[Beowulf] Frontier Announcement

John Hearns hearnsj at googlemail.com
Thu May 9 09:53:20 PDT 2019

Gerald that is an excellent history.
One small thing though: "Of course the ML came along"
What came first - the chicken or the egg? Perhaps the Nvidia ecosystem made
the ML revolution possible.
You could run ML models on a cheap workstation or a laptop with an Nvidia
Indeed I am sitting next to my Nvidia Jetson Nano - 90 dollars for a GPU
which can do deep learning.
Prior to CUDA etc. you could of course do machine learning, but it was
being done in universities.
I stand to be corrected.

On Thu, 9 May 2019 at 17:40, Gerald Henriksen <ghenriks at gmail.com> wrote:

> On Wed, 8 May 2019 14:13:51 -0400, you wrote:
> >On Wed, May 8, 2019 at 1:47 PM Jörg Saßmannshausen <
> >sassy-work at sassy.formativ.net> wrote:
> >>
> >Once upon a time portability, interoperabiilty, standardization, were
> >considered good software and hardware attributes.
> >Whatever happened to them?
> I suspect in a lot of cases they were more ideals and goals than
> actual things.
> Just look at the struggles the various BSDs have in getting a lot of
> software running given the inherent Linuxisms that seem to happen.
> In the case of what is relevant to this discussion, CUDA, Nvidia saw
> an opportunity (and perhaps also reacted to the threat of not having
> their own CPU to counter the integrated GPU market) and invested
> heavily into making their GPUs more than simply a 3D graphics device.
> As Nvidia built up the libraries and other software to make life
> easier for programmers to get the most out of Nvidia hardware AMD and
> Intel ignored the threat until it was too late, and partial attempts
> at open standards struggled.
> And programmers, given struggling with OpenCL or other options vs
> going with CUDA with its tools and libraries, went for what gave them
> the best performance and easiest implementation (aka a win/win).
> Of course then ML came along and suddenly AMD and Intel couldn't
> ignore the market anymore, but they are both struggling from a distant
> 2nd place to try and replicate the CUDA ecosystem...
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