for reading and writing? No.
So like I said, what do they mean by "async"? The blog post refers to a web server that does "async" in Rust without any async runtime, and without the `async` keyword.
In other words, that parent commenter is what's called "not even wrong".
When passing a mutable reference, the lifetime of the object is largely decided by "foo" (with some caveats).
Now, let's say that "foo" instead calls "fn bar(_: T) -> T".
When passing the object itself, the lifetime is largely decided/decide-able by "bar".
In my case, I have code that essentially looks like this:
struct Parser {
state: ParserState
}
struct Subparser {
state: ParserState
}
impl Parser {
pub fn parse_something(&mut self) -> Subparser {
Subparse { state: self.state } // NOTE: doesn't work
}
}
impl Drop for Subparser {
fn drop(&mut self) {
parser.state = self.state; // NOTE: really doesn't work
}
}
It's the give-back portion of the borrow-to-give-back pattern that ends up being gnarly. I'm actually somewhat disappointed that the Rust ecosystem has in general given up on trying to build up safe pointer abstractions in the ecosystem, like doing use tracking for a pointed-to object. FWIW, a rough C++ implementation of what I would like to do is this:
template <typename T> class HotPotato {
T *data;
HotPotato<T> *borrowed_from = nullptr, *given_to = nullptr;
public:
T *get_data() {
// If we've given the data out, we can't use it at the moment.
return given_to ? nullptr : data;
}
std::unique_ptr<HotPotato<T>> borrow() {
assert(given_to == nullptr);
auto *new_holder = new HotPotato();
new_holder->data = data;
new_holder->borrowed_from = this;
given_to = new_holder;
}
~HotPotato() {
if (given_to) {
given_to->borrowed_from = borrowed_from;
}
if (borrowed_from) {
borrowed_from->given_to = given_to;
} else {
delete data;
}
}
};It's an equivalent of Rc<Cell<(Option<Box<T>>, Option<Box<T>>)>>, but with the Rc replaced by a custom shared type that avoids keeping refcount by having max 2 owners.
You're going to need UnsafeCell to implement the exact solution, which needs a few lines of code that is as safe as the C++ version.
1. global my_global_var: GlobalType = …
2. heap my_heap_var: HeapType = …
3. stack my_stack_var: StackType = …
So by having the location of allocation in the type itself, we no longer have to do boxing mental gymnastics
The compiler can perform all sorts of optimizations, and on most modern CPU architectures, it is better to shove as many values into registers as possible. If you don't take the address of a variable, you don't run out of registers, and you don't call other, non-inlined functions, then let-bindings (and function arguments/return values) need not ever spill onto the stack.
In some cases, values don't even get into registers. Small numeric constants (literals, consts, immutable lets) can simply be inlined as immediate values in the assembly/machine code. In the other direction, large constant arrays and strings don't spill onto the stack but rather the constant pool.
To be honest, I was thinking more in terms of cognitive overload i.e. is all that Box boilerplate even needed if we were to treat all `heap my_heap = …” as box underneath? In other words, couldn’t we elide all that away:
let foo = Box::new(MyFoo::default ());
heap foo = MyFoo::default();
This is why you have to use various hacks when using io-uring based executors with Rust async (like using polling mode or ring-owned buffers and additional data copies). It could be "resolved" on the language level with an additional pile of hacks which would implement async Drop, but, in my opinion, it would only further hurt consistency of the language.
>He even calls out how naïve completion (callbacks) leads to more allocation on future composition and points to where green threads were abandoned.
I already addressed it in the other comment.
I wouldn't call async drop a pile of hacks, it's actually something that would be useful in this context.
And that said there's an easy fix: don't use the pointers supplied by the future!
Nope. The problem does not exist in the stackfull model by the virtue of user being unable (in safe code) to drop stack of a stackfull task similarly to how you can not drop stack of a thread. If you want to cancel a stackfull task, you have to send a cancellation signal to it and wait for its completion (i.e. cancellation is fully cooperative). And you can not fundamentally panic while waiting for a completion event, the task code is "frozen" until the signal is received.
>it's actually something that would be useful in this context.
