Locality Aware Task Scheduling in Parallel Data Stream Processing

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F14%3A10218422" target="_blank" >RIV/00216208:11320/14:10218422 - isvavai.cz</a>

Výsledek na webu

<a href="http://link.springer.com/chapter/10.1007/978-3-319-10422-5_35" target="_blank" >http://link.springer.com/chapter/10.1007/978-3-319-10422-5_35</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-319-10422-5_35" target="_blank" >10.1007/978-3-319-10422-5_35</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Locality Aware Task Scheduling in Parallel Data Stream Processing

Popis výsledku v původním jazyce

Parallel data processing and parallel streaming systems become quite popular. They are employed in various domains such as real-time signal processing, OLAP database systems, or high performance data extraction. One of the key components of these systemsis the task scheduler which plans and executes tasks spawned by the system on available CPU cores. The multiprocessor systems and CPU architecture of the day become quite complex, which makes the task scheduling a challenging problem. In this paper, wepropose a novel task scheduling strategy for parallel data stream systems, that rejects many technical issues of the current hardware. We were able to achieve up to 3x speed up on a NUMA system and up to 10% speed up on an older SMP system with respect to the unoptimized version of the scheduler. The basic ideas implemented in our scheduler may be adopted for task schedulers that focus on other priorities or employ different constraints.

Název v anglickém jazyce

Locality Aware Task Scheduling in Parallel Data Stream Processing

Popis výsledku anglicky

Parallel data processing and parallel streaming systems become quite popular. They are employed in various domains such as real-time signal processing, OLAP database systems, or high performance data extraction. One of the key components of these systemsis the task scheduler which plans and executes tasks spawned by the system on available CPU cores. The multiprocessor systems and CPU architecture of the day become quite complex, which makes the task scheduling a challenging problem. In this paper, wepropose a novel task scheduling strategy for parallel data stream systems, that rejects many technical issues of the current hardware. We were able to achieve up to 3x speed up on a NUMA system and up to 10% speed up on an older SMP system with respect to the unoptimized version of the scheduler. The basic ideas implemented in our scheduler may be adopted for task schedulers that focus on other priorities or employ different constraints.

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

—

Projekt

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

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2014

Kód důvěrnosti údajů

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

Název statě ve sborníku

Proceedings of the 8th International Symposium on Intelligent Distributed Computing - IDC'2014

ISBN

978-3-319-10421-8

ISSN

1860-949X

e-ISSN

—

Počet stran výsledku

12

Strana od-do

331-342

Název nakladatele

Springer Verlag

Místo vydání

Madrid

Místo konání akce

Madrid

Datum konání akce

3. 9. 2014

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

—