Dynamic resizing of parallel scientific simulations: A case study using lammps

Abstract

Large-scale computational science simulations are a dominant component of the workload on modern supercomputers. Efficient use of high-end resources for these large computations is of considerable scientific and economic importance. However, conventional job schedulers limit flexibility in that they are 'static', i.e., the number of processors allocated to an application can not be changed at runtime. In earlier work, we described ReSHAPE, a system that eliminates this drawback by supporting dynamic resizability in distributed-memory parallel applications. The goal of this paper is to present a case study highlighting the steps involved in adapting a production scientific simulation code to take advantage of ReSHAPE. LAMMPS, a widely used molecular dynamics code, is the test case. Minor extensions to LAMMPS allow it to be resized using ReSHAPE, and experimental results show that resizing significantly improves overall system utilization as well as performance of an individual LAMMPS job. © 2009 Springer Berlin Heidelberg.