About: Locality Aware Task Scheduling in Parallel Data Stream Processing

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An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

Attributes	Values
rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
rdfs:seeAlso	http://link.springer.com/chapter/10.1007/978-3-319-10422-5_35
Description	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 systems is 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, we propose 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. 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 systems is 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, we propose 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. (en)
Title	Locality Aware Task Scheduling in Parallel Data Stream Processing Locality Aware Task Scheduling in Parallel Data Stream Processing (en)
skos:prefLabel	Locality Aware Task Scheduling in Parallel Data Stream Processing Locality Aware Task Scheduling in Parallel Data Stream Processing (en)
skos:notation	RIV/00216208:11320/14:10218422!RIV15-MSM-11320___
http://linked.open...avai/riv/aktivita	I P
http://linked.open...avai/riv/aktivity	I, P(GA13-08195S), P(GP14-14292P)
http://linked.open...vai/riv/dodaniDat	2015
http://linked.open...aciTvurceVysledku	Zavoral, Filip Bednárek, David Yaghob, Jakub Falt, Zbyněk Kruliš, Martin
http://linked.open.../riv/druhVysledku	D - Článek ve sborníku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	Univerzita Karlova v Praze / Matematicko-fyzikální fakulta
http://linked.open...dnocenehoVysledku	26473
http://linked.open...ai/riv/idVysledku	RIV/00216208:11320/14:10218422
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	data streams; task scheduling; cache aware; NUMA; multicore CPU; Parallel (en)
http://linked.open.../riv/klicoveSlovo	NUMA cache aware data streams multicore CPU Parallel task scheduling
http://linked.open...ontrolniKodProRIV	[0444BBF2957C]
http://linked.open...v/mistoKonaniAkce	Madrid
http://linked.open...i/riv/mistoVydani	Madrid
http://linked.open...i/riv/nazevZdroje	Proceedings of the 8th International Symposium on Intelligent Distributed Computing - IDC'2014
http://linked.open...in/vavai/riv/obor	IN
http://linked.open...ichTvurcuVysledku	5 (xsd:int)
http://linked.open...cetTvurcuVysledku	5 (xsd:int)
http://linked.open...vavai/riv/projekt	Vysoce škálovatelné paralelní a distribuované metody zpracování vědeckých dat Employing Modern Parallel Architectures in Specific Domains of Database Systems
http://linked.open...UplatneniVysledku	2014
http://linked.open...iv/tvurceVysledku	Bednárek, David Yaghob, Jakub Zavoral, Filip Falt, Zbyněk Kruliš, Martin
http://linked.open...vavai/riv/typAkce	WRD - Světová
http://linked.open.../riv/zahajeniAkce	2014-09-03 (xsd:date)
issn	1860-949X
number of pages	12 (xsd:int)
http://bibframe.org/vocab/doi	10.1007/978-3-319-10422-5_35
http://purl.org/ne...btex#hasPublisher	Springer-Verlag
https://schema.org/isbn	978-3-319-10421-8
http://localhost/t...ganizacniJednotka	11320

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