Introduction One of the great features of LAMMPS is that it can run on single processors or in parallel using message-passing techniques and a spatial-decomposition of the simulation domain. As it’s named acronym implies, Large-scale Atomic/Molecular Massively Parallel Simulator is well suited for parallelization in the cloud, and this article will review ways to optimize those simulations. This can work equally well for Molecular Dynamics and Materials Sciences simulations. Background/Problem Statement (Boundary 3 - x, y, z) If you were to take one of the example input files from the LAMMPS installation directory, you can run the simulations in a few seconds or minutes on a local or cloud machine.

Data sets for investigation and research can be critical and need to be kept around for at least the life of a research project, but possibly much longer based on data retention policies. Google Cloud Storages (GCS) is object storage that is resilient and easy to use and scale. GCS has such features as: *>*9.99% availability for standard, and *>*99.95% for other storage classes Multiple storage classes (Standard, Nearline, Coldline, and Archive) which can be managed automatically based on access frequency or time.