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Re: [lammps-users] Computer Difference


From: Emir Kocer <emirkocer92@...24...>
Date: Tue, 19 Sep 2017 12:38:41 +0300

Hi Axel,

20 ps was dump interval of auto-correlation function (ACF) that we were using. It is the 'd' value of the sample code in the following link.

http://lammps.sandia.gov/doc/compute_heat_flux.html

However, we thought that there might be random noise associated with the ACF, and reduced dump interval to 1 ps by following the procedure of

Chen, Zhang, Baowen, "How to improve the accuracy of equilibrium molecular dynamics for computation of thermal conductivity?" Physics Letters (2010)

Now we use Green-Kubo (GK) parameters of s=2, p=500, d=1000 (w.r.t notation of the sample GK code above), and run preliminary simulations with 100 ps NPT equilibration + 100 ps NVE equilibration + 100 ps NVE production run. So the production run now includes 100 different ACFs, and corresponding thermal conductivity (k) values. We tested LAMMPS versions, machines, and number of processors(NoP) in the first place and surprisingly (at least for me), we observed significant effect of NoP for both machines with different versions. The k values are generally converging for the last 40 data (out of 100 in the production run), and giving standard deviation in the order of 0.01 after that).




We believe that we can solve issues for GK parameters by extending our literature analysis at some point, as you suggested (This may not be a LAMMPS topic anyways). However, first we need to resolve this problem (if you want to call it like this) about parallel computing as it may suppress any effect on GK that we may want to see. So we are curious about your comments about the table above, if it is a bug, or our mistake in implementation etc. Thanks for helping.

Emir


2017-09-14 16:23 GMT+03:00 Axel Kohlmeyer <akohlmey@...24...>:


On Thu, Sep 14, 2017 at 8:40 AM, Emir Koçer <emirkocer92@...24...> wrote:
 

Yes I've checked, and by the way the older version measures it much better than the latest version.

emir,

​you seem to be mixing up two things here: getting the expected result and getting the correct result for the model and method at hand.

i know from personal experience, how many bugs and problematic issues were fixed in LAMMPS over the ​last 2 years since we started to systematically use code analysis and code review tools. also, unless you compiled your LAMMPS binaries yourself, please note, that the precompiled LAMMPS windows binaries from two years ago were based on an experimental fork of LAMMPS with additional changes and potentially additional bugs. current windows binaries for LAMMPS are built from the *exact* same sources.

it is for certain a misguided approach to declare a version of a software "better" solely based on how well its output agrees with your expectations.
moreover, the same version of the same software *has* to produce the *same* results. mind you, that doesn't mean *identical*, but with the same *statistical certainty*. 

now, since you are using a statistical mechanical method, statistical certainty is a key issue here. 
​i recall you mentioning a time span of 20ps somewhere. is that the total simulation time? or the total time of ​data accumulation? or something else?
20ps would be rather short for total simulation time. it would even be little for equilibration. as a rule of the thumb you can assume that for typical bulk water systems, you need a space of the order of 1ps between two configurations for them to be mostly statistically independent. if you are looking at data collected more frequently (as is often needed), you have to factor in, that your statistical relevance is reduced and the statistical certainty much less than what a computed standard deviation would suggest. to get a handle on that you need to review and compare multiple independent and uncorrelated data sets.

this also means, that it is irrelevant for the statistical certainty (and thus the reliability of your results), whether those results agree with experiment. they must agree with what the model represents. especially in the case of water, different models represent experiment different thermodynamical properties differently well compared to experiment, so it is quite possible that your "better" result is actually worse, i.e. if it agrees better with the experimental result for the wrong reason and that the "worse" result is in keeping with the model.

​please also keep in mind, that codes using floating point math will produce different trajectories due to floating point math being not associative, i.e. the order of operations has an impact on the exact (bitwise) result and then trajectories will be equivalent, but also diverging exponentially. this can happen with having different OS, hardware, number of parallel processes, code path (multi-thread vs. MPI vs. GPU)​. all of these differences should eventually converge to the same result, provided your trajectories contain a sufficiently representative subset of the total phase space (i.e. you have achieved ergodicity).

