Scheduling Algorithms for Distributed Cosmic Ray Detection Using Apache Mesos

  • Germán Schnyder
  • Sergio Nesmachnow
  • Gonzalo Tancredi
  • Andrei Tchernykh
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 697)

Abstract

This article presents two scheduling algorithms applied to the processing of astronomical images to detect cosmic rays on distributed memory high performance computing systems. We extend our previous article that proposed a parallel approach to improve processing times on image analysis using the Image Reduction and Analysis Facility IRAF software and the Docker project over Apache Mesos. By default, Mesos introduces a simple list scheduling algorithm where the first available task is assigned to the first available processor. On this paper we propose two alternatives for reordering the tasks allocation in order to improve the computational efficiency. The main results show that it is possible to reduce the makespan getting a speedup = 4.31 by adjusting how jobs are assigned and using Uniform processors.

Keywords

Image processing Distributed memory Containers Mesos Scheduling 

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Germán Schnyder
    • 1
  • Sergio Nesmachnow
    • 1
  • Gonzalo Tancredi
    • 1
  • Andrei Tchernykh
    • 2
  1. 1.Universidad de la RepúblicaMontevideoUruguay
  2. 2.CICESE Research CenterEnsenadaMexico

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