Planning of distributed data production for High Energy and Nuclear Physics
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F18%3A00100898" target="_blank" >RIV/00216224:14330/18:00100898 - isvavai.cz</a>
Alternative codes found
RIV/61389005:_____/18:00500205
Result on the web
<a href="http://dx.doi.org/10.1007/s10586-018-2834-3" target="_blank" >http://dx.doi.org/10.1007/s10586-018-2834-3</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s10586-018-2834-3" target="_blank" >10.1007/s10586-018-2834-3</a>
Alternative languages
Result language
angličtina
Original language name
Planning of distributed data production for High Energy and Nuclear Physics
Original language description
Modern experiments in High Energy and Nuclear Physics heavily rely on distributed computations using multiple computational facilities across the world. One of the essential types of the computations is a distributed data production where petabytes of raw files from a single source has to be processed once (per production campaign) using thousands of CPUs at distant locations and the output has to be transferred back to that source. The data distribution over a large system does not necessary match the distribution of storage, network and CPU capacity. Therefore, bottlenecks may appear and lead to increased latency and degraded performance. In this paper we propose a new scheduling approach for distributed data production which is based on the network flow maximization model. In our approach a central planner defines how much input and output data should be transferred over each network link in order to maximize the computational throughput. Such plans are created periodically for a fixed planning time interval using up-to-date information on network, storage and CPU resources. The centrally created plans are executed in a distributed manner by dedicated services running at participating sites. Our simulations based on the log records from the data production framework of the experiment STAR (Solenoid Tracker at RHIC) have shown that the proposed model systematically provides a better performance compared to the simulated traditional techniques.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
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
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Cluster Computing
ISSN
1386-7857
e-ISSN
1573-7543
Volume of the periodical
21
Issue of the periodical within the volume
4
Country of publishing house
US - UNITED STATES
Number of pages
17
Pages from-to
1949-1965
UT code for WoS article
000457276800012
EID of the result in the Scopus database
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