Monday, February 20, 2023

Writing a C library in Rust

I started working on libblkio in 2020 with the goal of creating a high-performance block I/O library. The internals are written in Rust while the library exposes a public C API for easy integration into existing applications. Most languages have a way to call C APIs, often called a Foreign Function Interface (FFI). It's the most universal way to call into code written in different languages within the same program. The choice of building a C API was a deliberate one in order to make it easy to create bindings in many programming languages. However, writing a library in Rust that exposes a C API is relatively rare (librsvg is the main example I can think of), so I wanted to share what I learnt from this project.

Calling Rust code from C

Rust has good support for making functions callable from C. The documentation on calling Rust code from C covers the basics. Here is the Rust implementation of void blkioq_set_completion_fd_enabled(struct blkioq *q, bool enable) from libblkio:

#[no_mangle]
pub extern "C" fn blkioq_set_completion_fd_enabled(q: &mut Blkioq, enable: bool) {
    q.set_completion_fd_enabled(enable);
}

A C program just needs a function prototype for blkioq_set_completion_fd_enabled() and can call it directly like a C function.

What's really nice is that most primitive Rust types can be passed between languages without special conversion code in Rust. That means the function can accept arguments and return values that map naturally from Rust to C. In the code snippet above you can see that the Rust bool argument can be used without explicit conversion.

C pointers are converted to Rust pointers or references automatically by the compiler. If you want them to be nullable, just wrap them in Rust Option and the C NULL value becomes Rust None while a non-NULL pointer becomes Some. This makes it a breeze to pass data between Rust and C. In the example above, the Rust &mut Blkioq argument is a C struct blkioq *.

Rust structs also map to C nicely when they are declared with repr(C). The Rust compiler lays out the struct in memory so that its representation is compatible with the equivalent C struct.

Limitations of Rust FFI

It's not all roses though. There are fundamental differences between Rust and C that make FFI challenging. Not all language constructs are supported by FFI and some that are require manual work.

Rust generics and dynamically sized types (DST) cannot be used in extern "C" function signatures. Generics require that Rust compiler to generate code, which does not make sense in a C API because there is no Rust compiler involved. DSTs have no mapping to C and so they need to be wrapped in something that can be expressed in C, like a struct. DSTs include trait objects, so you cannot directly pass trait objects across the C/Rust language boundary.

Two extremes in library design

The limitations of FFI raise the question of how to design the library. The first extreme is to use the lowest common denominator language features supported by FFI. In the worst case this means writing C in Rust with frequent use of unsafe (because pointers and unpacked DSTs are passed around). This is obviously a bad approach because it foregoes the safety and expressiveness benefits of Rust. I think few human programmers would follow this approach although code generators or translators might output Rust code of this sort.

The other extreme is to forget about C and focus on writing an idiomatic Rust crate and then build a C API afterwards. Although this sounds nice, it's not entirely a good idea either because of the FFI limitations I mentioned. The Rust crate might be impossible to express as a C API and require significant glue code and possibly performance sacrifices if it values cannot be passed across language boundaries efficiently.

Lessons learnt

When I started libblkio I thought primarily in terms of the C API. Although the FFI code was kept isolated and the rest of the codebase was written in acceptably nice Rust, the main mistake was that I didn't think of what the native Rust crate API should look like. Only thinking of the C API meant that some of the key design decisions were suboptimal for a native Rust crate. Later on, when we began experimenting with a native Rust crate, it became clear where assumptions from the unsafe C API had crept in. It is hard to change them now, although Alberto Faria has done great work in revamping the codebase for a natural Rust API.

I erred too much on the side of the C API. In the future I would try to stay closer to the middle or slightly towards the native Rust API (but not to the extreme). That approach is most likely to end up with code that presents an efficient C API while still implementing it in idiomatic Rust. Overall, implementing a C library API in Rust was a success. I would continue to do this instead of writing new libraries in C because Rust's language features are more attractive than C's.

Video and slides available for "vhost-user-blk: a fast userspace block I/O interface"

At FOSDEM '23 I gave a talk about vhost-user-blk and its use as a userspace block I/O interface. The video and slides are now available here. Enjoy!

