Abstract
Global heterogeneous computing, often referred to as “the Grid” [5, 6], is a popular emerging computing model in which high performance computers linked by high-speed networks are used to solve technical problems that cannot be solved on any single machine. The vision for Grid computing is that these interconnected computers form a global distributed problem-solving system, much as the Internet has become a global information system. However, to achieve this vision for a broad community of scientists and engineers, we will need to build software tools that make the job of constructing Grid programs easy. This is the principle goal of the Virtual Grid Application Development Software (VGrADS) Project, an NSF-supported effort involving 11 principal investigators at 7 institutions: Rice, Houston, North Carolina, Tennessee, UCSB, UCSD, and USC Information Sciences Institute.
Please use the following format when citing this chapter: Kennedy, K., 2007, in IFIP International Federation for Information Processing, Volume 239, Grid-Based Problem Solving Environments, eds. Gaffney. P. W., Pool, J.C.T., (Boston: Springer), pp. 19–29.
Chapter PDF
Similar content being viewed by others
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
C. H. Bischof, P. Khademi, A. Mauer, and A. Carle. ADIFOR 2.0 — sautomatic differentiation of Fortran 77 programs. IEEE Computational Science and Engineering, 3(3): 18–32, 1996.
J. Blythe, S. Jain, E. Deelman, Y. Gil, K. Vahi, A. Mandai, and K. Kennedy. Task scheduling strategies for workflow-based applications in grids. In IEEE International Symposium on Cluster Computing and the Grid (CCGrid (2005)). IEEE Press, 2005.
J. Brevik, D. Nurmi, and R. Wolski. Predicting bounds on queuing delay for batch-scheduled parallel machines. In Proceedings of PPoPP (2006), March 2006.
I. Foster and C. Kesselman. Globus: A metacomputing infrastructure toolkit. International Journal of Supercomputer Applications, 1997.
I. Foster and C. Kesselman. The Grid: Blueprint for a New Computing Infrastructure. Morgan Kaufmann Publishers, Inc., 1999.
I. Foster and C. Kesselman. The Grid 2. Morgan Kaufmann Publishers, Inc., 2003.
Y.-S. Kee, D. Logothetis, R. Huang, H. Casanova, and A. Chien. Efficient resource description and high quality selection for virtual grids. In Proceedings of the 5th IEEE Symposium on Cluster Computing and the Grid (GGGrid’05), Cardiff, U.K., May 2005.
S. Ludtke, P. Baldwin, and W. Chiu. EMAN: Semiautomated software for high resolution single-particle reconstructions. J. Struct. Biol, (128): 82–97, 1999.
A. Mandai, K. Kennedy, C. Koelbel, G. Marin, J. Mellor-Crummey, B. Liu, and L. Johnsson. Scheduling strategies for mapping application workflows onto the grid. In 14-th IEEE Symposium on High Performance Distributed Computing (HPDC14), pages 125–134, 2005.
Gabriel Marin and John Mellor-Crummey. Cross architecture performance predictions for scientific applications using parameterized models. In Proceedings of the Joint International Conference on Measurement and Modeling of Computer Systems, June 2004.
Gabriel Marin and John Mellor-Crummey. Scalable cross-architecture predictions of memory hierarchy response for scientific applications. In Proceedings of the Los Alamos Computer Science Institute Sixth Annual Symposium, Santa Fe, NM, October 2005.
M. Mika, G. Waligora, and J. Weglarz. Grid Resource Management: State of the Art and Future Trends. Kluwer Academic Publishers, 2003.
Daniel Nurmi, Anirban Mandai, John Brevik, Rich Wolski, Charles Koelbel, and Ken Kennedy. Evaluation of a workflow scheduler using integrated performance modelling and batch queue wait time prediction. In Proceedings of SC’06, Tampa, FL, November 2006.
R. Wolski. Dynamically forecasting network performance to support dynamic scheduling using the network weather service. In Proceedings 6th IEEE Symposium on High Performance Distributed Computing, August 1997.
Yang Zhang, Anirban Mandai, Henri Casanova, Andrew Chien, Yang-Suk Kee, Ken Kennedy, and Charles Koelbel. Scalable Grid application scheduling via decoupled resource selection and scheduling. In Proceedings of the 6th IEEE Symposium on Cluster Computing and the Grid (CCGrid’06), May 2006.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2007 International Federation for Information Processing
About this paper
Cite this paper
Kennedy, K. (2007). Why Performance Models Matter for Grid Computing. In: Gaffney, P.W., Pool, J.C.T. (eds) Grid-Based Problem Solving Environments. IFIP The International Federation for Information Processing, vol 239. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-73659-4_2
Download citation
DOI: https://doi.org/10.1007/978-0-387-73659-4_2
Publisher Name: Springer, Boston, MA
Print ISBN: 978-0-387-73658-7
Online ISBN: 978-0-387-73659-4
eBook Packages: Computer ScienceComputer Science (R0)