Efficient IO in Linux with io_uring [pdf] (2019)
kernel.dk
kernel.dk
Actually, io_uring has received around 500 commits just in 2022. Here's a list of interesting feature additions(this year),
- https://www.phoronix.com/news/Linux-LPC2022-io_uring_spawn
- https://www.phoronix.com/news/Linux-520-XFS-uring-Async-Buff
- https://www.phoronix.com/news/Linux-5.20-IO_uring-ZC-Send
- https://www.phoronix.com/news/Linux-5.19-IO_uring
io_uring like API was also adopted by Windows recently. Lots of fun.
I’ve never managed to do a comparison of io_uring vs IOCP but I guess there was some benefit here, I left that job before io_uring was mature.
Would anyone be willing to share a comparison of the two systems?
The Windows IORing is only storage today, but hopefully becomes a generic system for making batched, async system calls just like on Linux.
Edit: you can read about it by googling for the original RIO presentation, but the gist is that at very high packet rates the completion signaling and locking/unlocking buffers for I/O cause a lot of overhead and RIO mitigates that by preregistering buffers
Whereas NT was a fresh new design, by seasoned operating systems designers and implementers, who had seen the shortcomings of the Unix model (and others) and not only knew what to do differently to improve on these, but actually wanted to and were permitted to as well.
The logging system was implemented in a module which was inserted into the kernel and then used the calling thread to run a service. The module provided a device and some ioctls. Processes used the ioctls to attach circular buffers to the device, which was mapped into kernel space using get_user_pages.
Processes would just place messages into their circular buffers and update an index variable in the buffer header. The kernel would automatically pick up the message, without any system call. There was a wakeup ioctl to poke the kernel thread, which was used upon hitting a high water mark (buffer getting near full). This is the basic intuition behind io_uring.
The kernel thread collected messages from multiple buffers and sent them into several destination (files and sockets).
I do not have most of this code, but some of it survived, including a kernel mutex and condition variable library featuring a function that lets you give up a mutex to wait on a condition variable, while also polling any mixture of kernel file and socket handles, with a timeout. This function at the core of the kernel thread's loop.
The nice thing was that when processes crashed, their buffer would not go away immediately. Of course their own address space would be gone, but the kernel's mapping of the shared buffer mapping would gracefully persist, until the thread emptied the buffer; everything put into the buffer before the crash was safe. Empty buffers belonging to processes that had died would then be cleaned away.
I had a utility program that would list the buffers and the PIDs of their processes, and provide stats, like outstanding bytes, and is that process still alive.
(The one inefficiency in logging was that log messages need time stamps. Depending on where you get a time stamp from, that requires a trip to the kernel. I can't remember what I did about that.)
A bit of a difficulty in the whole approach is that I wasn't getting a linear mapping of the user pages in the kernel. So I wrote the grotty C code (kernel side) to pull the messages correctly from a scrambled buffer whose pages are out of order, without making an extra copy.
To be honest, ordinary "naive" programming methods are good enough to run a sizable single node WebSocket server. I'd be curious how much performance you can get out of a single server or, perhaps more broadly useful, a single core in a single Linux VPS, using different languages and relatively esoteric techniques like this.
source - I helped create SPDK.
Nor is io_uring the first or only asynchronous I/O API available to Linux userspace. It's just the best.
Did you implement a write barrier on this to ensure the compiler or CPU doesn’t run these two writes out of order?
The hardware this was running on supported cache-coherent NUMA, but we didn't use it in that mode; the blades that had multiple nodes ran multiple Linux instances that didn't share memory. Reordering effects at the hardware level weren't observed in the separate mode; if one core wrote to a location A and then B another core would not see the B update before A. Under ccNUMA, had we used it, I believe that would have been an issue.
Compiler reordering is always a threat, so you need at least that __volatile__ __asm__(": : memory"). In the user space infrastructure of that project, I made a library of atomic operations; there must have been barrier macros in there; I can't imagine providing atomic primitives without barriers.
> To find the index of an event, the application must mask the current tail index with the size mask of the ring. This commonly looks something like the below:
unsigned head;
head = cqring→head;
read_barrier();
if (head != cqring→tail) {
struct io_uring_cqe *cqe;
unsigned index;
index = head & (cqring→mask);
cqe = &cqring→cqes[index];
/* process completed cqe here */
...
/* we've now consumed this entry */
head++;
}
cqring→head = head;
write_barrier();
If you plan on using it, or just want to learn more about it, check this out:
https://github.com/libuv/libuv/issues/1947#issuecomment-4852...