Dynamic Resizing of Parallel Scientific Simulations: A Case Study Using LAMMPS

Authors:
Rajesh Sudarsan;Calvin J. Ribbens;Diana Farkas
Affiliations:
Department of Computer Science, Virginia Tech, Blacksburg, VA 24060;Department of Computer Science, Virginia Tech, Blacksburg, VA 24060;Department of Materials Science and Engineering, Virginia Tech, Blacksburg, VA 24061
Venue:
ICCS '09 Proceedings of the 9th International Conference on Computational Science: Part I
Year:
2009

Citing 8
Cited 0

Fast parallel algorithms for short-range molecular dynamics

Journal of Computational Physics
Dynamic resource management on distributed systems using reconfigurable applications

IBM Journal of Research and Development - Special issue: performance analysis and its impact on design
Using moldability to improve the performance of supercomputer jobs

Journal of Parallel and Distributed Computing
A framework for adaptive execution in grids

Software—Practice & Experience
ReSHAPE: A Framework for Dynamic Resizing and Scheduling of Homogeneous Applications in a Parallel Environment

ICPP '07 Proceedings of the 2007 International Conference on Parallel Processing
Scheduling malleable applications in multicluster systems

CLUSTER '07 Proceedings of the 2007 IEEE International Conference on Cluster Computing
Scheduling resizable parallel applications

IPDPS '09 Proceedings of the 2009 IEEE International Symposium on Parallel&Distributed Processing
Efficient multidimensional data redistribution for resizable parallel computations

ISPA'07 Proceedings of the 5th international conference on Parallel and Distributed Processing and Applications

Quantified Score

Hi-index	0.00

Visualization

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.