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Energy-aware scheduling for streamin...

University of Pittsburgh.

Energy-aware scheduling for streaming applications.

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	Energy-aware scheduling for streaming applications./
Author:	Xu, Ruibin.
Description:	1 online resource (148 pages)
Notes:	Source: Dissertation Abstracts International, Volume: 71-08, Section: B, page: 4936.
Contained By:	Dissertation Abstracts International71-08B.
Subject:	Computer science. -
Online resource:	click for full text (PQDT)
ISBN:	9781124147956

Energy-aware scheduling for streaming applications.
Xu, Ruibin.

Energy-aware scheduling for streaming applications. - 1 online resource (148 pages)

Source: Dissertation Abstracts International, Volume: 71-08, Section: B, page: 4936.

Thesis (Ph.D.)

Includes bibliographical references

Streaming applications have become increasingly important and widespread, with application domains ranging from embedded devices to server systems. Traditionally, researchers have been focusing on improving the performance of streaming applications to achieve high throughput and low response time. However, increasingly more attention is being shifted to power/performance trade-off because power consumption has become a limiting factor on system design as integrated circuits enter the realm of nanometer technology.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9781124147956Subjects--Topical Terms:

573171
Computer science.
Index Terms--Genre/Form:

554714
Electronic books.

Energy-aware scheduling for streaming applications.
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020 $a 9781124147956
035 $a (MiAaPQ)AAI3417430
035 $a AAI3417430
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099 $a TUL $f hyy $c available through World Wide Web
100 1 $a Xu, Ruibin. $3 1182036
245 1 0 $a Energy-aware scheduling for streaming applications.
264 0 $c 2010
300 $a 1 online resource (148 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a Source: Dissertation Abstracts International, Volume: 71-08, Section: B, page: 4936.
500 $a Advisers: Rami Melhem; Daniel Mosse.
502 $a Thesis (Ph.D.) $c University of Pittsburgh $d 2010.
504 $a Includes bibliographical references
520 $a Streaming applications have become increasingly important and widespread, with application domains ranging from embedded devices to server systems. Traditionally, researchers have been focusing on improving the performance of streaming applications to achieve high throughput and low response time. However, increasingly more attention is being shifted to power/performance trade-off because power consumption has become a limiting factor on system design as integrated circuits enter the realm of nanometer technology.
520 $a This work addresses the problem of scheduling a streaming application (represented by a task graph) with the goal of minimizing its energy consumption while satisfying its two quality of service (QoS) requirements, namely, throughput and response time. The available power management mechanisms are dynamic voltage scaling (DVS), which has been shown to be effective in reducing dynamic power consumption, and vary-on/vary-off, which turns processors on and off to save static power consumption.
520 $a Scheduling algorithms are proposed for different computing platforms (uniprocessor and multiprocessor systems), different characteristics of workload (deterministic and stochastic workload), and different types of task graphs (singleton and general task graphs). Both continuous and discrete processor power models are considered. The highlights are a unified approach for obtaining optimal (or provably close to optimal) uniprocessor DVS schemes for various DVS strategies and a novel multiprocessor scheduling algorithm that exploits the difference between the two QoS requirements to perform processor allocation, task mapping, and task speed scheduling simultaneously.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
650 4 $a Computer science. $3 573171
655 7 $a Electronic books. $2 local $3 554714
690 $a 0984
710 2 $a ProQuest Information and Learning Co. $3 1178819
710 2 $a University of Pittsburgh. $3 1178873
773 0 $t Dissertation Abstracts International $g 71-08B.
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3417430 $z click for full text (PQDT)

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