Yes, it's useful to patch a bunch of holes introduced by the Rust async model and only for that. And this is why I call it a bunch of hacks, especially considering the fundamental issues which prevent implementation of async Drop. A properly designed system would've properly worked with the classic Drop.
>And that said there's an easy fix: don't use the pointers supplied by the future!
It's always amusing when Rust async advocates say that. Let met translate: don't use `let mut buf = [0u8; 16]; socket.read_all(&mut buf).await?;`. If you can't see why such arguments are bonkers, we don't have anything left to talk about.
I just had to double-check as this sounded strange to me, and no that's not true.
The most efficient design is to do it that way, yes, but there are no guarantees of that sort. If one wants to build a less efficient executor, it's perfectly permissible to just poll futures on a tight loop without involving the Waker at all.
Uhm all of that is just sugar on top of stable feature. None of these features or lack off prevent portability.
Full portability isn't possible specifically due to how Waker works (i.e. is implementation specific). That allows async to work with different style of asyncs. Reason why io_uring is hard in rust is because of io_uring way of dealing with memory.
Rust is in a strange place because they're a systems language directly competing with C++. Async, in general, doesn't vibe with that but green threads definitely don't.
If you're gonna do green threads you might as well throw in a GC too and get a whole runtime. And now you're writing Go.
I think they made the wrong bet, personally. Having worked in enough languages that have function coloring problems I would avoid it as a language design as a line in the sand item, regardless of tradeoffs
I don't think I nor most systems programmers would have chosen rust if it required green threads instead of stackless coroutines for async. If you work on embedded or low level environments like kernels and whatnot, you need something that falls back to callbacks for async. I'm sure folks who work on servers would have been fine with green threads but they were not the target audience for rust. Being upset because you fall outside the target demographic of a particular language doesn't mean they made the wrong choice. It just means you should look for something else.
For me the mistake that Rust made was that it tried too hard to behave like C/C++ with its single execution stack.
Ada uses two stacks allowing a callee to return a stack-allocated arrays to the caller. Not only it allows to avoid dynamic allocations in many cases where C++ allocates memory, but it also reduces the need for pointers making the code safer even without the borrow checker.
If instead of async Rust spent efforts on implementing something like that or even allow for explicit stack control from safe code so green threads or co-routines could be implemented as a library it could be more compatible with io_uring world.
self.buffer = io_read(self.buffer)?
io_read(&mut self.buffer)?
Or well you can, using unsafe, Arc and Mutex - but at that point the safety guarantees aren’t much better than what I get in well designed C++.
Don’t get me wrong, I still much prefer Rust, but I wish async and references worked together better.
Source: I recently wrote a high-throughput RPC library in Rust (saturating > 100 Gbit NICs)
You could do this manually by threading a pointer to a separately-allocated stack (could be on the heap or perhaps just a static allocation) as an extra function parameter. It's just a very simple case of arena allocation, with similar advantages and disadvantages. (For example, the caller must ensure that enough space is available on the dynamic-data stack for anything that the callee might want to push onto it.) In general it's just not really worth it, because it turns out that dynamically-sized data that one would not want to simply place on the heap is rare anyway.
Indeed, one thing I’ve always wondered is if you can submit a read request for a page aligned buffer and have the kernel arrange for data to be written directly into that without any additional copies. That’s probably not possible since there’s routing happening in the kernel and it accumulates everything into sk_buffs.
But maybe it could arrange for the framing part of the packet and the data to be decoupled so that it can just give you a mapping into the data region (maybe instead of you even providing a buffer, it gives you back an address mapped into your space). Not sure if that TLB update might be more expensive than a single copy.
Parity with synchronous programming is an explicit goal of Rust async declared many times (e.g. see here https://github.com/rust-lang/rust-project-goals/issues/105). I agree with your rant about the illusion of synchronicity, but it does not matter. The synchronous abstraction is immensely useful in practice and less leaky it is, the better.
