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dc.contributor.authorKhayyat, Zuhair*
dc.contributor.authorAwara, Karim*
dc.contributor.authorAlOnazi, Amani A.*
dc.contributor.authorJamjoom, Hani T.*
dc.contributor.authorWilliams, Daniel W.*
dc.contributor.authorKalnis, Panos*
dc.date.accessioned2015-08-04T07:10:51Zen
dc.date.available2015-08-04T07:10:51Zen
dc.date.issued2013en
dc.identifier.isbn9781450319942en
dc.identifier.doi10.1145/2465351.2465369en
dc.identifier.urihttp://hdl.handle.net/10754/564648en
dc.description.abstractPregel [23] was recently introduced as a scalable graph mining system that can provide significant performance improvements over traditional MapReduce implementations. Existing implementations focus primarily on graph partitioning as a preprocessing step to balance computation across compute nodes. In this paper, we examine the runtime characteristics of a Pregel system. We show that graph partitioning alone is insufficient for minimizing end-to-end computation. Especially where data is very large or the runtime behavior of the algorithm is unknown, an adaptive approach is needed. To this end, we introduce Mizan, a Pregel system that achieves efficient load balancing to better adapt to changes in computing needs. Unlike known implementations of Pregel, Mizan does not assume any a priori knowledge of the structure of the graph or behavior of the algorithm. Instead, it monitors the runtime characteristics of the system. Mizan then performs efficient fine-grained vertex migration to balance computation and communication. We have fully implemented Mizan; using extensive evaluation we show that - especially for highly-dynamic workloads - Mizan provides up to 84% improvement over techniques leveraging static graph pre-partitioning. © 2013 ACM.en
dc.publisherAssociation for Computing Machinery (ACM)en
dc.titleMizan: A system for dynamic load balancing in large-scale graph processingen
dc.typeConference Paperen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division*
dc.contributor.departmentComputer Science Program*
dc.identifier.journalProceedings of the 8th ACM European Conference on Computer Systems - EuroSys '13en
dc.conference.date15 April 2013 through 17 April 2013en
dc.conference.name8th ACM European Conference on Computer Systems, EuroSys 2013en
dc.conference.locationPragueen
dc.contributor.institutionIBM T. J. Watson Research Center, Yorktown Heights, NY, United States*
kaust.authorAlOnazi, Amani A.*
kaust.authorKalnis, Panos*
kaust.authorKhayyat, Zuhair*
kaust.authorAwara, Karim*


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