Preemptive Parallel Job Scheduling for Heterogeneous Systems Supporting Urgent Computing

Mulya Agung, Yuta Watanabe, Henning Weber, Ryusuke Egawa, Hiroyuki Takizawa

Research output: Contribution to journalArticlepeer-review

Abstract

Dedicated infrastructures are commonly used for urgent computations. However, using dedicated resources is not always affordable due to budget constraints. As a result, utilizing shared infrastructures becomes an alternative solution for urgent computations. Since the infrastructures are meant to serve many users, the urgent jobs may arrive when regular jobs are using the necessary resources. In such a case, it is necessary to preempt the regular jobs so that urgent jobs can be executed immediately. Most conventional methods for job scheduling have focused on reducing the response times and waiting times of all jobs. However, these methods can delay urgent jobs and hinder them from being completed within a stipulated deadline. Furthermore, in heterogeneous systems with coprocessors, preemption becomes more difficult because coprocessors rely on several system software functionalities provided by the host processor. In this paper, we propose a parallel job scheduling method to effectively use shared heterogeneous systems for urgent computations. Our method employs an in-memory process swapping mechanism to preempt jobs running on the coprocessor devices. The results of our simulations show that our method can achieve a significant reduction in the response time and slowdown of regular jobs without substantial delays of urgent jobs.

Original languageEnglish
Article number9328750
Pages (from-to)17557-17571
Number of pages15
JournalIEEE Access
Volume9
DOIs
Publication statusPublished - 2021

Keywords

  • Job scheduling
  • heterogeneous systems
  • preemption
  • process swapping
  • urgent computing

ASJC Scopus subject areas

  • Computer Science(all)
  • Materials Science(all)
  • Engineering(all)

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