Resiliency in Exascale Systems and Computations Using Chaotic-Identity Maps

Nageswara S. V. Rao²⁷

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7640))

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European Conference on Parallel Processing

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Abstract

For exascale computing systems, we propose (i) light-weight computational modules that utilize chaotic computations and customized identity maps to detect component failures, and (ii) statistical estimation methods that generate robustness estimates for the system and computations based on the module outputs. The diagnosis modules execute multiple Poincare and identity maps, which are customized to detect certain classes of failures in the compute nodes and interconnects. We propose statistical methods that generate robustness estimates for the system using the outputs of pipelined chains of diagnosis modules.

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References

Alligood, K.T., Sauer, T.D., Yorke, J.A.: Chaos: An Introduction to Dynamical Systems. Springer-Verlag Pub., Reading (1996)
MATH Google Scholar
International exascale software project, http://www.exascale.org
Rao, N.S.V.: Computational complexity issues in operative diagnosis of graph-based systems. IEEE Transactions on Computers 42(4), 447–457 (1993)
Article Google Scholar
Rao, N.S.V.: Chaotic-Identity Maps for Robustness Estimation of Exascale Computations. In: IEEE Workshop on Fault Tolerance for HPC at Extreme Scale (2012)
Google Scholar
Vapnik, V.N.: Statistical Learning Theory. John-Wiley and Sons, New York (1998)
MATH Google Scholar
von Neumann, J.: Probabilistic logics and the synthesis of reliable organisms from unreliable components. In: Shannon, C.E., MaCarthy, J. (eds.) Automata Studies. Princeton University Press (1956)
Google Scholar

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Oak Ridge National Laboratory, Oak Ridge, TN, 37831, USA
Nageswara S. V. Rao

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Nageswara S. V. Rao
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Computer Technology Institute and Press “Diophantus” & Department of Computer Engineering and Informatics, University of Patras, 26504, Rio, Greece
Ioannis Caragiannis
Technische Universität Wien, Austria
Michael Alexander
Artificial Intelligence Research Institute (IIIA), Spanish National Research Council (CSIC), Spain
Rosa Maria Badia
Department of Medical and Surgical Sciences, Bioinformatics Laboratory, University Magna Græcia of Catanzaro, 88100, Catanzaro, Italy
Mario Cannataro
Inria Rennes, France
Alexandru Costan
Dept. Computer Science, Univ. Pisa, Largo Pontecorvo 3, 56127, Pisa, Italy
Marco Danelutto
Inria, 46 Allée d’Italie, 69364, Lyon Cedex 7, France
Frédéric Desprez
Université de Versailles, France
Bettina Krammer
Department of Computer Engineering (DISCA), Universitat Politècnica de València, Spain
Julio Sahuquillo
Oak Ridge National Laboratory, USA
Stephen L. Scott
Technische Universität München, Germany
Josef Weidendorfer

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Rao, N.S.V. (2013). Resiliency in Exascale Systems and Computations Using Chaotic-Identity Maps. In: Caragiannis, I., et al. Euro-Par 2012: Parallel Processing Workshops. Euro-Par 2012. Lecture Notes in Computer Science, vol 7640. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36949-0_55

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DOI: https://doi.org/10.1007/978-3-642-36949-0_55
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-36948-3
Online ISBN: 978-3-642-36949-0
eBook Packages: Computer ScienceComputer Science (R0)

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