Re: [dpdk-dev] [RFC PATCH v2 0/7] heterogeneous computing library

[Thomas Monjalon <thomas@monjalon.net>]

31/07/2021 09:06, Jerin Jacob:
> On Fri, Jul 30, 2021 at 7:25 PM Thomas Monjalon <thomas@monjalon.net> wrote:
> >
> > From: Elena Agostini <eagostini@nvidia.com>
> >
> > In heterogeneous computing system, processing is not only in the CPU.
> > Some tasks can be delegated to devices working in parallel.
> >
> > The goal of this new library is to enhance the collaboration between
> > DPDK, that's primarily a CPU framework, and other type of devices like GPUs.
> >
> > When mixing network activity with task processing on a non-CPU device,
> > there may be the need to put in communication the CPU with the device
> > in order to manage the memory, synchronize operations, exchange info, etc..
> >
> > This library provides a number of new features:
> > - Interoperability with device specific library with generic handlers
> > - Possibility to allocate and free memory on the device
> > - Possibility to allocate and free memory on the CPU but visible from the device
> > - Communication functions to enhance the dialog between the CPU and the device
> >
> > The infrastructure is prepared to welcome drivers in drivers/hc/
> > as the upcoming NVIDIA one, implementing the hcdev API.
> >
> > Some parts are not complete:
> >   - locks
> >   - memory allocation table
> >   - memory freeing
> >   - guide documentation
> >   - integration in devtools/check-doc-vs-code.sh
> >   - unit tests
> >   - integration in testpmd to enable Rx/Tx to/from GPU memory.
> 
> Since the above line is the crux of the following text, I will start
> from this point.
> 
> + Techboard
> 
> I  can give my honest feedback on this.
> 
> I can map similar  stuff  in Marvell HW, where we do machine learning
> as compute offload
> on a different class of CPU.
> 
> In terms of RFC patch features
> 
> 1) memory API - Use cases are aligned
> 2) communication flag and communication list
> Our structure is completely different and we are using HW ring kind of
> interface to post the job to compute interface and
> the job completion result happens through the event device.
> Kind of similar to the DMA API that has been discussed on the mailing list.

Interesting.

> Now the bigger question is why need to Tx and then Rx something to
> compute the device
> Isn't  ot offload something? If so, why not add the those offload in
> respective subsystem
> to improve the subsystem(ethdev, cryptiodev etc) features set to adapt
> new features or
> introduce new subsystem (like ML, Inline Baseband processing) so that
> it will be an opportunity to
> implement the same in  HW or compute device. For example, if we take
> this path, ML offloading will
> be application code like testpmd, which deals with "specific" device
> commands(aka glorified rawdev)
> to deal with specific computing device offload "COMMANDS"
> (The commands will be specific to  offload device, the same code wont
> run on  other compute device)

Having specific features API is convenient for compatibility
between devices, yes, for the set of defined features.
Our approach is to start with a flexible API that the application
can use to implement any processing because with GPU programming,
there is no restriction on what can be achieved.
This approach does not contradict what you propose,
it does not prevent extending existing classes.

> Just my _personal_ preference is to have specific subsystems to
> improve the DPDK instead of raw device kind of
> path. If we decide another path as a community it is _fine_ too(as a
> _project manager_ point of view it will be an easy path to dump SDK
> stuff to DPDK without introducing the pain of the subsystem nor
> improving the DPDK).

Adding a new class API is also improving DPDK.