The Grid2003 production grid: principles and practice

Ian Foster(Argonne National Laboratory), J. Gieraltowski(Argonne National Laboratory), S. Gose(Argonne National Laboratory), Natalia Maltsev(Argonne National Laboratory), E.N. May(Argonne National Laboratory), Álex Rodríguez(Argonne National Laboratory), Dinanath Sulakhe(Argonne National Laboratory), A. Vaniachine(Argonne National Laboratory), J.T. Shank(Boston University), S. Youssef(Boston University), D. L. Adams(Brookhaven College), Richard S. Baker(Brookhaven College), Wei Deng(Brookhaven College), Jazz Mack Smith(Brookhaven College), Yu Dai(Brookhaven College), I. Legrand(California Institute of Technology), Sarbjeet Singh(California Institute of Technology), Conrad Steenberg(California Institute of Technology), Yang Xia(California Institute of Technology), Anzar Afaq, E. Berman, J. Annis, L. A. T. Bauerdick, Michael D. Ernst, I. Fisk, L. Giacchetti, G. Graham, A. Heavey, Johannes W. Kaiser, N. Kuropatkin, R. Pordes, V. Sekhri, J. Weigand, Y. Wu, Keith Baker(Hampton University), Lawrence Sorrillo(Hampton University), J. Huth(Harvard University Press), Matthew S. Allen(Indiana University Bloomington), L. Grundhoefer(Indiana University Bloomington), John Hicks(Indiana University Bloomington), F. Luehring(Indiana University Bloomington), Sarah A. Peck Justice(Indiana University Bloomington), Rob Quick(Indiana University Bloomington), Stephen Simms(Indiana University Bloomington), György Fekete(Johns Hopkins University), Jan Vandenberg(Johns Hopkins University), K. Cho, K. Kwon, D. C. Son, H. Park, Shane Canon(Lawrence Berkeley National Laboratory), Keith Jackson(Lawrence Berkeley National Laboratory), David E. Konerding(Lawrence Berkeley National Laboratory), Jason Lee(Lawrence Berkeley National Laboratory), D. Olson(Lawrence Berkeley National Laboratory), I. Sakrejda(Lawrence Berkeley National Laboratory), Brian Tierney(Lawrence Berkeley National Laboratory), M. Green, Russ Miller, J Letts, T. A. Martin, D. Bury(University of Chicago), Cătălin Dumitrescu(University of Chicago), D. Engh(University of Chicago), R. W. Gardner(University of Chicago), Marco Mambelli(University of Chicago), Y. Smirnov(University of Chicago), Jens Voeckler(University of Chicago), Michael Wilde(University of Chicago), Yong Zhao(University of Chicago), Xin Zhao(University of Chicago), P. Avery, R. Cavanaugh, B. Kim, C. Prescott, J. L. Rodriguez, Aljoscha Zahn, S. P. Mc Kee(University of Michigan), Chris Jordan, Jim Prewett, T. L. Thomas, H. Severini, Ben Clifford, Ewa Deelman, L. Flon, Carl Kesselman, Gaurang Mehta, N. Olomu, Karan Vahi, K. De, Patrick J McGuigan, M. Sosebee, D Bradley(University of Wisconsin–Madison), P. Couvares(University of Wisconsin–Madison), Arthur De Smet(University of Wisconsin–Madison), C. Kireyev(University of Wisconsin–Madison), E K Paulson(University of Wisconsin–Madison), A. Roy(University of Wisconsin–Madison), Scott Koranda, B. Moe, Benjamin P. Brown(Vanderbilt University), Paul Sheldon(Vanderbilt University)
High Performance Distributed Computing
June 4, 2004
10.1109/hpdc.2004.36
Cited by 121

Abstract

The Grid2003 Project has deployed a multivirtual organization, application-driven grid laboratory (Grid3) that has sustained for several months the production-level services required by physics experiments of the Large Hadron Collider at CERN (ATLAS and CMS), the Sloan Digital Sky Survey project, the gravitational wave search experiment LIGO, the BTeV experiment at Fermilab, as well as applications in molecular structure analysis and genome analysis, and computer science research projects in such areas as job and data scheduling. The deployed infrastructure has been operating since November 2003 with 27 sites, a peak of 2800 processors, work loads from 10 different applications exceeding 1300 simultaneous jobs, and data transfers among sites of greater than 2 TB/day. We describe the principles that have guided the development of this unique infrastructure and the practical experiences that have resulted from its creation and use. We discuss application requirements for grid services deployment and configuration, monitoring infrastructure, application performance, metrics, and operational experiences. We also summarize lessons learned.

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