Progress Towards Petascale Applications in Biology: Status in 2006

Abstract

Petascale computing is currently a common topic of discussion in the high performance computing community. Biological applications, particularly protein folding, are often given as examples of the need for petascale computing. There are at present biological applications that scale to execution rates of approximately 55 teraflops on a special-purpose supercomputer and 2.2 teraflops on a general-purpose supercomputer. In comparison, Qbox, a molecular dynamics code used to model metals, has an achieved performance of 207.3 teraflops. It may be useful to increase the extent to which operation rates and total calculations are reported in discussion of biological applications, and use total operations (integer and floating point combined) rather than (or in addition to) floating point operations as the unit of measure. Increased reporting of such metrics will enable better tracking of progress as the research community strives for the insights that will be enabled by petascale computing.This research was supported in part by the Indiana Genomics Initiative and the Indiana Metabolomics and Cytomics Initiative. The Indiana Genomics Initiative of Indiana University and the Indiana Metabolomics and Cytomics Initiative of Indiana University are supported in part by Lilly Endowment, Inc. The authors also wish to thank IBM, Inc. for support via Shared University Research Grants and partnerships via IU’s relationship as an IBM Life Sciences Institute of Innovation. Indiana University also thanks the TeraGrid partners; IU’s participation in the TeraGrid is funded by National Science Foundation grant numbers 0338618, 0504075, and 0451237. The early development of this paper was supported by a Fulbright Senior Scholars award from the Council for International Exchange of Scholars (CIES) and the United States Department of State to Dr. Craig A. Stewart; Matthias Mueller and the Technische Universität Dresden were hosts. Many reviewers contributed to the improvement of the ideas expressed in this paper and are gratefully appreciated; Thom Dunning, Robert Germain, Chris Mueller, Jim Phillips, Richard Repasky, Ralph Roskies, and Allan Snavely are thanked particularly for their insights

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