
Anton Sequel Makes Stronger Case for Custom Supercomputing - jonbaer
http://www.nextplatform.com/2016/02/04/anton-sequel-makes-stronger-case-for-custom-supercomputing/
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jedbrown
A huge source of uncertainty in molecular dynamics comes from the force model,
which are crude approximations of electronic structure. There is a great deal
of active research on improved force models, many of which are implemented in
AMBER ([http://ambermd.org](http://ambermd.org)) and can be used from most
popular MD packages. Other approximations, such as the cut-off for short- vs
long-range force evaluation, must also be validated.

Anton is built for a very specific configuration; the modeling assumptions may
or may not be valid for a given scientific or engineering experiment. Its
value is in being able to rapidly experiments for which the modeling
assumptions have already been validated (and run those configurations for
longer simulated time), but not for questioning the modeling assumptions or
for developing better models.

~~~
p4wnc6
This is a very underappreciated point. For example, in pharmaceutical drug
discovery, what often matters most is the ability to play around with
different modeling assumptions, and to do large-scale "search engine" work on
different compound properties and how they might affect desired overall
properties of the final product.

I wonder if one reason why this highly specific computational architecture is
only deployed in two places (as far as I can tell) is because it's actually
_not_ very applicable to mainstream molecular dynamics use cases? A lot of the
business around pharma drug discovery seems to be pushing for more cloud
computing solutions that offer better analytics APIs for engineers, rather
than beefing up hardware for larger-scale simulations.

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ChuckMcM
It is an interesting time to bring out a new architecture. There was a time
that any short term advantage a custom architecture would have over commodity
chips would evaporate in 4 years, less than the depreciation time of the
machine. However as the ability to scale commodity machines becomes harder,
and they scale in useless ways (like the P4 debacle of focusing on video
streaming performance) the economics once again shift to more bespoke
machines. And some of these machines understand that memory throughput is just
as important as instructions per clock and so you get more general purpose
architectures with the memory bandwidth of modern GPUS. That opens up some
interesting opportunities for large memory computation spaces.

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iskander
Has molecular dynamics had any big success stories? Have new drugs been
approved which were initially found by in-silico screening using MD?

