TERRA SOFT SHOWCASE

Sandia National Lab*

In the spring of 2005, Terra Soft delivered a cluster to the Geochemistry Department of Sandia National Lab for use with LAMMPS based modeling. Trial benchmarks demonstrated the G5 Xserve to be superior in problem resolution given the following benchmark problem:
~5000+ atom box of period water, executed for one (1) nanosecond
Single AMD-242 CPU, 4GB RAM, using PCG161 hours
Single G5 CPU, 4GB RAM, using gcc 64130 hours
Single G5 CPU, 4GB RAM, using XLC 64104 hours

The physical construct of the systems is comprised of the following:
  • 18 x dual 2.0GHz G5 Xserve Cluster Nodes.
  • Gigabit ethernet internode communication fabric.
  • Yellow Dog Linux OS pre-installed.
  • Y-HPC cluster construction suite pre-installed.

  • A major theme at Sandia, and the primary focus of this team and their cluster is understanding the behavior of "interfacial water". This theme includes looking at (1) the structure of water at oxide-water interfaces and how this structure affects both the structure and energetics of cation- and anion- binding to these surfaces; (2) the structure of water trapped in pores within large crystal structures, like zeolite, and (3) the structure of water in nanoscale layers between mineral layers. Interest in this area is driven in part by the need to design membranes for waste water purification, design in situ remediation strategies for contaminated groundwater, and provide estimates for regulatory purposes.

    The clusters (both PC and Apple Xserve G5) provide the ability to perform large-scale (e.g., 10,000 atoms) molecular dynamics simulations for longer time periods (several nanoseconds). This allows for much better collection of statistical data from output trajectories for the interaction of water with a solid surface from MD simulations. It also allows for the possibility of performing more complex analysis of the MD results and opens the door to calculating free energies from molecular models. The clusters provides this lab the performance ability to address more complicated problems than before.

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