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PBS: a unified priority-based scheduler

Published: 12 June 2007 Publication History

Abstract

Blind scheduling policies schedule tasks without knowledge of the tasks' remaining processing times. Existing blind policies, such as FCFS, PS, and LAS, have proven useful in network and operating system applications, but each policy has a separate, vastly differing description, leading to separate and distinct implementations. This paper presents the design and implementation of a configurable blind scheduler that contains a continuous, tunable parameter. By merely changing the value of this parameter, the scheduler's policy exactly emulates or closely approximates several existing standard policies. Other settings enable policies whose behavior is a hybrid of these standards. We demonstrate the practical benefits of such a configurable scheduler by implementing it into the Linux operating system. We show that we can emulate the behavior of Linux's existing, more complex scheduler with a single (hybrid) setting of the parameter. We also show, using synthetic workloads, that the best value for the tunable parameter is not unique, but depends on distribution of the size of tasks arriving to the system. Finally, we use our formulation of the configurable scheduler to contrast the behavior of various blind schedulers by exploring how various properties of the scheduler change as we vary our scheduler's tunable parameter.

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Published In

cover image ACM Conferences
SIGMETRICS '07: Proceedings of the 2007 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
June 2007
398 pages
ISBN:9781595936394
DOI:10.1145/1254882
  • cover image ACM SIGMETRICS Performance Evaluation Review
    ACM SIGMETRICS Performance Evaluation Review  Volume 35, Issue 1
    SIGMETRICS '07 Conference Proceedings
    June 2007
    382 pages
    ISSN:0163-5999
    DOI:10.1145/1269899
    Issue’s Table of Contents
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. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 12 June 2007

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Author Tags

  1. FCFS
  2. LAS
  3. PBS
  4. linux
  5. queueing systems
  6. scheduling

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Overall Acceptance Rate 459 of 2,691 submissions, 17%

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  • (2024)MalleTrain: Deep Neural Networks Training on Unfillable Supercomputer NodesProceedings of the 15th ACM/SPEC International Conference on Performance Engineering10.1145/3629526.3645035(190-200)Online publication date: 7-May-2024
  • (2024)Role of heterogeneity: National scale data-driven agent-based modeling for the US COVID-19 Scenario Modeling HubEpidemics10.1016/j.epidem.2024.10077948(100779)Online publication date: Sep-2024
  • (2024)Enhancing heterogeneous cluster efficiency through node-centric schedulingThe Journal of Supercomputing10.1007/s11227-024-05988-zOnline publication date: 11-Mar-2024
  • (2023)Mastering HPC Runtime Prediction: From Observing Patterns to a Methodological ApproachPractice and Experience in Advanced Research Computing 2023: Computing for the Common Good10.1145/3569951.3593598(75-85)Online publication date: 23-Jul-2023
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  • (2022)Data-driven scalable pipeline using national agent-based models for real-time pandemic response and decision supportThe International Journal of High Performance Computing Applications10.1177/1094342022112703437:1(4-27)Online publication date: 20-Oct-2022
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