Optimizing Biomedical Ultrasound Workflow Scheduling Using Cluster Simulations
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F63839172%3A_____%2F20%3A10133331" target="_blank" >RIV/63839172:_____/20:10133331 - isvavai.cz</a>
Alternative codes found
RIV/00216305:26230/20:PU138624
Result on the web
<a href="https://link.springer.com/chapter/10.1007/978-3-030-63171-0_4" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-030-63171-0_4</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-63171-0_4" target="_blank" >10.1007/978-3-030-63171-0_4</a>
Alternative languages
Result language
angličtina
Original language name
Optimizing Biomedical Ultrasound Workflow Scheduling Using Cluster Simulations
Original language description
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%.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/EF16_013%2F0001797" target="_blank" >EF16_013/0001797: CESNET E-Infrastructure - Modernisation</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Job Scheduling Strategies for Parallel Processing
ISBN
978-3-030-63170-3
ISSN
0302-9743
e-ISSN
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Number of pages
17
Pages from-to
68-84
Publisher name
Springer
Place of publication
Switzerland
Event location
New Orleans
Event date
May 22, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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