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Energy-Aware Scheduling for Streaming Applications

Xu, Ruibin (2010) Energy-Aware Scheduling for Streaming Applications. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

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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 performanceof streaming applications to achieve high throughput and low response time.However, increasingly more attention is being shifted topower/performance trade-offbecause power consumption has become a limiting factor on system designas integrated circuits enter the realm of nanometer technology.This work addresses the problem of scheduling a streaming application(represented by a task graph)with the goal of minimizing its energy consumptionwhile 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, andvary-on/vary-off, which turns processors on and off to save static power consumption.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 anda novel multiprocessor scheduling algorithm that exploits the differencebetween the two QoS requirements to perform processor allocation,task mapping, and task speedscheduling simultaneously.


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Item Type: University of Pittsburgh ETD
Status: Unpublished
CreatorsEmailPitt UsernameORCID
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairMelhem, Ramimelhem@cs.pitt.eduMELHEM
Committee CoChairMosse, Danielmosse@cs.pitt.eduMOSSE
Committee MemberChilders, Brucechilders@cs.pitt.eduCHILDERS
Committee MemberYang, Junjuy9@pitt.eduJUY9
Date: 24 June 2010
Date Type: Completion
Defense Date: 4 January 2010
Approval Date: 24 June 2010
Submission Date: 8 March 2010
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Institution: University of Pittsburgh
Schools and Programs: Dietrich School of Arts and Sciences > Computer Science
Degree: PhD - Doctor of Philosophy
Thesis Type: Doctoral Dissertation
Refereed: Yes
Uncontrolled Keywords: energy management; power management; streaming application; dynamic voltage scaling; scheduling algorithm
Other ID:, etd-03082010-201840
Date Deposited: 10 Nov 2011 19:32
Last Modified: 15 Nov 2016 13:36


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