Planning for distributed workfows: constraint-based coscheduling of computational jobs and data placement in distributed environments

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F15%3A00081123" target="_blank" >RIV/00216224:14330/15:00081123 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1088/1742-6596/608/1/012028A" target="_blank" >http://dx.doi.org/10.1088/1742-6596/608/1/012028A</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1088/1742-6596/608/1/012028A" target="_blank" >10.1088/1742-6596/608/1/012028A</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Planning for distributed workfows: constraint-based coscheduling of computational jobs and data placement in distributed environments

Popis výsledku v původním jazyce

When running data intensive applications on distributed computational resources long I/O overheads may be observed as access to remotely stored data is performed. Latencies and bandwidth can become the major limiting factor for the overall computation performance and can reduce the CPU/WallTime ratio to excessive IO wait. Reusing the knowledge of our previous research, we propose a constraint programming based planner that schedules computational jobs and data placements (transfers) in a distributed environment in order to optimize resource utilization and reduce the overall processing completion time. The optimization is achieved by ensuring that none of the resources (network links, data storages and CPUs) are oversaturated at any moment of time andeither (a) that the data is pre-placed at the site where the job runs or (b) that the jobs are scheduled where the data is already present.

Název v anglickém jazyce

Planning for distributed workfows: constraint-based coscheduling of computational jobs and data placement in distributed environments

Popis výsledku anglicky

When running data intensive applications on distributed computational resources long I/O overheads may be observed as access to remotely stored data is performed. Latencies and bandwidth can become the major limiting factor for the overall computation performance and can reduce the CPU/WallTime ratio to excessive IO wait. Reusing the knowledge of our previous research, we propose a constraint programming based planner that schedules computational jobs and data placements (transfers) in a distributed environment in order to optimize resource utilization and reduce the overall processing completion time. The optimization is achieved by ensuring that none of the resources (network links, data storages and CPUs) are oversaturated at any moment of time andeither (a) that the data is pre-placed at the site where the job runs or (b) that the jobs are scheduled where the data is already present.

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

<a href="/cs/project/GAP202%2F12%2F0306" target="_blank" >GAP202/12/0306: Dyschnet - Dynamické plánování a rozvrhování výpočetních a síťových zdrojů</a><br>

Návaznosti

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

Rok uplatnění

2015

Kód důvěrnosti údajů

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

Název statě ve sborníku

16th International Workshop on Advanced Computing and Analysis Techniques in Physics Research: Bridging Disciplines, ACAT 2014

ISBN

—

ISSN

1742-6588

e-ISSN

—

Počet stran výsledku

6

Strana od-do

1-6

Název nakladatele

Institute of Physics Publishing

Místo vydání

Prague, Czech Republic

Místo konání akce

Prague, Czech Republic

Datum konání akce

1. 1. 2015

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000358218000028