From: Jerome Karp (jerome.karp_at_med.einstein.yu.edu)
Date: Tue Sep 22 2015 - 10:39:30 CDT
Thanks! I did see the tutorial and looked at the files, but couldn't find
the main file *swarms.namd* in the folder. (The Archives folder has two
subfolders, "Path Collective Variables" and "String with Swarms of
Trajectories," and *initial.conf* [and also *restart.conf*] call
*../swarms.namd*, but this file isn't included in the directory immediately
above, or in any of the subdirectories as far as I can find.) I assume
this file is supposed to be similar to *replica.namd* which is in the
*/lib/replica* folder of the NAMD base directory, but it doesn't seem to be
included. Is there anywhere I can find it?
Thanks again for your help.
- Jerry Karp
On Tue, Sep 22, 2015 at 11:26 AM, Chris Chipot <chipot_at_ks.uiuc.edu> wrote:
> Jerome,
>
> you might find it useful to check out the tutorials at
> http://www.ks.uiuc.edu/Training/Tutorials/. We have released a new
> tutorial on the string method
> with swarms of trajectories, which can be downloaded from there. Once
> you have a converged string, the tutorial also proposes a route to compute
> the free-energy change along it. Feel free to try the tutorial out and
> give us
> some feedback, as I am sure, it is perfectible.
>
> Cheers,
>
> Chris Chipot
>
>
>
>
> On 9/22/15 8:05 AM, Jerome Karp wrote:
>
> 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
>>
>>
>>
>
>
> --
> _______________________________________________________________________
>
> Chris Chipot, Ph.D.
> Theoretical and Computational Biophysics Group
> 3047 Beckman Institute for Advanced Science and Technology
> University of Illinois at Urbana-Champaign
> 405 North Mathews
> Urbana, Illinois 61801 Phone: (217) 244-5493
>
> E-mail: chipot_at_ks.uiuc.edu
> Christophe.Chipot_at_Univ-Lorraine.fr
> Web: http://www.ks.uiuc.edu/~chipot
> http://www.edam.uhp-nancy.fr
>
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> Thomas L. Friedman
> _______________________________________________________________________
>
>
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