Abstract
We examine the performance of the molecular dynamics code Parallacs and the time-domain (TD) codes in the General ElectroMagnetic Solvers (GEMS) code suite for a 32 CPUs IBM 1.1 GHz pwr4 node. Parallacs is an easily portable molecular dynamics (MD) benchmark code, which contains most features found in current general-purpose production MD codes. Timings and scaling behavior up to 16 CPUs is reported.
The GEMS TD codes give the expected performance. For large problems, they are three to four times faster on a 1.1 GHz pwr4 node than on a 375 MHz pwr3 node.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
U. Andersson. Parallelization of a 3D FD-TD code for the Maxwell equations using MPI. In B. Kågström et al., editors, Applied Parallel Computing, PARA’98, Lecture Notes in Computer Science, No. 1541, pages 12–19, June 1998.
Ulf Andersson and Gunnar Ledfelt. Large scale FD-TD—A billion cells. In 15th Annual Review of Progress in Applied Computational Electromagnetics, volume 1, pages 572–577, Monterey, CA, March 1999.
Fredrik Edelvik and Gunnar Ledfelt. A comparison of time-domain hybrid solvers for complex scattering problems. International Journal of Numerical Modeling, 15(5), September/October 2002.
Florian Müller-Plathe, Walter Scott, and Wilfred F. van Gunsteren. PARALLACS: a benchmark for parallel molecular dynamics. Computer Physics Communications, 84:102–114, 1994.
PSCI. Parallel and Scientific Computing Institute. http://www.psci.kth.se/ , 2002.
A. Taflove. Computational Electrodynamics: The Finite-Difference Time-Domain Method. Artech House, Boston, MA, second edition, 2000.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2002 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Andersson, U., Hedman, F. (2002). Performance of an IBM Pwr4 Node for the GEMS TD Codes and Parallacs. In: Fagerholm, J., Haataja, J., Järvinen, J., Lyly, M., Råback, P., Savolainen, V. (eds) Applied Parallel Computing. PARA 2002. Lecture Notes in Computer Science, vol 2367. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48051-X_46
Download citation
DOI: https://doi.org/10.1007/3-540-48051-X_46
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-43786-4
Online ISBN: 978-3-540-48051-8
eBook Packages: Springer Book Archive