2021
Complex simulation workflows in containerized high-performance environment
VIŠŇOVSKÝ, Vladimír; Viktória SPIŠAKOVÁ; Jana HOZZOVÁ; Jaroslav OĽHA; Dalibor TRAPL et al.Základní údaje
Originální název
Complex simulation workflows in containerized high-performance environment
Autoři
VIŠŇOVSKÝ, Vladimír; Viktória SPIŠAKOVÁ ORCID; Jana HOZZOVÁ; Jaroslav OĽHA; Dalibor TRAPL; Vojtěch SPIWOK; Lukáš HEJTMÁNEK a Aleš KŘENEK
Vydání
Brusel, Proc. ESM 2021, od s. 42-45, 4 s. 2021
Nakladatel
EUROSIS
Další údaje
Jazyk
angličtina
Typ výsledku
Stať ve sborníku
Obor
10201 Computer sciences, information science, bioinformatics
Stát vydavatele
Belgie
Utajení
není předmětem státního či obchodního tajemství
Forma vydání
paměťový nosič (CD, DVD, flash disk)
Označené pro přenos do RIV
Ano
Kód RIV
RIV/00216224:14610/21:00119698
Organizační jednotka
Ústav výpočetní techniky
ISBN
978-94-92859-18-1
UT WoS
EID Scopus
Klíčová slova anglicky
Docker; Jupyter notebook; Kubernetes; Molecular force field; Protein folding; Reproducibility; Workflow
Štítky
Příznaky
Mezinárodní význam, Recenzováno
Změněno: 30. 3. 2023 14:31, Mgr. Alena Mokrá
V originále
utting-edge research involving in-silico simulations often requires to use many heterogeneous software tools made by different developers, resulting in complex, custom-made pipelines of various scripts and programs. Such pipelines are nearly impossible to be reproduced by other research groups, jeopardizing both quality and acceptance of such research results. Starting with two in-house use cases in computational chemistry, we identified a common pattern applicable for other applications as well, and we designed and implemented a solution based on Jupyter notebooks to drive the simulation, Docker containers to package all software dependencies, and Kubernetes execution environment to run several cooperating containers which build up the whole application.
Česky
utting-edge research involving in-silico simulations often requires to use many heterogeneous software tools made by different developers, resulting in complex, custom-made pipelines of various scripts and programs. Such pipelines are nearly impossible to be reproduced by other research groups, jeopardizing both quality and acceptance of such research results. Starting with two in-house use cases in computational chemistry, we identified a common pattern applicable for other applications as well, and we designed and implemented a solution based on Jupyter notebooks to drive the simulation, Docker containers to package all software dependencies, and Kubernetes execution environment to run several cooperating containers which build up the whole application.
Návaznosti
| GA19-16857S, projekt VaV |
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