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<title level="a" type="main">Bi-criteria Algorithm for Scheduling Jobs on Cluster Platforms *</title>
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<date>June 27–30, 2004</date>
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<persName xmlns="http://www.tei-c.org/ns/1.0"><forename type="first">Pierre-François</forename><surname>Dutot</surname></persName>
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<persName xmlns="http://www.tei-c.org/ns/1.0"><forename type="first">Lionel</forename><surname>Eyraud</surname></persName>
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<persName xmlns="http://www.tei-c.org/ns/1.0"><forename type="first">Grégory</forename><surname>Gr´</surname></persName>
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<persName xmlns="http://www.tei-c.org/ns/1.0"><forename type="first">Grégory</forename><surname>Mouní</surname></persName>
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<persName xmlns="http://www.tei-c.org/ns/1.0"><forename type="first">Denis</forename><surname>Trystram</surname></persName>
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<title level="a" type="main">Bi-criteria Algorithm for Scheduling Jobs on Cluster Platforms *</title>
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<date type="published">June 27–30, 2004</date>
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<note>Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. ACM 1-58113-840-7/04/0006 ...$5.00.</note>
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<term>F22 [Analysis of Algorithms and Problem Complexity]: Nonnumerical Algorithms and Problems—Sequencing</term>
<term>and scheduling; D41 [Operating Systems]: Process management—Scheduling, Concurrency</term>
<term>Keywords</term>
<term>Parallel Computing, Algorithms, Scheduling, Parallel Tasks,</term>
<term>Moldable Tasks, Bi-criteria</term>
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<abstract>
<p>We describe in this paper a new method for building an efficient algorithm for scheduling jobs in a cluster. Jobs are considered as parallel tasks (PT) which can be scheduled on any number of processors. The main feature is to consider two criteria that are optimized together. These criteria are the makespan and the weighted minimal average completion time (minsum). They are chosen for their complementarity, to be able to represent both user-oriented objectives and system administrator objectives. We propose an algorithm based on a batch policy with increasing batch sizes, with a smart selection of jobs in each batch. This algorithm is assessed by intensive simulation results, compared to a new lower bound (obtained by a relaxation of ILP) of the optimal schedules for both criteria separately. It is currently implemented in an actual real-size cluster platform.</p>
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