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K-means in space: a radiation sensitivity evaluation

Published:14 June 2009Publication History

ABSTRACT

Spacecraft increasingly employ onboard data analysis to inform further data collection and prioritization decisions. However, many spacecraft operate in high-radiation environments in which the reliability of dataintensive computation is not known. This paper presents the first study of radiation sensitivity for k-means clustering. Our key findings are 1) k-means data structures differ in sensitivity, which is not determined solely by the amount of memory exposed; 2) no special radiation protection is needed below a data-set-dependent radiation threshold, enabling the use of faster, smaller, and cheaper onboard memory; and 3) subsampling improves radiation tolerance slightly, but the use of kd-trees unfortunately reduces tolerance. Our conclusions can help tailor k-means for use in future high-radiation environments.

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          cover image ACM Other conferences
          ICML '09: Proceedings of the 26th Annual International Conference on Machine Learning
          June 2009
          1331 pages
          ISBN:9781605585161
          DOI:10.1145/1553374

          Copyright © 2009 Copyright 2009 by the author(s)/owner(s).

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          Association for Computing Machinery

          New York, NY, United States

          Publication History

          • Published: 14 June 2009

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