KLUSÁČEK, Dalibor and Hana RUDOVÁ. The importance of complete data sets for job scheduling simulations. In Job Scheduling Strategies for Parallel Processing, Revised Selected Papers. Heidelberg: Springer, Lecture Notes in Computer Science 6253, 2010, p. 132-153. ISBN 978-3-642-16504-7. Available from: https://dx.doi.org/10.1007/978-3-642-16505-4_8.
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Basic information
Original name The importance of complete data sets for job scheduling simulations
Authors KLUSÁČEK, Dalibor (203 Czech Republic, guarantor, belonging to the institution) and Hana RUDOVÁ (203 Czech Republic, belonging to the institution).
Edition Heidelberg, Job Scheduling Strategies for Parallel Processing, Revised Selected Papers, p. 132-153, 22 pp. 2010.
Publisher Springer, Lecture Notes in Computer Science 6253
Other information
Original language English
Type of outcome Proceedings paper
Field of Study 10201 Computer sciences, information science, bioinformatics
Country of publisher Germany
Confidentiality degree is not subject to a state or trade secret
Publication form printed version "print"
WWW URL
Impact factor Impact factor: 0.402 in 2005
RIV identification code RIV/00216224:14330/10:00067181
Organization unit Faculty of Informatics
ISBN 978-3-642-16504-7
ISSN 0302-9743
Doi http://dx.doi.org/10.1007/978-3-642-16505-4_8
UT WoS 000286164600008
Keywords in English Grid; Cluster; Scheduling; MetaCentrum; Workload; Failures; Specific Job Requirements
Tags International impact, Reviewed
Changed by Changed by: RNDr. Pavel Šmerk, Ph.D., učo 3880. Changed: 30/4/2014 04:37.
Abstract
This paper has been inspired by the study of the complex data set from the Czech National Grid MetaCentrum. Unlike other widely used workloads from Parallel Workloads Archive or Grid Workloads Archive, this data set includes additional information concerning machine failures, job requirements and machine parameters which allows to perform more realistic simulations. We show that large differences in the performance of various scheduling algorithms appear when these additional information are used. Moreover, we studied other publicly available workloads and partially reconstructed information concerning their machine failures and job requirements using statistical and analytical models to demonstrate that similar behavior is also expectable for other workloads. We suggest that additional information about both machines and jobs should be incorporated into the workloads archives to allow proper and more realistic simulations.
Links
MSM0021622419, plan (intention)Name: Vysoce paralelní a distribuované výpočetní systémy
Investor: Ministry of Education, Youth and Sports of the CR, Highly Parallel and Distributed Computing Systems
MUNI/A/0914/2009, interní kód MUName: Rozsáhlé výpočetní systémy: modely, aplikace a verifikace (Acronym: SV-FI MAV)
Investor: Masaryk University, Category A
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