To me it's pretty clear that parity in the issue referenced refers to equivalence parity - that is you can accomplish the tasks in some way, not that it's a drop-in replacement. I haven't seen anywhere suggested that async lets you write synchronous code without any changes, nor that integrating completion-style APIs with asynchronous will yield code that looks like synchronous. For one, completion-style APIs are for performance and performance APIs are rarely structured for simplicity but to avoid implicit costs hidden in common leaky (but simpler) abstractions. For another, completion-style APIs in synchronous programming ALSO looks different from epoll/select-like APIs, so I really don't understand the argument you're trying to make.
EDIT:
> You have an inevitable overhead of managing the owned buffer when compared against simply passing mutable borrow to an already existing buffer. Imagine if `io::Read` APIs were constructed as `fn read(&mut self, buf: Vec<u8>) -> io::Resul<Vec<u8>>`.
I'm imaging and I don't see a huge problem in terms of the overhead this implies. And you'd probably not necessarily take in a Vec directly but some I/O-specific type since such an API would be for performance.
It makes sense to ask the ring wrapper for memory that you can emplace your payload into before submitting the IO if you want to use zero-copy.
It doesn't seem bonkers to me. I know you already know these details, but spelling it out: If I'm using select/poll/epoll in C to do non-blocking reads of a socket, then yes I can use any old stack buffer to receive the bytes, because those are readiness APIs that only write through my pointer "now or never". But if I'm using IOCP/io_uring, I have to be careful not to use a stack buffer that doesn't outlive the whole IO loop, because those are completion APIs that write through my pointer "later". This isn't just a question of the borrow checker being smart enough to analyze our code; it's a genuine difference in what correct code needs to do in these two different settings. So if async Rust forces us to use heap allocated (or long-lived in some other way) buffers to do IOCP/io_uring reads, is that a failure of the async model, or is that just the nature of systems programming?
This, 100%. Being really generous, it can be called a leaky model which is poorly compatible with completion-based APIs.
As someone else mentioned, what you really want is to ask io_uring to allocate the pages itself so that for reads it gives you pages that were allocated by the kernel to be filled directly by HW and then mapped into your userspace process without any copying by the kernel or any other SW layer involved.
If you're not doing things better than threads then why don't you just use threads?
> And you can not fundamentally panic while waiting for a completion event, the task code is "frozen" until the signal is received.
So you only allow join/select at the task level? Sounds awful!
> Let met translate: don't use `let mut buf = [0u8; 16]; socket.read_all(&mut buf).await?;
Yes, exactly. It's more like `let buf = socket.read(16);`
Because green threads are more efficient than the classical threads. You have less context switching, more control over concurrency (e.g. you can have application-level pseudo critical section and tools like `join!`/`select!`), and with io-uring you have a much smaller number of syscalls.
In other words, memory footprint would be similar to the classical threads, but runtime performance can be much higher.
>So you only allow join/select at the task level? Sounds awful!
What is the difference with join/select at the future level?
Yes, with the most straightforward implementation you have to allocate full stack for each sub-task (somewhat equivalent to boxing sub-futures). But it's theoretically possible to use the parent task stack for sub-task stacks with the aforementioned compiler improvements.
Another difference is that instead of just dropping the future state on the floor you have to explicitly send a cancellation signal (e.g. based on `IORING_OP_ASYNC_CANCEL`) and wait for the sub-task to finish. Performance-wise it should have minimal difference when compared against the hypothetical async Drop.
>Yes, exactly.
Ok, I have nothing more to add then.
Okay, but what about writes? If I have a memory region that I want io_uring to write, it's a major pain in the ass to manage the lifetime of objects in that region in a safe way. My choices are basically: manually manage the lifetime and only allow it to be dropped when I see a completion show up (this is what most everything does now, and it's a) hard to get right and b) limited in many ways, e.g. it's heap-only), or permanently leak that memory as unusable.
Using the feature to let io_uring handle buffers for you limits you to the mem lock limit of a process, which is 8MB on a typical debian install (more on others) And that's a hard limit unless you got root access to said machine.
The memory frequently needs to be mlocked memory anyway, so a general purpose allocator doesn't work.
[1] https://docs.rs/glommio/latest/glommio/fn.allocate_dma_buffe...