​so my recommendation is to reduce the degrees of freedom in what you are looking at and pick one version and determine what the statistical certainty (or relevance) of your results is and adapt your simulation time and other sampling parameters until you can say with confidence, that your numbers are sufficiently well converged.
only then, you can look into whether you find differences between different versions of LAMMPS or between different platforms (that means, your comparison of windows vs. linux is useless unless you have results of comparable and meaningful quality for both versions of LAMMPS on both platforms).
finally, you should hit the literature and research, if somebody has already done a similar study to identify the same thermodynamic properties for the same water models. it is more important to compare to those than to compare to experiment. comparison to experiment should only be done, after simulation results are confirmed beyond doubts. what you have told us so far, does not provide that level of confirmation.

axel.

 


On 14-09-2017 15:33, Wes Barnett wrote:


On Thu, Sep 14, 2017 at 7:49 AM, Emir Koçer <emirkocer92@...24...> wrote:

Hello again,
-on Windows 7 Enterprise we have lmp_mpi dated to 15 May 15, on Linux Debian we have lmp_mpi dated to the latest version (11 Aug 17)


There's a two year difference in those versions. Have you checked the change log to see if a bug related to these calculations has been fixed, changed have been made to the algorithm, etc?
 

- calculating thermal conductivity of pure water with TIP5P rigid model
- on Windows we get 0.63 W/mK with a std of 0.02-0.03, on Linux we get 0.85 W/mK with a std of 0.02-0.03 (experimental value is 0.60 W/mK )

It's hard to compare Windows vs. Linux if you are running two different versions of LAMMPS.
 

- sampling time is 20 ps and yes we can rule out them.
with another water models (TIP3P,etc.) which are not rigid, I get almost same results from both machines, so I've started to believe that there may be something different about the rigid algorithm of GK in two systems, but this is just my guess after checking everything.

TIP3P most certainly is a rigid water model unless you are specifying it not to be.
 



On 14-09-2017 14:35, Giacomo Fiorin wrote:
You need to copy the list on reply.  

On Sep 14, 2017 7:27 AM, "Emir Koçer" <emirkocer92@...24...> wrote:

Hello again,
-on Windows 7 Enterprise we have lmp_mpi dated to 15 May 15, on Linux Debian we have lmp_mpi dated to the latest version (11 Aug 17)
- calculating thermal conductivity of pure water with TIP5P rigid model
- on Windows we get 0.63 W/mK with a std of 0.02-0.03, on Linux we get 0.85 W/mK with a std of 0.02-0.03 (experimental value is 0.60 W/mK )
- sampling time is 20 ps and yes we can rule out them.
with another water models (TIP3P,etc.) which are not rigid, I get almost same results from both machines, so I've started to believe that there may be something different about the rigid algorithm of GK in two systems, but this is just my guess after checking everything.

Emir


On 12-09-2017 23:27, Giacomo Fiorin wrote:
You should provide some information:
- what are the exact versions of the Windows and Linux executables, and who compiled them?
- what are the dynamic properties you are computing with the Green-Kubo formalism?
- what are their computed values?
- what is the sampling time?
- can you safely rule out sampling errors?



On Tue, Sep 12, 2017 at 12:41 PM, Emir Koçer <emirkocer92@...92......> wrote:
Dear all,
I ran exactly same scripts on different machines (windows and linux).  Windows has one of the 2016 versions of LAMMPS and Linux has the latest version. Simulations are TIP5P pure water models with Green-Kubo algorithm (EMD). They have similar results when I run TIP3P models, but with TIP5P, Linux machine overestimates the experimental result, while Windows' results are in good agreement with the experiment. Both machines are operating properly and have no observable problems (We use them a lot in our research and this is the only type of simulation they disagree with each other).
Can somebody explain this situation ?

Emir


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Giacomo Fiorin
Associate Professor of Research, Temple University, Philadelphia, PA
Contractor, National Institutes of Health, Bethesda, MD




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James "Wes" Barnett
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Department of Chemical Engineering


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Dr. Axel Kohlmeyer  akohlmey@...24...  http://goo.gl/1wk0
College of Science & Technology, Temple University, Philadelphia PA, USA
International Centre for Theoretical Physics, Trieste. Italy.