Abstract
This paper presents the design, prototype implementation, and evaluation of a runtime management framework for structured adaptive mesh refinement applications. The framework is capable of reactively and proactively managing and optimizing application execution using current system and application state, predictive models for system behavior and application performance, and an agent based control network. The overall goal of this research is to enable large-scale dynamically adaptive scientific and engineering simulations on distributed, heterogeneous and dynamic execution environments such as the computational “grid”.
Support for this work was provided by the NSF via grants numbers ACI 9984357 (CAREERS), EIA 0103674 (NGS) and EIA-0120934 (ITR), DOE ASCI/ASAP (Caltech) via grant number PC295251, and the DOE Scientific Discovery through Advanced Computing (SciDAC) program via grant number DE-FC02-01ER41184.
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© 2002 Springer-Verlag Berlin Heidelberg
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Chandra, S., Sinha, S., Parashar, M., Zhang, Y., Yang, J., Hariri, S. (2002). Adaptive Runtime Management of SAMR Applications. In: Sahni, S., Prasanna, V.K., Shukla, U. (eds) High Performance Computing — HiPC 2002. HiPC 2002. Lecture Notes in Computer Science, vol 2552. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36265-7_53
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DOI: https://doi.org/10.1007/3-540-36265-7_53
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