Wednesday, January 25, 2023

Speaking at FOSDEM '23 about "vhost-user-blk: A fast userspace block I/O interface"

vhost-user-blk has connected hypervisors to software-defined storage since around 2017, but it was mainly seen as virtualization technology. Did you know that vhost-user-blk is not specific to virtual machines? I think it's time to use it more generally as a userspace block I/O interface because it's fast, unprivileged, and avoids exposing kernel attack surfaces.

My LWN.net article about Accessing QEMU storage features without a VM already hinted at this, but now it's time to focus on what vhost-user-blk is and why it's easy to integrate into your applications. libblkio is a simple and familiar block I/O API with vhost-user-blk support. You can connect to existing SPDK-based software-defined storage applications, qemu-storage-daemon, and other vhost-user-blk back-ends.

Come see my FOSDEM '23 talk about vhost-user-blk as a fast userspace block I/O interface live on Saturday Feb 4 2023, 11:15 CET. It will be streamed on the FOSDEM website and recordings will be available later. Slides are available here.

Friday, November 18, 2022

LWN article on "Accessing QEMU storage features without a VM"

At KVM Forum 2022 Kevin Wolf and Stefano Garzarella gave a talk on qemu-storage-daemon, a way to get QEMU's storage functionality without running a VM. It's great for accessing disk images, basically taking the older qemu-nbd to the next level. The cool thing is this makes QEMU's software-defined storage functionality - block devices with snapshots, incremental backup, image file formats, etc - available to other programs. Backup and forensics tools as well as other types of programs can take advantage of qemu-storage-daemon.

Here is the full article about Accessing QEMU storage features without a VM. Enjoy!

Thursday, November 10, 2022

Using qemu-img to access vhost-user-blk storage

vhost-user-blk is a high-performance storage protocol that connects virtual machines to software-defined storage like SPDK or qemu-storage-daemon. Until now, tool support for vhost-user-blk has been lacking. Accessing vhost-user-blk devices involved running a virtual machine, which requires more setup than one would like.

QEMU 7.2 adds vhost-user-blk support to the qemu-img tool. This is possible thanks to libblkio, a library that other programs besides QEMU can use too.

Check for vhost-user-blk support in your installed qemu-img version like this (if it says 0 then you need to update qemu-img or compile it from source with libblkio enabled):

$ qemu-img --help | grep virtio-blk-vhost-user | wc -l
1

You can copy a raw disk image file into a vhost-user-blk device like this:

$ qemu-img convert \
      --target-image-opts \
      -n \
      test.img \
      driver=virtio-blk-vhost-user,path=/tmp/vhost-user-blk.sock,cache.direct=on

The contents of the vhost-user-blk device can be saved as a qcow2 image file like this:

$ qemu-img convert \
      --image-opts \
      -O qcow2 \
      driver=virtio-blk-vhost-user,path=/tmp/vhost-user-blk.sock,cache.direct=on out.qcow2

The size of the virtual disk can be read:

$ qemu-img info \
      --image-opts \
      driver=virtio-blk-vhost-user,path=/tmp/vhost-user-blk.sock,cache.direct=on
image: json:{"driver": "virtio-blk-vhost-user"}
file format: virtio-blk-vhost-user
virtual size: 4 GiB (4294967296 bytes)
disk size: unavailable

Other qemu-img sub-commands like bench and dd are also available for quickly accessing the vhost-user-blk device without running a virtual machine:

$ qemu-img bench \
      --image-opts \
      driver=virtio-blk-vhost-user,path=/tmp/vhost-user-blk.sock,cache.direct=on
Sending 75000 read requests, 4096 bytes each, 64 in parallel (starting at offset 0, step size 4096)
Run completed in 1.443 seconds.

Being able to access vhost-user-blk devices from qemu-img makes vhost-user-blk a little easier to work with.

Thursday, June 30, 2022

Comparing VIRTIO, NVMe, and io_uring queue designs

Queues and their implementation using shared memory ring buffers are a standard tool for communicating with I/O devices and between CPUs. Although ring buffers are widely used, there is no standard memory layout and it's interesting to compare the differences between designs. When defining libblkio's APIs, I surveyed the ring buffer designs in VIRTIO, NVMe, and io_uring. This article examines some of the differences between the ring buffers and queue semantics in VIRTIO, NVMe, and io_uring.

