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Computing, Networking, Storage and Analysis
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SCHEDULE: NOV 15-20, 2015

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Multi-Objective Job Placement in Clusters

SESSION: Resource Management


EVENT TAG(S): System Software, Resource Management

TIME: 11:30AM - 12:00PM


AUTHOR(S):Sergey Blagodurov, Alexandra Fedorova, Evgeny Vinnik, Tyler Dwyer, Fabien Hermenier



One of the key decisions made by both MapReduce and HPC cluster management frameworks, is the placement of jobs within a cluster. To make this decision they consider factors like resource constraints within a node or the proximity of data to a process. However, they fail to account for the degree of collocation on the cluster’s nodes. A tight process placement can create contention for the intra-node shared resources, such as shared caches, memory, disk or network bandwidth. A loose placement would create less contention, but exacerbate network delays and increase cluster-wide power consumption. Finding the best job placement is challenging, because among many possible placements, we need to find one that gives us an acceptable trade-off between performance and power consumption. We propose to tackle the problem via multi-objective optimization. Our solution is able to balance conflicting objectives specified by the user and efficiently find a suitable job placement.

Chair/Author Details:

Kim Cupps (Chair) - Lawrence Livermore National Laboratory|

Sergey Blagodurov - Simon Fraser University and Advanced Micro Devices, Inc.

Alexandra Fedorova - Simon Fraser University and The University of British Columbia

Evgeny Vinnik - Simon Fraser University

Tyler Dwyer - Simon Fraser University and The University of British Columbia

Fabien Hermenier - INRIA and the University of Nice - Sophia Antipolis

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Paper provided by the ACM Digital Library

Paper also available from IEEE Computer Society