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From:   Daniel Vetter <daniel@ffwll.ch>
Date:   Mon, 17 May 2021 21:39:39 +0200
Message-ID: <CAKMK7uFzcdX-knzZEwLWsPiF2WfePdr0ou1dD169Pwx0GMzgtQ@mail.gmail.com>
Subject: Re: [PATCH v3 00/14] Driver of Intel(R) Gaussian & Neural Accelerator
To:     Alex Deucher <alexdeucher@gmail.com>
Cc:     Thomas Zimmermann <tzimmermann@suse.de>,
        Arnd Bergmann <arnd@arndb.de>,
        Jonathan Corbet <corbet@lwn.net>,
        Greg Kroah-Hartman <gregkh@linuxfoundation.org>,
        Dragan Cvetic <dragan.cvetic@xilinx.com>,
        "open list:DOCUMENTATION" <linux-doc@vger.kernel.org>,
        Linux Kernel Mailing List <linux-kernel@vger.kernel.org>,
        DRI Development <dri-devel@lists.freedesktop.org>,
        Maciej Kwapulinski <maciej.kwapulinski@linux.intel.com>,
        Andy Shevchenko <andy.shevchenko@gmail.com>,
        Derek Kiernan <derek.kiernan@xilinx.com>
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On Mon, May 17, 2021 at 9:23 PM Alex Deucher <alexdeucher@gmail.com> wrote:
>
> On Mon, May 17, 2021 at 3:12 PM Thomas Zimmermann <tzimmermann@suse.de> w=
rote:
> >
> > Hi
> >
> > Am 17.05.21 um 09:40 schrieb Daniel Vetter:
> > > On Fri, May 14, 2021 at 11:00:38AM +0200, Arnd Bergmann wrote:
> > >> On Fri, May 14, 2021 at 10:34 AM Greg Kroah-Hartman
> > >> <gregkh@linuxfoundation.org> wrote:
> > >>> On Thu, May 13, 2021 at 01:00:26PM +0200, Maciej Kwapulinski wrote:
> > >>>> Dear kernel maintainers,
> > >>>>
> > >>>> This submission is a kernel driver to support Intel(R) Gaussian & =
Neural
> > >>>> Accelerator (Intel(R) GNA). Intel(R) GNA is a PCI-based neural co-=
processor
> > >>>> available on multiple Intel platforms. AI developers and users can=
 offload
> > >>>> continuous inference workloads to an Intel(R) GNA device in order =
to
> > free
> > >>>> processor resources and save power. Noise reduction and speech rec=
ognition
> > >>>> are the examples of the workloads Intel(R) GNA deals with while it=
s usage
> > >>>> is not limited to the two.
> > >>>
> > >>> How does this compare with the "nnpi" driver being proposed here:
> > >>>          https://lore.kernel.org/r/20210513085725.45528-1-guy.zadic=
ario@intel.com
> > >>>
> > >>> Please work with those developers to share code and userspace api a=
nd
> > >>> tools.  Having the community review two totally different apis and
> > >>> drivers for the same type of functionality from the same company is
> > >>> totally wasteful of our time and energy.
> > >>
> > >> Agreed, but I think we should go further than this and work towards =
a
> > >> subsystem across companies for machine learning and neural networks
> > >> accelerators for both inferencing and training.
> > >
> > > We have, it's called drivers/gpu. Feel free to rename to drivers/xpu =
or
> > > think G as in General, not Graphisc.
> >
> > I hope this was a joke.
> >
> > Just some thoughts:
> >
> > AFAICT AI first came as an application of GPUs, but has now
> > evolved/specialized into something of its own. I can imagine sharing
> > some code among the various subsystems, say GEM/TTM internals for memor=
y
> > management. Besides that there's probably little that can be shared in
> > the userspace interfaces. A GPU is device that puts an image onto the
> > screen and an AI accelerator isn't. Treating both as the same, even if
> > they share similar chip architectures, seems like a stretch. They might
> > evolve in different directions and fit less and less under the same
> > umbrella.
>
> The putting something on the screen is just a tiny part of what GPUs
> do these days.  Many GPUs don't even have display hardware anymore.
> Even with drawing APIs, it's just some operation that you do with
> memory.  The display may be another device entirely.  GPUs also do
> video encode and decode, jpeg acceleration, etc.  drivers/gpu seems
> like a logical place to me.  Call it drivers/accelerators if you like.
> Other than modesetting most of the shared infrastructure in
> drivers/gpu is around memory management and synchronization which are
> all the hard parts.  Better to try and share that than to reinvent
> that in some other subsystem.

Maybe to add: Most of our driver stack is in userspace (like for NN/AI
chips too), both where high amounts of code sharing are the norm (like
with mesa3d) and areas there the landscape is a lot more fragmented
(like compute and media, where the userspace driver APIs are all
different for each vendor, or at least highly specialized). That's
another thing which I don't think any other kernel subsystem has, at
least as much as we do.

So for both the big design questions on how the overall stack is
organized down to the details like code sharing, drivers/g^Hxpu should
be the best place. Aside from the pesky problem that we do actually
look at the userspace side and have some expectations on that too, not
just on the kernel code alone.
-Daniel

>
> Alex
>
> >
> > And as Dave mentioned, these devices are hard to obtain. We don't reall=
y
> > know what we sign up for.
> >
> > Just my 2 cents.
> >
> > Best regards
> > Thomas
> >
> >
> >
> > --
> > Thomas Zimmermann
> > Graphics Driver Developer
> > SUSE Software Solutions Germany GmbH
> > Maxfeldstr. 5, 90409 N=C3=BCrnberg, Germany
> > (HRB 36809, AG N=C3=BCrnberg)
> > Gesch=C3=A4ftsf=C3=BChrer: Felix Imend=C3=B6rffer
> >


--=20
Daniel Vetter
Software Engineer, Intel Corporation
http://blog.ffwll.ch