011 IEEE International Parallel & Distributed Processing Symposium
Cyberinfrastructure Usage Modalities on the TeraGrid
Daniel S. Katz David Hart Computational Institute Computational & Information Systems Laboratory University of Chicago & Argonne National Laboratory National Center for Atmospheric Research Chicago, USA Boulder, USA [email protected] [email protected]
Chris Jordan Amit Majumdar Texas Advanced Computing Center San Diego Supercomputer Center University of Texas Austin University of California San Diego Austin, USA San Diego, USA [email protected] [email protected]
J.P. Navarro Warren Smith Computational Institute Texas Advanced Computing Center Argonne National Laboratory & University of Chicago University of Texas Austin Chicago, USA Austin, USA [email protected] [email protected]
John Towns Von Welch National Center for Supercomputing Applications Indiana University University of Illinois Bloomington, IN Urbana, USA [email protected] [email protected]
Nancy Wilkins-Diehr San Diego Supercomputer Center U. of California San Diego San Diego, USA [email protected]
Abstract—This paper is intended to explain how the TeraGrid storage, and specialized computing systems. These would like to be able to measure “usage modalities.” We would combinations of integrated resources make possible a variety like to (and are beginning to) measure these modalities to of user and usage scenarios. To better support our user understand what objectives our users are pursuing, how they community, TeraGrid wants to understand how users are go about achieving them, and why, so that we can make actually using these resources to achieve their scientific changes in the TeraGrid to better support them. objectives, so that we can make changes in the TeraGrid environment to improve operations and services. Because Keywords-component; production grid infrastructure; TeraGrid will be transitioning into a new project (eXtreme cyberinfrastructure Digital, or XD) in mid-2011, much of this data gathering will be given to the new project and can be used in planning its I. INTRODUCTION growth. The TeraGrid represents one of an emerging class of A great deal of attention has gone into the study of HPC entities that can be referred to as “production workloads, with the goals of improving scheduler cyberinfrastructures.” These cyberinfrastructures, which also performance and maximizing resource utilization. A study of include the Open Science Grid in the US, DEISA and EGI in the TeraGrid’s workload patterns shows that, in many ways, Europe, and RENKEI in Japan, harness distributed the TeraGrid’s HPC resources demonstrate many of these resources, including high-performance computing (HPC), same patterns, both on individual systems and across the federation [1].