Ring buffer basics

A ring buffer is a circular array where new elements are written or produced on one side and read or consumed on the other side. Often terms such as head and tail or reader and writer are used to describe the array indices at which the next element is accessed. When the end of the array is reached, one moves back to the start of the array. The empty and full conditions are special states that must be checked to avoid underflow and overflow.

VIRTIO, NVMe, and io_uring all use single producer, single consumer shared memory ring buffers. This allows a CPU and an I/O device or two CPUs to communicate across a region of memory to which both sides have access.

Embedding data in descriptors

At a minimum a ring buffer element, or descriptor, contains the memory address and size of a data buffer:

OffsetTypeName
0x0u64buf
0x8u64len

In a storage device the data buffer contains a request structure with information about the I/O request (logical block address, number of sectors, etc). In order to process a request, the device first loads the descriptor and then loads the request structure described by the descriptor. Performing two loads is sub-optimal and it would be faster to fetch the request structure in a single load.

Embedding the data buffer in the descriptor is a technique that reduces the number of loads. The descriptor layout looks like this:

OffsetTypeName
0x0u64remainder_buf
0x8u64remainder_len
0x10...request structure

The descriptor is extended to make room for the data. If the size of the data varies and is sometimes too large for a descriptor, then the remainder is put into an external buffer. The common case will only require a single load but larger variable-sized buffers can still be handled with 2 loads as before.

VIRTIO does not embed data in descriptors due to its layered design. The data buffers are defined by the device type (net, blk, etc) and virtqueue descriptors are one layer below device types. They have no knowledge of the data buffer layout and therefore cannot embed data.

NVMe embeds the request structure into the Submission Queue Entry. The Command Dword 10, 11, 12, 13, 14, and 15 fields contain the request data and their meaning depends on the Opcode (request type). I/O buffers are still external and described by Physical Region Pages (PRPs) or Scatter Gather Lists (SGLs).

io_uring's struct io_uring_sqe embeds the request structure. Only I/O buffer(s) need to be external as their size varies, would be too large for the ring buffer, and typically zero-copy is desired due to the size of the data.

It seems that VIRTIO could learn from NVMe and io_uring. Instead of having small 16-byte descriptors, it could embed part of the data buffer into the descriptor so that devices need to perform fewer loads during request processing. The 12-byte struct virtio_net_hdr and 16-byte struct virtio_blk_req request headers would fit into a new 32-byte descriptor layout. I have not prototyped and benchmarked this optimization, so I don't know how effective it is.

Descriptor chaining vs external descriptors

I/O requests often include variable size I/O buffers that require scatter-gather lists similar to POSIX struct iovec arrays. Long arrays don't fit into a descriptor so descriptors have fields that point to an external array of descriptors.

Another technique for scatter-gather lists is to chain descriptors together within the ring buffer instead of relying on memory external to the ring buffer. When descriptor chaining is used, I/O requests that don't fit into a single descriptor can occupy multiple descriptors.

Advantages of chaining are better cache locality when a sequence of descriptors is used and no need to allocate separate per-request external descriptor memory.

A consequence of descriptor chaining is that the maximum queue size, or queue depth, becomes variable. It is not possible to guarantee space for specific number of I/O requests because the available number of descriptors depends on the chain size of requests placed into the ring buffer.

VIRTIO supports descriptor chaining although drivers usually forego it when VIRTIO_F_RING_INDIRECT_DESC is available.

NVMe and io_uring do not support descriptor chaining, instead relying on embedded and external descriptors.

Limits on in-flight requests

The maximum number of in-flight requests depends on the ring buffer design. Designs where descriptors are occupied from submission until completion prevent descriptor reuse for other requests while the current request is in flight.

An alternative design is where the device processes submitted descriptors and they are considered free again as soon as the device has looked at them. This approach is natural when separate submission and completion queues are used and there is no relationship between the two descriptor rings.

