On 22-02-2023 15:32, Stefan Hajnoczi wrote:
On Wed, Feb 08, 2023 at 05:29:25PM +0100, Peter-Jan Gootzen wrote:
On 08/02/2023 11:43, Stefan Hajnoczi wrote:
On Wed, Feb 08, 2023 at 09:33:33AM +0100, Peter-Jan Gootzen wrote:
On 07/02/2023 22:57, Vivek Goyal wrote:
On Tue, Feb 07, 2023 at 04:32:02PM -0500, Stefan Hajnoczi wrote:
On Tue, Feb 07, 2023 at 02:53:58PM -0500, Vivek Goyal wrote:
On Tue, Feb 07, 2023 at 02:45:39PM -0500, Stefan Hajnoczi wrote:
On Tue, Feb 07, 2023 at 11:14:46AM +0100, Peter-Jan Gootzen wrote:
Hi,
[cc German]
For my MSc thesis project in collaboration with IBM
(https://github.com/IBM/dpu-virtio-fs) we are looking to improve the
performance of the virtio-fs driver in high throughput scenarios. We think
the main bottleneck is the fact that the virtio-fs driver does not support
multi-queue (while the spec does). A big factor in this is that our setup on
the virtio-fs device-side (a DPU) does not easily allow multiple cores to
tend to a single virtio queue.
This is an interesting limitation in DPU.
Virtqueues are single-consumer queues anyway. Sharing them between
multiple threads would be expensive. I think using multiqueue is natural
and not specific to DPUs.
Can we create multiple threads (a thread pool) on DPU and let these
threads process requests in parallel (While there is only one virt
queue).
So this is what we had done in virtiofsd. One thread is dedicated to
pull the requests from virt queue and then pass the request to thread
pool to process it. And that seems to help with performance in
certain cases.
Is that possible on DPU? That itself can give a nice performance
boost for certain workloads without having to implement multiqueue
actually.
Just curious. I am not opposed to the idea of multiqueue. I am
just curious about the kind of performance gain (if any) it can
provide. And will this be helpful for rust virtiofsd running on
host as well?
Thanks
Vivek
There is technically nothing preventing us from consuming a single queue on
multiple cores, however our current Virtio implementation (DPU-side) is set
up with the assumption that you should never want to do that (concurrency
mayham around the Virtqueues and the DMAs). So instead of putting all the
work into reworking the implementation to support that and still incur the
big overhead, we see it more fitting to amend the virtio-fs driver with
multi-queue support.
Is it just a theory at this point of time or have you implemented
it and seeing significant performance benefit with multiqueue?
It is a theory, but we are currently seeing that using the single request
queue, the single core attending to that queue on the DPU is reasonably
close to being fully saturated.
And will this be helpful for rust virtiofsd running on
host as well?
I figure this would be dependent on the workload and the users-needs.
Having many cores concurrently pulling on their own virtq and then
immediately process the request locally would of course improve performance.
But we are offloading all this work to the DPU, for providing
high-throughput cloud services.
I think Vivek is getting at whether your code processes requests
sequentially or in parallel. A single thread processing the virtqueue
that hands off requests to worker threads or uses io_uring to perform
I/O asynchronously will perform differently from a single thread that
processes requests sequentially in a blocking fashion. Multiqueue is not
necessary for parallelism, but the single queue might become a
bottleneck.
Requests are handled non-blocking with remote IO on the DPU. Our current
architecture is as follows:
T1: Tends to the Virtq, parses FUSE to remote IO and fires off the
asynchronous remote IO.
T2: Polls for completion on the remote IO and parses it back to FUSE, puts
the FUSE buffers in a completion queue of T1.
T1: Handles the Virtio completion and DMA of the requests in the CQ.
Thread 1 is busy polling on its two queues (Virtq and CQ) with equal
priority, thread 2 is busy polling as well. This setup is not really
optimal, but we are working within the constraints of both our DPU and
remote IO stack.
Why does T1 need to handle VIRTIO completion and DMA requests instead of
T2?
Stefan
No good reason other than the fact that the concurrency safety of our
DPU's virtio-fs library requires this.
> I had been doing some performance benchmarking for virtio-fs and I found
> some old results.
>
>
https://github.com/rhvgoyal/virtiofs-tests/tree/master/performance-results/feb-10-2021
>
> While running on top of local fs, with bs=4K, with single queue I could
> achieve more than 600MB/s.
>
> NAME WORKLOAD Bandwidth IOPS
> default seqread-psync 625.0mb 156.2k
> no-tpool seqread-psync 660.8mb 165.2k
>
> But catch here I think is that host is doing the caching. In your
> case I am assuming there is no caching at DPU and all the I/O is
> going to remote storage (which might be doing caching in memory).
>
> Anyway, point I am trying to make is that even with single vq, virtiofs
> can push a reasonable amount of I/O.
>
> I will be cuirous to find how multiqueue can improve these numbers
> further.
We are currently seeing the following throughput numbers:
https://github.com/IBM/dpu-virtio-fs/blob/d0e0560546e2da86b0022a69abe02ab6ac4a6541/experiments/results/graphs/nulldev_tp.pdf
This is using a null device implementation in the DPU (immediately
return reads and writes in the FUSE file system). All using a single vq
and one DPU thread attending to it. On the host this experiment is using
two fio threads pinned to the DPU's NUMA node. We see no additional
throughput when using more than two threads.
> I am wondering how did you conclude that single vq is the bottleneck for
> performance and not the remote storage DPU is sending I/O to.
The single vq is not the sole bottleneck.
With us operating within the constrains in our DPU library, it leads us
to two options:
1. Do thread pooling DPU-side to distribute the requests from the single
queue to our eight cores.
2. Implement multi-queue.
We would like to go for the multi-queue option as it is the superior
option with it exploiting parallelism both host and DPU-side (like in
the block and net layers).
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