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.
This work has been supported by the MCyT (Spain) under contract TIN 2004-03388.
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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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