VIRTIO requests occupy descriptors for the duration of their lifetime, at least in the Split Virtqueue format. Therefore the number of in-flight requests is influenced by the descriptor table size.

NVMe has separate Submission Queues and Completion Queues, but its design still limits the number of in-flight requests to the queue size. The Completion Queue Entry's SQ Head Pointer (SQHD) field precludes having more requests in flight than the Submission Queue size because the field would no longer be unique. Additionally, the driver has no way of detecting Submission Queue Head changes, so it only knows there is space for more submissions when completions occur.

io_uring has independent submission (SQ) and completions queues (CQ) with support for more in-flight requests than the ring buffer size. When there are more in-flight requests than CQ capacity, it's possible to overflow the CQ. io_uring has a backlog mechanism for this case, although the intention is for applications to properly size queues to avoid hitting the backlog often.

Conclusion

VIRTIO, NVMe, and io_uring have slightly different takes on queue design. The semantics and performance vary due to these differences. VIRTIO lacks data embedding inside descriptors. io_uring supports more in-flight requests than the queue size. NVMe and io_uring rely on external descriptors with no ability to chain descriptors.

Friday, April 29, 2022

Debugging Flatpak applications

Flatpak is a way to distribute applications on Linux. Its container-style approach allows applications to run across Linux distributions. This means native packages (rpm, deb, etc) are not needed and it's relatively easy to get your app to Linux users with fewer worries about distro compatibility. This makes life a lot easier for developers and is also convenient for users.

I've run popular applications like OBS Studio as flatpaks and even publish my own on Flathub, a popular hosting site for applications. Today I figured out how to debug flatpaks, which requires some extra steps that I'll share below so I don't forget them myself!

Bonus Tip: Testing local flatpaks

If you're building a flatpak of your own application it's handy to use the dir sources type in the manifest to compile your application's source code from a local directory instead of a git tag or tarball URL. This way you can make changes to the source code and test them quickly inside Flatpak.

Put something along these lines in the manifest's modules object where /home/user/my-app is you local directory with your app's source code:

{
     "name": "my-app",
     "sources": [
         {
             "type": "dir",
             "path": "/home/user/my-app"
         }
     ],
     ...
}

Building and installing apps with debuginfo

flatpak-builder(1) automatically creates a separate .Debug extension for your flatpak that contains your application's debuginfo. You'll need the .Debug extension if you want proper backtraces and source level debugging. At the time of writing the Flatpak documentation did not mention how to install the locally-built .Debug extension. Here is how:

$ flatpak-builder --user --force-clean --install build my.org.app.json
$ flatpak install --user --reinstall --assumeyes "$(pwd)/.flatpak-builder/cache" my.org.app.Debug

It might be a good idea to install debuginfo for the system libraries in your SDK too in case it's not already installed:

$ flatpak install org.kde.Sdk.Debug # or your runtime's SDK

Running applications for debugging

There is a flatpak(1) option that launches the application with the SDK instead of the Runtime:

$ flatpak run --user --devel my.org.app

The SDK contains development tools whereas the Runtime just has the files needed to run applications.

It can also be handy to launch a shell so you can control the launch of your app and maybe use gdb or strace:

$ flatpak run --user --devel --command=sh my.org.app
[📦 my.org.app ~]$ gdb /app/bin/my-app

Working with core dumps

If your application crashes it will dump core like any other process. However, existing ways of inspecting core dumps like coredumpctl(1) are not fully functional because the process ran inside namespaces and debuginfo is located inside flatpaks instead of the usual system-wide /usr/lib/debug location. coredumpctl(1), gdb, etc aren't Flatpak-aware and need extra help.

Use the flatpak-coredumpctl wrapper to launch gdb:

$ flatpak-coredumpctl -m <PID> my.org.app

You can get PID from the list printed by coredumpctl(1).

Conclusion

This article showed how to install locally-built .Debug extensions and inspect core dumps when using Flatpak. I hope that over time these manual steps will become unnecessary as flatpak-builder(1) and coredumpctl(1) are extended to automatically install .Debug extensions and handle Flatpak core dumps. For now it just takes a few extra commands compared to debugging regular applications.