<?xml version="1.0" encoding="utf-8" standalone="yes"?>
<item>
  <id>05970228</id>
  <dt>j</dt>
  <an>05970228</an>
  <augroup>
    <au>Barbosa, Jorge G.</au>
    <au>Moreira, Belmiro</au>
  </augroup>
  <ti>Dynamic scheduling of a batch of parallel task jobs on heterogeneous clusters.</ti>
  <so>Parallel Comput. 37, No. 8, 428-438 (2011).</so>
  <py>2011</py>
  <pu>Elsevier (North Holland), Amsterdam</pu>
  <lagroup>
    <la>EN</la>
  </lagroup>
  <ccgroup>
  </ccgroup>
  <utgroup>
    <ut>parallel task scheduling</ut>
    <ut>list scheduling</ut>
    <ut>image data</ut>
    <ut>multiple DAG</ut>
    <ut>non-deterministic job arrival</ut>
  </utgroup>
  <cigroup>
  </cigroup>
  <ligroup>
    <li>doi:10.1016/j.parco.2010.12.004</li>
  </ligroup>
  <abgroup>
    <ab>Summary: This paper addresses the problem of minimizing the scheduling length (make-span) of a batch of jobs with different arrival times. A job is described by a direct acyclic graph (DAG) of parallel tasks. The paper proposes a dynamic scheduling method that adapts the schedule when new jobs are submitted and that may change the processors assigned to a job during its execution. The scheduling method is divided into a scheduling strategy and a scheduling algorithm. We also propose an adaptation of the Heterogeneous Earliest-Finish-Time (HEFT) algorithm, called here P-HEFT, to handle parallel tasks in heterogeneous clusters with good efficiency without compromising the makespan. The results of a comparison of this algorithm with another DAG scheduler using a simulation of several machine configurations and job types shows that P-HEFT gives a shorter makespan for a single DAG but scores worse for multiple DAGs. Finally, the results of the dynamic scheduling of a batch of jobs using the proposed scheduler method showed significant improvements for more heavily loaded machines when compared to the alternative resource reservation approach.</ab>
    <rv></rv>
  </abgroup>
</item>