Hyperloom Possibilities for Executing Scientific Workflows on the Cloud

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F18%3A10237362" target="_blank" >RIV/61989100:27240/18:10237362 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/61989100:27740/18:10237362

Výsledek na webu

<a href="https://link.springer.com/chapter/10.1007%2F978-3-319-61566-0_36" target="_blank" >https://link.springer.com/chapter/10.1007%2F978-3-319-61566-0_36</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-319-61566-0_36" target="_blank" >10.1007/978-3-319-61566-0_36</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Hyperloom Possibilities for Executing Scientific Workflows on the Cloud

Popis výsledku v původním jazyce

We have developed HyperLoom - a platform for defining and executing scientific workflows in large-scale HPC systems. The computational tasks in such workflows often have non-trivial dependency patterns, unknown execution time and unknown sizes of generated outputs. HyperLoom enables to efficiently execute the workflows respecting task requirements and cluster resources agnostically to the shape or size of the workflow. Although HPC infrastructures provide an unbeatable performance, they may be unavailable or too expensive especially for small to medium workloads. Moreover, for some workloads, due to HPCs not very flexible resource allocation policy, the system energy efficiency may not be optimal at some stages of the execution. In contrast, current public cloud providers such as Amazon, Google or Exoscale allow users a comfortable and elastic way of deploying, scaling and disposing a virtualized cluster of almost any size. In this paper, we describe HyperLoom virtualization and evaluate its performance in a virtualized environment using workflows of various shapes and sizes. Finally, we discuss the Hyperloom potential for its expansion to cloud environments.

Název v anglickém jazyce

Hyperloom Possibilities for Executing Scientific Workflows on the Cloud

Popis výsledku anglicky

We have developed HyperLoom - a platform for defining and executing scientific workflows in large-scale HPC systems. The computational tasks in such workflows often have non-trivial dependency patterns, unknown execution time and unknown sizes of generated outputs. HyperLoom enables to efficiently execute the workflows respecting task requirements and cluster resources agnostically to the shape or size of the workflow. Although HPC infrastructures provide an unbeatable performance, they may be unavailable or too expensive especially for small to medium workloads. Moreover, for some workloads, due to HPCs not very flexible resource allocation policy, the system energy efficiency may not be optimal at some stages of the execution. In contrast, current public cloud providers such as Amazon, Google or Exoscale allow users a comfortable and elastic way of deploying, scaling and disposing a virtualized cluster of almost any size. In this paper, we describe HyperLoom virtualization and evaluate its performance in a virtualized environment using workflows of various shapes and sizes. Finally, we discuss the Hyperloom potential for its expansion to cloud environments.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2018

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Advances in Intelligent Systems and Computing. Volume 611

ISBN

978-3-319-61565-3

ISSN

2194-5357

e-ISSN

2194-5365

Počet stran výsledku

10

Strana od-do

397-406

Název nakladatele

Springer

Místo vydání

Cham

Místo konání akce

Turín

Datum konání akce

10. 7. 2017

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000432998800036