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Message-ID: <CAPj87rMqYNdHMT5v9fiMuDzcB8462nJuthB9To70JOsORgxk=w@mail.gmail.com>
Date:   Mon, 17 May 2021 20:32:43 +0100
From:   Daniel Stone <daniel@...ishbar.org>
To:     Thomas Zimmermann <tzimmermann@...e.de>
Cc:     Arnd Bergmann <arnd@...db.de>, Dave Airlie <airlied@...il.com>,
        Greg Kroah-Hartman <gregkh@...uxfoundation.org>,
        Maciej Kwapulinski <maciej.kwapulinski@...ux.intel.com>,
        Jonathan Corbet <corbet@....net>,
        Derek Kiernan <derek.kiernan@...inx.com>,
        Dragan Cvetic <dragan.cvetic@...inx.com>,
        Andy Shevchenko <andy.shevchenko@...il.com>,
        Linux Kernel Mailing List <linux-kernel@...r.kernel.org>,
        "open list:DOCUMENTATION" <linux-doc@...r.kernel.org>,
        DRI Development <dri-devel@...ts.freedesktop.org>
Subject: Re: [PATCH v3 00/14] Driver of Intel(R) Gaussian & Neural Accelerator

Hi,

On Mon, 17 May 2021 at 20:12, Thomas Zimmermann <tzimmermann@...e.de> wrote:
> Am 17.05.21 um 09:40 schrieb Daniel Vetter:
> > 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 memory
> 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.

But it isn't. A GPU is a device that has a kernel-arbitrated MMU
hosting kernel-managed buffers, executes user-supplied compiled
programs with reference to those buffers and other jobs, and informs
the kernel about progress.

KMS lies under the same third-level directory, but even when GPU and
display are on the same die, they're totally different IP blocks
developed on different schedules which are just periodically glued
together.

> 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.

Why not? All we have in common in GPU land right now is MMU + buffer
references + job scheduling + synchronisation. None of this has common
top-level API, or even a common top-level model. It's not just ISA
differences, but we have very old-school devices where the kernel
needs to register fill on every job, living next to middle-age devices
where the kernel and userspace co-operate to fill a ring buffer,
living next to modern devices where userspace does some stuff and then
the hardware makes it happen with the bare minimum of kernel
awareness.

Honestly I think there's more difference between lima and amdgpu then
there is between amdgpu and current NN/ML devices.

Cheers,
Daniel

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