Abstract
The possibility of having available massive computer resources to users opens ideas for the future of interoperability between multiple infrastructure systems. This wide system should be composed of multiple high performance resource clusters and their users should share them to solve big scientific problems. These resources have a dynamic behavior and to reach the expected performance indexes it is necessary to tune the application in an automatic and dynamic way. The MATE environment was designed to tune parallel applications running on a cluster. This paper presents the key ideas for tracking down application process in a wide distributed environment like Computational Grids. We explain how to enable the use of MATE for dynamic application optimizations in such systems.
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This work has been supported by the MCyT (Spain) under contract TIN 2004-03388.
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References
Foster, I., Kesselman, C.: The Grid 2: Blueprint for a New Computing Infrastructure. Morgan Kauffman, San Francisco (2003)
Frey, J., Tannenbaum, T., Foster, I., Livny, M., Tuecke, S.: Condor-G: A Computation Management Agent for Multi-Institutional Grids. In: Cluster Computing, vol. 5, pp. 237–246. Springer, Netherlands (2002)
Portable Batch System Administrator Guide. Veridian Information Solutions, Inc.: Veridian Systems PBS Products Dept. 2672 Bayshore Parkway, Suite 810 Mountain View, CA 94043 (2000)
Czajkowski, K., Fitzgerald, S., Foster, I., Kesselman, C.: Grid information services for distributed resource sharing. In: Proceedings. 10th IEEE International Symposium on, High Performance Distributed Computing 2001, pp. 181–194 (2001)
Foster, I.T., Kesselman, C., Tuecke, S.: The Anatomy of the Grid - Enabling Scalable Virtual Organizations. International Journal of High Performance Computing 15, 200 (2001)
Morajko, A., Morajko, O., Margalef, T., Luque, E.: MATE: Dynamic Performance Tuning Environment. In: Danelutto, M., Vanneschi, M., Laforenza, D. (eds.) Euro-Par 2004. LNCS, vol. 3149, pp. 98–107. Springer, Heidelberg (2004)
Foster, I., Kesselman, C., Nick, J.M., Tuecke, S.: The Physiology of the Grid, pp. 217–249 (2003)
Gerndt, M., Wismuuller, R., Balaton, Z., Gombás, G., Kacsuk, P., Námeth, Z., Podhorszki, N., Truong, H.-L., Fahringer, T., Bubak, M., Laure, E., Margalef, T.: Performance Tools for the Grid: State of the Art and Future. APART White Paper (2004)
Zanikolas, S., Sakellariou, R.: A taxonomy of grid monitoring systems. Future Generation Computer Systems 21, 163–188 (2005)
Shende, S.S., Malony, A.D.: The Tau Parallel Performance System. International Journal of High Performance Computing Applications 20, 287–311 (2006)
Truong, H.-L.: Novel Techniques and Methods for Performance Measurement, Analysis and Monitoring of Cluster and Grid Applications. University of Innsbruck (2005)
Miller, B.P., Callaghan, M.D., Cargille, J.M., Hollingsworth, J.K., Irvin, R.B., Karavanic, K.L., Kunchithapadam, K., Newhall, T.: The Paradyn parallel performance measurement tool. Computer 28, 37–46 (1995)
Miller, B., Cortes, A., Senar, M.A., Livny, M.: The Tool Dæmon Protocol (TDP). IEEE Computer Society, Washington (2003)
Hollingsworth, J.K., Keleher, P.J.: Prediction and adaptation in Active Harmony. Cluster Computing 2, 195–205 (1999)
Buck, B., Hollingsworth, J.K.: An API for Runtime Code Patching. Journal of High Performance Computing Applications (2000)
Morajko, A.: Dynamic Tuning of Parallel/Distributed Applications. vol. Phd. Universitat Autonoma de Barcelona (2004)
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Costa, G., Morajko, A., Margalef, T., Luque, E. (2007). Automatic Tuning in Computational Grids. In: Kågström, B., Elmroth, E., Dongarra, J., Waśniewski, J. (eds) Applied Parallel Computing. State of the Art in Scientific Computing. PARA 2006. Lecture Notes in Computer Science, vol 4699. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75755-9_47
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DOI: https://doi.org/10.1007/978-3-540-75755-9_47
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