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The Cactus Worm: Experiments with Dynamic Resource Discovery and Allocation in a Grid Enviroment

MPG-Autoren

Allen,  Gabrielle
Cactus Group, AEI-Golm, MPI for Gravitational Physics, Max Planck Society;

Lanfermann,  Gerd
Cactus Group, AEI-Golm, MPI for Gravitational Physics, Max Planck Society;

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Radke,  Thomas
Astrophysical Relativity, AEI-Golm, MPI for Gravitational Physics, Max Planck Society;

Seidel,  Edward
Cactus Group, AEI-Golm, MPI for Gravitational Physics, Max Planck Society;

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Zitation

Allen, G., Angulo, D., Foster, I., Lanfermann, G., Liu, C., Radke, T., et al. (2001). The Cactus Worm: Experiments with Dynamic Resource Discovery and Allocation in a Grid Enviroment. International Journal of High Performance Computing Applications, 15(4), 345-358.


Zitierlink: https://hdl.handle.net/11858/00-001M-0000-0013-56C1-A
Zusammenfassung
The ability to harness heterogeneous, dynamically available grid resources, is attractive to typically resource-starved computational scientists and engineers, as in principle it can increase, by significant factors, the number of cycles that can be delivered to applications. However, new adaptive application structures and dynamic runtime system mechanisms are required if we are to operate effectively in grid environments. To explore some of these issues in a practical setting, the authors are developing an experimental framework, called Cactus, that incorporates both adaptive application structures for dealing with changing resource characteristics and adaptive resource selection mechanisms that allow applications to change their resource allocations (e.g., via migration) when performance falls outside specified limits. The authors describe the adaptive resource selection mechanisms and describe how they are used to achieve automatic application migration to "better" resources following performance degradation. The results provide insights into the architectural structures required to support adaptive resource selection. In addition, the authors suggest that the Cactus Worm affords many opportunities for grid computing.