HPC WORKLOAD BALANCING ALGORITHM for CO-SCHEDULING ENVIRONMENTS

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HPC WORKLOAD BALANCING ALGORITHM for CO-SCHEDULING ENVIRONMENTS. / Kuchumov, Ruslan I.; Korkhov, Vladimir V.

In: CEUR Workshop Proceedings, Vol. 3041, 01.12.2021, p. 133-137.

Research output: Contribution to journal › Conference article › peer-review

BibTeX

@article{6002d543907c476880a1fb2323ba42c0,

title = "HPC WORKLOAD BALANCING ALGORITHM for CO-SCHEDULING ENVIRONMENTS",

abstract = "The goal of this research work is to reduce wait time of HPC (high performance computing) applications in schedulers queue by applying a co-scheduling strategy. This strategy allows the execution of more than one task with different non-overlapping requirements for computational resources simultaneously. Co-scheduling strategy reduces task queue wait time and improves utilization of cluster resources when compared to the scheduling strategies that do not allow for parallel task execution on the same machine. We have proposed a method for measuring application processing speed in its run-time, which can be used as a feedback for scheduling strategies. In this work, we have formalized the co-scheduling problem and proposed strategies for solving it. For some strategies we have shown analytically the upper bounds values of their competitive ratios. Besides that for the proposed scheduling strategies we ran numerical experiments using imitation models to show how they compare to the optimal strategy.",

keywords = "Co-scheduling, HPC, Scheduling theory, Stochastic optimization",

author = "Kuchumov, {Ruslan I.} and Korkhov, {Vladimir V.}",

note = "Publisher Copyright: Copyright {\textcopyright} 2021 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).; 9th International Conference {"}Distributed Computing and Grid Technologies in Science and Education{"}, GRID 2021 ; Conference date: 05-07-2021 Through 09-07-2021",

year = "2021",

month = dec,

day = "1",

language = "English",

volume = "3041",

pages = "133--137",

journal = "CEUR Workshop Proceedings",

issn = "1613-0073",

publisher = "RWTH Aahen University",

url = "https://indico.jinr.ru/event/1086/overview",

}

RIS

TY - JOUR

T1 - HPC WORKLOAD BALANCING ALGORITHM for CO-SCHEDULING ENVIRONMENTS

AU - Kuchumov, Ruslan I.

AU - Korkhov, Vladimir V.

N1 - Conference code: 9

PY - 2021/12/1

Y1 - 2021/12/1

N2 - The goal of this research work is to reduce wait time of HPC (high performance computing) applications in schedulers queue by applying a co-scheduling strategy. This strategy allows the execution of more than one task with different non-overlapping requirements for computational resources simultaneously. Co-scheduling strategy reduces task queue wait time and improves utilization of cluster resources when compared to the scheduling strategies that do not allow for parallel task execution on the same machine. We have proposed a method for measuring application processing speed in its run-time, which can be used as a feedback for scheduling strategies. In this work, we have formalized the co-scheduling problem and proposed strategies for solving it. For some strategies we have shown analytically the upper bounds values of their competitive ratios. Besides that for the proposed scheduling strategies we ran numerical experiments using imitation models to show how they compare to the optimal strategy.

AB - The goal of this research work is to reduce wait time of HPC (high performance computing) applications in schedulers queue by applying a co-scheduling strategy. This strategy allows the execution of more than one task with different non-overlapping requirements for computational resources simultaneously. Co-scheduling strategy reduces task queue wait time and improves utilization of cluster resources when compared to the scheduling strategies that do not allow for parallel task execution on the same machine. We have proposed a method for measuring application processing speed in its run-time, which can be used as a feedback for scheduling strategies. In this work, we have formalized the co-scheduling problem and proposed strategies for solving it. For some strategies we have shown analytically the upper bounds values of their competitive ratios. Besides that for the proposed scheduling strategies we ran numerical experiments using imitation models to show how they compare to the optimal strategy.

KW - Co-scheduling

KW - HPC

KW - Scheduling theory

KW - Stochastic optimization

UR - http://www.scopus.com/inward/record.url?scp=85121622442&partnerID=8YFLogxK

M3 - Conference article

AN - SCOPUS:85121622442

VL - 3041

SP - 133

EP - 137

JO - CEUR Workshop Proceedings

JF - CEUR Workshop Proceedings

SN - 1613-0073

T2 - 9th International Conference "Distributed Computing and Grid Technologies in Science and Education", GRID 2021

Y2 - 5 July 2021 through 9 July 2021

ER -

ID: 91158628