Detail výsledku

Optimizing Biomedical Ultrasound Workflow Scheduling Using Cluster Simulations

JAROŠ, M.; KLUSÁČEK, D.; JAROŠ, J. Optimizing Biomedical Ultrasound Workflow Scheduling Using Cluster Simulations. In Job Scheduling Strategies for Parallel Processing. JSSPP 2020. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). New Orleans: Springer Nature Switzerland AG, 2020. p. 68-84. ISBN: 978-3-030-63170-3.
Typ
článek ve sborníku konference
Jazyk
anglicky
Autoři
Jaroš Marta, Ing., Ph.D., UPSY (FIT)
KLUSÁČEK, D.
Jaroš Jiří, prof. Ing., Ph.D., UPSY (FIT)
Abstrakt

Therapeutic ultrasound plays an increasing role in dealing
with oncological diseases, drug delivery and neurostimulation. To maximize the treatment outcome, thorough pre-operative planning using complex numerical models considering patient anatomy is crucial. From the
computational point of view, the treatment planning can be seen as the
execution of a complex workflow consisting of many different tasks with
various computational requirements on a remote cluster or in cloud. Since
these resources are precious, workflow scheduling plays an important part
in the whole process.
This paper describes an extended version of the k-Dispatch workflow
management system that uses historical performance data collected on
similar workflows to choose suitable amount of computational resources
and estimates execution time and cost of particular tasks. This paper
also introduces necessary extensions to the Alea cluster simulator that
enable the estimation of the queuing and total execution time of the
whole workflow. The conjunction of both systems then allows for finegrain optimization of the workflow execution parameters with respect to
the current cluster utilization. The experimental results show that this
approach is able to reduce the computational time by 26%.

Klíčová slova

scheduling, workflow, k-Dispatch, simulation, ALEA

URL
Rok
2020
Strany
68–84
Sborník
Job Scheduling Strategies for Parallel Processing. JSSPP 2020
Řada
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Svazek
12326
Konference
Job Scheduling Strategies for Parallel Processing 23rd International Workshop, JSSPP 2020
ISBN
978-3-030-63170-3
Vydavatel
Springer Nature Switzerland AG
Místo
New Orleans
DOI
EID Scopus
BibTeX
@inproceedings{BUT168133,
  author="JAROŠ, M. and KLUSÁČEK, D. and JAROŠ, J.",
  title="Optimizing Biomedical Ultrasound Workflow Scheduling Using Cluster Simulations",
  booktitle="Job Scheduling Strategies for Parallel Processing. JSSPP 2020",
  year="2020",
  series="Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
  volume="12326",
  pages="68--84",
  publisher="Springer Nature Switzerland AG",
  address="New Orleans",
  doi="10.1007/978-3-030-63171-0\{_}4",
  isbn="978-3-030-63170-3",
  url="https://link.springer.com/chapter/10.1007/978-3-030-63171-0_4"
}
Soubory
Projekty
Fotoakustická/ultrazvuková mamoskopie pro dektekci lézí v prsou, MŠMT, Společná technologická iniciativa ECSEL, PAMMOTH, zahájení: 2017-01-01, ukončení: 2021-06-30, ukončen
IT4Innovations excellence in science, MŠMT, Národní program udržitelnosti II, LQ1602, zahájení: 2016-01-01, ukončení: 2020-12-31, ukončen
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