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Mental experiments with io_uring

Recently, a new Linux kernel interface, called io_uring, appeared. I have been looking into it a little bit and I can’t help but wondering about it. Unfortunately, I’ve had only enough time to keep thinking and reading about it. Nevertheless, I’ve decided to share what I’ve been thinking about so far in case someone wants to write some actual code and experiment. Basically, I have an idea for a crate and I’d love someone else to write it 😇.

Therefore, as a little disclaimer, all things included here can be inaccurate or wrong. I believe the general high-level picture is correct, but as I haven’t actually used the APIs, all kinds of surprises might appear. The code examples are not tried either and are just illustrative.

A little about the kernel API

There are some APIs for asynchronous network IO in Linux. The older and more portable ones are poll and select, the newer one being epoll. These allow stuffing the kernel with large amount of sockets and waiting until some of them are ready to read or write data. Once the kernel identifies a subset of them as being ready, the application performs the reading and writing operations.

But these don’t really work for files. There’s the AIO subsystem, but it is generally considered awkward to use and with huge amount of drawbacks and nobody really uses it at all.

However, there’s a lot of applications that could benefit from having asynchronous and cheap file access. The cheap part is also important. On one side, syscalls (eg. calls from userspace into the kernel) got more expensive with spectre workarounds. On the other hand SSDs and NVMes are getting much faster and are capable to work more in parallel (a rotation disk could do only one read at a time, SSD can read simultaneously in each of its chips). While it didn’t matter that much for rotation disks (because waiting for the disk itself took so long nobody cared about the syscall cost) and network IO is generally quite expensive too, the syscalls form significant part of modern disk access.

The io_uring tries to solve these problems. While it can be used for asynchronous network IO, the main purpose is the disk IO.

The interface is composed of two ringbuffers or queues, one for requests going from program to kernel, the other for the kernel returning results. The queues live in memory shared between the kernel and the application, so reading and writing these queues don’t need any syscalls, only some thread synchronization primitives. There’s one syscall that is used both for notifying the kernel that there are at least n new requests in the queue and that the application would like to wait for at least m responses to be ready before continuing. This allows one to submit many requests and receive many responses per one syscall, amortizing its cost. Under some circumstances one can avoid even that one syscall.

Comparing to other kernel interfaces, it is quite well documented. Which still means somewhat worse documentation that most of Rust crates, but there’s more documentation that just the kernel sources (I’m looking at you, netlink…). There’s even a high-level document about it.

What exists already

Rust and rustaceans being what they are, if you say „performance“ you can expect few crates to pop up. Indeed, I’ve found some and this one looks the most user friendly.

However this is still a bit low-level. If we let aside that the kernel API now allows much more than just reading and writing, using this manually in normal code will turn out tiresome. It’s a useful wrapper of OS API in a similar way as mio is a wrapper around epoll (or something else on other platforms).

But similarly to how tokio builds asynchronous network primitives on top of mio, we would like to be able to use asynchronous files through this new API. Let’s look where the challenge lies and let’s also look if we can abuse the io_uring for something besides files.

Design goals

First, we want good performance. The design of the kernel API goes to great lengths to eliminate costs as much as possible. If we are going to play with it in Rust, it would be nice to know how far we can stretch it on the userspace side too. So, we’ll try to avoid unnecessary copies, allocations, context switches…

Second, the interface should be usable without any unsafe. We may need to use some of it internally, but people writing databases or fulltext search engines or whatever else that needs really fast disk IO should not have to worry about that kind of stuff. What they do is already challenging enough without piling more onto them.

And third, the API should be comfortable to use if at all possible.

Things like being sound (not being able to cause an undefined behaviour without using unsafe) go without saying.

Ownership of buffers

We are coming to the first challenge out there. We want to be able to do something like this:

async fn get_cache(path: &Path) -> Result<Vec<u8>, Error> {
    // This line can probably block, but let's ignore it for now
    let file = File::open(path)?;

    let mut buff = vec![0; 1024];
    let amount = ioring_read(&file, &mut buff).await?;

This, however, is problematic. When requesting the read, we pass the buffer to the kernel. It’ll do the reading directly into the buffer and will tell us when done. But there’s no way to take the buffer away from the kernel sooner than that. For one, the io_uring doesn’t seem to have a way to cancel an ongoing operation ‒ disk access is fast enough not to need timeouts and such. But even if there was, it would probably work by sending another request „please cancel that other request“ through the queue and having to wait for confirmation to get out of the other queue.

Edit: As pointed out by glaebhoerl in the comments, io_uring now has a support for cancellation. But the cancellation works as I expected, by sending the requests through the queues. Therefore this problem is not solved by it.

