Thank you for sharing this information. People who develop quantum
chemistry codes on this list for GPUs appreciate your experience and advice
on matters such as these. I do not appreciate the complexity of the market,
as I mostly struggle just to do proper coding for GPUs; knowing this sort
of big-picture information is invaluable.
On Mon, Oct 30, 2017 at 2:57 PM, Ross Walker <ross.rosswalker.co.uk> wrote:
> Dear All,
>
> In the spirit of open discussion I want to bring the AMBER community's
> attention to a concern raised in two recent news articles:
>
> 1) "Nvidia halts distribution partners from selling GeForce graphics cards
> to server, HPC sectors" - http://www.digitimes.com/news/
> a20171027PD200.html
>
> 2) "Nvidia is cracking down on servers powered by Geforce graphics cards"
> - https://www.pcgamesn.com/nvidia-geforce-server
>
> I know many of you have benefitted greatly over the years from the GPU
> revolution that has transformed the field of Molecular Dynamics. A lot of
> the work in this field was provided by people volunteering their time and
> grew out of the idea that many of us could not have access to or could not
> afford supercomputers for MD. The underlying drive was to bring
> supercomputing performance to the 99% and thus greatly extend the amount
> and quality of science each of us could do. For AMBER this meant supporting
> all three models of NVIDIA graphics card, Geforce, Quadro and Tesla in
> whatever format or combination, you the scientist and customer, wanted.
>
> In my opinion key to AMBER's success was the idea that, for running MD
> simulations, very few people in the academic field, and indeed many R&D
> groups within companies, small or large, could afford the high end tesla
> systems, whose price has been steadily going up substantially above
> inflation with each new generation (for example the $149K DGX-1). The
> understanding, both mine and that of the field in general, has essentially
> always been that assuming one was willing to accept the risks on
> reliability etc, use of Geforce cards should be perfectly reasonable. We
> are not after all running US air traffic control, or some other equally
> critical system. It is prudent use of limited R&D funds, or in many cases
> tax payer money and we are the customers after all so should be free to
> choose the hardware we buy. NVIDIA has fought a number of us for many years
> on this front but mostly in a passive aggressive stance with the occasional
> personal insult or threat. As highlighted in the above articles with the
> latest AI bubble they have cemented a worrying monopoly and are now getting
> substantially more aggressive, using this monopoly to pressure suppliers to
> try to effectively ban the use of Geforce cards for scientific compute and
> restrict what we can buy to Tesla cards, that for the vast majority of us
> are simply out of our price range.
>
> In my opinion this a very worrying trend that could hurt us all and have
> serious repercussions on all of our scientific productivities and the field
> in general. If this is a concern to you too I would encourage each of you
> to speak up. Contact people you know at NVIDIA and make your concerns
> heard. I am concerned that if we as a community do not speak up now we
> could see our field be completely priced out of the ability to make use of
> GPUs for MD over the next year.
>
> All the best
> Ross
>
>
>
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>
--
Robert Molt Jr
"Nothing is as practical as good theory."
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Received on Mon Oct 30 2017 - 13:00:02 PDT
