Dear Sir/Madam,
I’ve recently contacted this forum for help with compatibility with airebo/intel and the latest version of lammps to which i appreciate the help for (successful - https://sourceforge.net/p/lammps/mailman/message/36516031/). I bring that up incase it is relevant - i’m unsure of its complete impact.
I’m contacting again as i ran two half a nano-second simulations through Hydra (HPC cluster), input script attached, of crystalline polyethylene (multiple chains in z-direction) of the exact same conditions (same velocity seed / etc).
The difference in the second simulation was using the intel acceleration package for airebo in the second run (i.e. change in pair_style) to output the heat flux (using EMD w/ the Green-Kubo approach). From there, my python post-processing script outputs close to zero (~ 0.25 W/mk - range expected of bulk polymers) thermal conductivity for the airebo/intel, in comparison to the airebo version of ~15 W/mk (more expected due to no defects/etc).
The heat flux values are significantly different between these two (ran for 100k steps in NVT prior) (top 50 values of each .txt files attached - file size is too big otherwise), but i naively assume that to be within the error of the acceleration package. This behaviour shown for lower time simulations too (100k steps of 0.25 fs). Either way, this near-zero result is strange to me as i believed that despite the algorithm changes to speed this process it is labelled to be reproducible with the same parallel configurations.
I investigated with the outputting the mean-square-displacement and airebo values. MSD shown minimal differences. Interestingly, the airebo/intel simulations didn’t yield the airebo parameters (rebo, lj and torsional) - i’m not sure if this is intentional or not.
Also, the mean of the flux values columns for airebo were: {X: -0.92037, Y: -0.31219, Z: 6.57244} and airebo/intel: {X: 0.03045, Y: -0.31928, Z: -0.28367}. The averages of the flux values in their columns explains that airebo/intel oscillates around zero very closely.
I’m slowly learning about this field and would appreciate any thoughts on this matter. Let me know if any other information/files are needed for the full picture.
Kind regards,
Ben
Other potentially related information:
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the Hydra server i used has the following capabilities - ‘34 nodes (hydra152 to 185) with dual Intel Xeon CPU E5-2680 v2 at 2.80GHz 10 core processors (20 CPU cores per node) and 64GB RAM.’
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just in case someone is curious about the small lammps replication command (assuming they thought it’s just a single cell) - this is because the random.data is already with the positions of a crystalline polyethylene (learning python through this) - lammps runs w/ 15360 atoms. (960 * 2 * 2 * 4)
top50_aireboIntHflux.txt (2.71 KB)
top50_aireboHflux.txt (2.7 KB)
in.kappa (1.72 KB)