Re: string method in NAMD 2.10

From: Jerome Karp (jerome.karp_at_med.einstein.yu.edu)
Date: Tue Sep 22 2015 - 10:05:05 CDT

Hi,

Thanks for the helpful information! I'm surprised there doesn't seem to be
a script included with the release - I wonder if it's there but I can't
find it - but anyway I think this will help me get started in implementing
the algorithm.

Thanks again!
- Jerry Karp

On Tue, Sep 22, 2015 at 6:31 AM, Thomas Evangelidis <tevang3_at_gmail.com>
wrote:

> ​And this:
>
>
> ​---------- Forwarded message ----------
> From: Luca Maragliano <Luca.Maragliano_at_iit.it>
> Date: 18 December 2014 at 15:35
> Subject: RE: string method with swarms-of-trajectories - NAMD
> implementation
> To: Thomas Evangelidis <tevang3_at_gmail.com>
>
>
> Hi Thomas,
>
> I don't know if the same code can run on GPU's, I have no experience on
> that.
>
> Most importantly however the code was done serially because the system is
> super-simple (the AD
> in vacuum). There is no point in doing the string method serially
> otherwise, it would be a great
> loss of time for any reasonable size system.
>
> The evolution is just a steepest descent in the space of CVs, where you
> use an instantaneous
> approximation of the mean force rather than the true one (which otherwise
> would be estimated
> via an average on the x at z fixed).
>
> the slowing down recovers for the use of instantaneous rather then average
> and it is obtained by simply
> scaling the time step of z motion wrt that of the x (which is internal in
> NAMD).
> This dynamics is performed at each image and can be sketched as
>
> - evolve x with NAMD + harmonic force from potential
> .5*k*(theta(x)-z)^2 and its proper tstep
> - evolve z with force k*(thetha(x)-z) and scaled tstep
>
> If the CV is non-linear then the mean force on z is multiplied by the
> metric factor M.
>
> Every few steps of this descent you reparametrize the values along the
> curve (an example code in fortran
> is also in the bundle). Reparametrization does not require MD but does
> require communication of the CV
> values of all images.
>
> So in general you have
>
> - few steps of descent in CV space, at each image independently of the
> others
> - reparametrization call
>
>
> How many steps in between rep calls depends on the system. Too few would
> require too much communication
> and too many would break the curve integrity (but you can cycle the
> reparametrization a few times, if needed).
>
> Again please feel free to ask at any time
>
> ciao,
>
> Luca
>
> ------------------------------
> *From:* Thomas Evangelidis [tevang3_at_gmail.com]
> *Sent:* Thursday, December 18, 2014 2:07 PM
> *To:* Luca Maragliano
> *Subject:* Re: string method with swarms-of-trajectories - NAMD
> implementation
>
>
>
> Hi Luca,
>
> Thank you for the clarification
>
>
>> For the implementation of the otf version, look at table 1 of our JCTC
>> paper (page 527).
>> The otf method is similar to the mean forces method except that steps 1-3
>> are
>> substituted by the concurrent evolution of the CVs and the physical
>> variables, coupled
>> via the harmonic potential. In other words, rather than doing step 1
>> with fixed CV values
>> you evolve the CVs as well but on a different, slowed-down time-scale,
>> i.e. you give them
>> a high mass or friction. More details are in appendix B.
>> In terms of implementation, this amounts to modify the restraint
>> dynamics of step 1 by
>> introducing a line that evolves the CV values.
>>
>>
> Do those files with the "otf" keyword in their name need the modification
> you mentioned? I need to read more carefully your paper to understand how
> program the restr_dih_otf.tcl script to evolve the CVs slowly. Right now
> things are hectic, so I will probably come back with more questions. I just
> have one simple question, I saw you evolve the image trajectories serially.
> Does this mean the same code car run on GPUs?
>
> thank you for your help!
> Thomas
> ​
>
>

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