Article

Dynamic function placement for data-intensive cluster computing

Authors:

Gregory R. Ganger,

Garth A. GibsonAuthors Info & Claims

ATEC '00: Proceedings of the annual conference on USENIX Annual Technical Conference

Page 25

Published: 18 June 2000 Publication History

Abstract

Optimally partitioning application and filesystem functionality within a cluster of clients and servers is a difficult problem due to dynamic variations in application behavior, resource availability, and workload mixes. This paper presents ABACUS, a run-time system that monitors and dynamically changes function placement for applications that manipulate large data sets. Several examples of data-intensive workloads are used to show the importance of proper function placement and its dependence on dynamic run-time characteristics, with performance differences frequently reaching 2-10X. We evaluate how well the ABACUS prototype adapts to run-time system behavior, including both long-term variation (e.g., filter selectivity) and short-term variation (e.g., multi-phase applications and interapplication resource contention). Our experiments with ABACUS indicate that it is possible to adapt in all of these situations and that the adaptation converges most quickly in those cases where the performance impact is most significant.

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Index Terms

Dynamic function placement for data-intensive cluster computing
1. General and reference
  1. Cross-computing tools and techniques
    1. Performance
2. Software and its engineering

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ATEC '00: Proceedings of the annual conference on USENIX Annual Technical Conference

June 2000

704 pages

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USENIX Association

United States

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Published: 18 June 2000

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Tumanov AZhu TPark JKozuch MHarchol-Balter MGanger GCadar CPietzuch PKeeton KRodrigues R(2016)TetriSchedProceedings of the Eleventh European Conference on Computer Systems10.1145/2901318.2901355(1-16)Online publication date: 18-Apr-2016
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Ananthanarayanan GDouglas CRamakrishnan RRao SStoica ICarey MHand S(2012)True elasticity in multi-tenant data-intensive compute clustersProceedings of the Third ACM Symposium on Cloud Computing10.1145/2391229.2391253(1-7)Online publication date: 14-Oct-2012
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