Abstract

Scientific workflows are a common computational model for performing scientific simulations. They may include many jobs, many scientific codes, and many file dependencies. Since scientific workflow applications may include both high-performance computing (HPC) and high-throughput computing (HTC) jobs, meaningful performance metrics are difficult to define, as neither traditional HPC metrics nor HTC metrics fully capture the extent of the application. We describe and propose the use of alternative metrics to accurately capture the scale of scientific workflows and quantify their efficiency. In this paper, we present several specific practical scientific workflow performance metrics and discuss these metrics in the context of a large-scale scientific workflow application, the Southern California Earthquake Center CyberShake 1.0 Map calculation. Our metrics reflect both computational performance, such as floating …

Date

January 1, 1970

Authors

Scott Callaghan, Philip Maechling, Patrick Small, Kevin Milner, Gideon Juve, Thomas H Jordan, Ewa Deelman, Gaurang Mehta, Karan Vahi, Dan Gunter, Keith Beattie, Christopher Brooks

Journal

The International Journal of High Performance Computing Applications

Volume

25

Issue

3

Pages

274-285

Publisher

SAGE Publications