Abstract
The work we present in this paper focuses on dynamic provisioning of computational resources depending on the performance requirements of the application and the characteristics of the cluster available for execution. We target applications which exhibit variable performance over time. The idea is to dynamically optimize the cost (total CPU-time) / performance (program execution time) ratio of parallel applications by (1) reducing the number of processors when the computation requirements decrease enough to justify it, and (2) moving computation onto those processors that can compute faster but don’t require extensive remapping of the data. This approach adapts well to time-shared platforms in which many applications may need to execute on the same cluster at the same time, and allows users to implement different cost / performance tradeoffs.
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Martín, G., Singh, D.E., Marinescu, MC., Carretero, J. (2012). Runtime Support for Adaptive Resource Provisioning in MPI Applications. In: Träff, J.L., Benkner, S., Dongarra, J.J. (eds) Recent Advances in the Message Passing Interface. EuroMPI 2012. Lecture Notes in Computer Science, vol 7490. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33518-1_38
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DOI: https://doi.org/10.1007/978-3-642-33518-1_38
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33517-4
Online ISBN: 978-3-642-33518-1
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