Multi-Resource Aware Fairsharing for Heterogeneous Systems

D 2015

Multi-Resource Aware Fairsharing for Heterogeneous Systems

KLUSÁČEK, Dalibor and Hana RUDOVÁ

Basic information

Original name

Multi-Resource Aware Fairsharing for Heterogeneous Systems

Authors

KLUSÁČEK, Dalibor (203 Czech Republic) and Hana RUDOVÁ (203 Czech Republic, guarantor, belonging to the institution)

Edition

1. vyd. Switzerland, Job Scheduling Strategies for Parallel Processing, p. 53-69, 17 pp. 2015

Publisher

Springer, Lecture Notes in Computer Science 8828

Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

10201 Computer sciences, information science, bioinformatics

Country of publisher

Germany

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

printed version "print"

References:

URL

Impact factor

Impact factor: 0.402 in 2005

RIV identification code

RIV/00216224:14330/15:00080587

Organization unit

Faculty of Informatics

ISBN

978-3-319-15788-7

ISSN

DOI

http://dx.doi.org/10.1007/978-3-319-15789-4_4

UT WoS

000355729800004

Keywords in English

Multi-Resource Fairness; Fairshare; Heterogeneity

Abstract

V originále

Current production resource management and scheduling systems often use some mechanism to guarantee fair sharing of computational resources among different users of the system. For example, the user who so far consumed small amount of CPU time gets higher priority and vice versa. However, different users may have highly heterogeneous demands concerning system resources, including CPUs, RAM, HDD storage capacity or, e.g., GPU cores. Therefore, it may not be fair to prioritize them only with respect to the consumed CPU time. Still, applied mechanisms often do not reflect other consumed resources or they use rather simplified and "ad hoc" solutions to approach these issues. We show that such solutions may be (highly) unfair and unsuitable for heterogeneous systems. We provide a survey of existing works that try to deal with this situation, analyzing and evaluating their characteristics. Next, we present new enhanced approach that supports multi-resource aware user prioritization mechanism. Importantly, this approach is capable of dealing with the heterogeneity of both jobs and resources. A working implementation of this new prioritization scheme is currently applied in the Czech National Grid Infrastructure MetaCentrum.

Links

GAP202/12/0306, research and development project

Name: Dyschnet - Dynamické plánování a rozvrhování výpočetních a síťových zdrojů (Acronym: Dyschnet)

Investor: Czech Science Foundation

Citovat

KLUSÁČEK, Dalibor and Hana RUDOVÁ. Multi-Resource Aware Fairsharing for Heterogeneous Systems. In Walfredo Cirne and Narayan Desai. Job Scheduling Strategies for Parallel Processing. 1st ed. Switzerland: Springer, Lecture Notes in Computer Science 8828, 2015, p. 53-69. ISBN 978-3-319-15788-7. Available from: https://dx.doi.org/10.1007/978-3-319-15789-4_4.

@inproceedings{1186297,
   author = {Klusáček, Dalibor and Rudová, Hana},
   address = {Switzerland},
   booktitle = {Job Scheduling Strategies for Parallel Processing},
   doi = {http://dx.doi.org/10.1007/978-3-319-15789-4_4},
   edition = {1},
   editor = {Walfredo Cirne and Narayan Desai},
   keywords = {Multi-Resource Fairness; Fairshare; Heterogeneity},
   howpublished = {tištěná verze "print"},
   language = {eng},
   location = {Switzerland},
   isbn = {978-3-319-15788-7},
   pages = {53-69},
   publisher = {Springer, Lecture Notes in Computer Science 8828},
   title = {Multi-Resource Aware Fairsharing for Heterogeneous Systems},
   url = {http://www.cs.huji.ac.il/~feit/parsched/jsspp14},
   year = {2015}
}

TY  - JOUR
ID  - 1186297
AU  - Klusáček, Dalibor - Rudová, Hana
PY  - 2015
TI  - Multi-Resource Aware Fairsharing for Heterogeneous Systems
PB  - Springer, Lecture Notes in Computer Science 8828
CY  - Switzerland
SN  - 9783319157887
KW  - Multi-Resource Fairness
KW  - Fairshare
KW  - Heterogeneity
UR  - http://www.cs.huji.ac.il/~feit/parsched/jsspp14
N2  - Current production resource management and scheduling systems often use some mechanism to guarantee fair sharing of computational resources among different users of the system. For example, the user who so far consumed small amount of CPU time gets higher priority and vice versa. However, different users may have highly heterogeneous demands concerning system resources, including CPUs, RAM, HDD storage capacity or, e.g., GPU cores. Therefore, it may not be fair to prioritize them only with respect to the consumed CPU time. Still, applied mechanisms often do not reflect other consumed resources or they use rather simplified and "ad hoc" solutions to approach these issues. We show that such solutions may be (highly) unfair and unsuitable for heterogeneous systems. We provide a survey of existing works that try to deal with this situation, analyzing and evaluating their characteristics. Next, we present new enhanced approach that supports multi-resource aware user prioritization mechanism. Importantly, this approach is capable of dealing with the heterogeneity of both jobs and resources. A working implementation of this new prioritization scheme is currently applied in the Czech National Grid Infrastructure MetaCentrum.
ER  -

KLUSÁČEK, Dalibor and Hana RUDOVÁ. Multi-Resource Aware Fairsharing for Heterogeneous Systems. In Walfredo Cirne and Narayan Desai. \textit{Job Scheduling Strategies for Parallel Processing}. 1st ed. Switzerland: Springer, Lecture Notes in Computer Science 8828, 2015, p.~53-69. ISBN~978-3-319-15788-7. Available from: https://dx.doi.org/10.1007/978-3-319-15789-4\_{}4.

Detailed Information on Publication Record