Re: performance loss on GPUs

From: Aron Broom (broomsday_at_gmail.com)
Date: Wed Nov 28 2012 - 10:40:11 CST

right. So based on all of that, if the number of atoms is smallish and
you're not intending to use a cutoff, the "staticAtomAssignment yes" option
in NAMD is worthwhile, otherwise you just have to suffer I suppose. With a
single protein of ~2000 atoms, I see about the same simulation speed in
implicit solvent using either a 12 angstrom cutoff, or no cutoff with
staticAtomAssignment on an M2070 GPU. Not sure to what system size that
still holds true.

~Aron

P.S.

That's a neat video.

On Wed, Nov 28, 2012 at 11:07 AM, Axel Kohlmeyer <akohlmey_at_gmail.com> wrote:

> On Wed, Nov 28, 2012 at 4:57 PM, Aron Broom <broomsday_at_gmail.com> wrote:
> > Just checked some simulations, and I'm only really seeing an ~5% speed
> drop
> > over 50,000,000 steps with implicit solvent. That is also using
>
> i didn't say that *all* implicit solvent simulations.
> were affected, but rather simulation where the
> number of neighbors is changing. that may or
> may not be with implicit solvent. it is just more likely.
>
> you can have it also when you have, say, a liquid/gas
> system where you heat up the liquid to evaporate
> (the simulation gets faster this time).
>
> when doing self assembly with implicit solvent, the
> number of neighbors per atom increases and the
> simulation (GPU or CPU) will slow down. also in the
> case depicted in this movie the simulation speed
> varies significantly, depending on where exactly
> the buckyballs are located.
> http://youtu.be/JGz5oFR71jA
>
> axel.
>
> > metadynamics, which could slow things down over time also.
>
>
> >
> > --
> > Aron Broom M.Sc
> > PhD Student
> > Department of Chemistry
> > University of Waterloo
> >
>
>
>
> --
> Dr. Axel Kohlmeyer akohlmey_at_gmail.com http://goo.gl/1wk0
> International Centre for Theoretical Physics, Trieste. Italy.
>

-- 
Aron Broom M.Sc
PhD Student
Department of Chemistry
University of Waterloo

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