Why is this a problem? Because futures in Rust can be cancelled by dropping at any time. And even if we placed the waiting into the destructor, we can’t really count on the destructor being run. After all, it’s always possible to forget the future:

// What's the exact syntax for a select or timeout right now?
match ioring_read(&file, &mut buff).timeout(Duration::from_secs(0)).await {
    Ok((amount, _timeout)) => buff.truncate(amount),
    Err(read_future) => mem::forget(read_future),

// The `&mut` died with the future without descructor, so we can now:
println!("{:?}", buff);

Now, if the read times out, we don’t run the destructor. The kernel still thinks we want it to put data into buff and at some point it’s going to do so. But we print the content of it at the (potentially) same time. I don’t think anyone explicitly said what happens in such case, because the kernel is not our (Rust) thread and the Rust threading/aliasing/data-race model may not be directly applicable. But let’s assume its some kind of undefined behaviour that we definitely don’t want.

Destructors won’t help. Pinning won’t help (pinning doesn’t stop us from reading from it).

So far I think there are three options:

I’m slightly inclined to the last option. It has another benefit. The io_uring has a mode in which it prepares some buffers beforehand and they work a little bit faster. Using a special type would mean we could allocate them as part of these prepared buffers.

Reading the completion queue

We’ve created our future that represents the request to the kernel to read some data. We may put the request to the kernel at many different occasions ‒ at least on creation of the future (that’s not how Rust futures usually work, but it could be done) or on the first poll of the future.

But eventually someone needs to call „I’ve submitted n tasks and want at least m tasks done from you“ syscall, which might block, and then handle the done tasks somehow.

There are two obvious solutions.

Is there another option? I think there is. Tokio is quite flexible (that’s why I use tokio as example here, not eg. async-std, because the latter won’t let us do the kind of abuse we want here). Each thread participating in the runtime has three ingredients (no matter if it’s the current_thread or the work-stealing runtime or even some completely different one):

Whenever a layer doesn’t have anything to do right now, it passes control to the layer below it. So, if the executor doesn’t have any ready futures, it passes the control to the timer. It checks the clock and its data structure and maybe wakes some futures, in which case it would return the control back to the executor to run them. If there were none to be woken, it would compute for how long there’ll be none such and pass the control to the reactor. The reactor would extract notifications from the kernel (or block on getting them) and wake the relevant futures.

The trick here is, this passing of control is abstracted using a Park trait. And on top of that, we can assemble the runtime ourselves, doing any necessary tweaks to it. There’s a documentation how to do it (for the 0.1 tokio, but I assume it’ll assume it’s still possible with the 0.2 branch, probably with some minor differences). This allows us to insert additional layer into the equation.

We can put the io_ring poller between the timer and reactor. The reactor implements AsRawFd and, unless my guess is very wrong, it would become readable if the epoll inside has some events. The io_uring can be used to watch readiness of a file descriptor, so we can plug it in. When the completion queue spits out finished reads or writes, the corresponding future can be woken up. If the epoll file descriptor is returned, we can do one turn of the reactor.

We could probably connect it the other way around ‒ the completion queue can have a companion file descriptor that’s readable if there are finished tasks to pick up. Then we could simply create some kind of driving future that processes all the completed tasks when woken up. But my gut feeling is that the disk IO is going to be more sensitive to latency and performance and therefore should be the one closer to the top.

Using it for network IO

The io_uring was designed mainly for disk IO because that was the missing functionality. It was already possible to effectively handle large amounts of network IO operations so the gains for using the new interface for networked IO isn’t much.

But there probably can be some. But first, we probably don’t want to register reads and writes directly as with the files. Unlike files, network sockets might take really long time to provide or send data or they may not do it at all. So such task would be sitting in the kernel a very long time and a lot of them would be submitted. I didn’t find what the limits for how many tasks can be submitted is, but there was a hint about problems when the completion queue fills up ‒ which can happen if there are many such tasks.

We can, however, use the queues to replace epoll. That could save some syscalls ‒ for example, we could register multiple file descriptors using just one syscall. It would also piggy-back on some disk IO.

Furthermore, when epoll turns once, it may spit out multiple sockets ready to perform some operations. Currently, each future performs that operation on its own, each performing another syscall. All these follow-up syscalls could be batched and submitted at once through the queue.

So, all in all, this could help reduce number of syscalls and may improve performance a little bit. This would need to land in tokio itself, though (I think I’ve seen a pull request for something of it somewhere, but now I can’t find it).

What’s next?

I don’t know if any of these ideas are any good and I don’t have the time to pursue them right now. But they sound like something worth at least trying out. So, if anyone wants to have a go at it, here I give all the ideas for free. I’ll happily help brainstorming further ideas and provide advice, I just don’t feel like investing time into the actual coding.