Scheduling algorithms for multi-core and GPU

Multiprocessor systems are now widely used as solution to the performance limitation and power problem currently limiting single processor systems. However to fully exploit the job parallelism on these systems, its resources(processors) must be assigned efficiently. In addition to improving the prog...

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Main Author: Song, Lee Yong.
Other Authors: Hsu Wen Jing
Format: Final Year Project
Language:English
Published: 2011
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Online Access:http://hdl.handle.net/10356/44096
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-440962023-03-03T20:25:09Z Scheduling algorithms for multi-core and GPU Song, Lee Yong. Hsu Wen Jing School of Computer Engineering Parallel and Distributed Computing Centre DRNTU::Engineering::Computer science and engineering::Computer systems organization::Computer-communication networks Multiprocessor systems are now widely used as solution to the performance limitation and power problem currently limiting single processor systems. However to fully exploit the job parallelism on these systems, its resources(processors) must be assigned efficiently. In addition to improving the program's performance, the power consumption must also be minimized. In this project, adaptive scheduling and algorithms to reduce the power consumption will be studied. The algorithms are evaluated based on the response time and power consumption. Equiparttioning (EQ) divide the number of processors equally to every job. Dynamic Equiparttioning (DEQ) operates the same way as EQ with a slight difference. Jobs are never allocated more than what was requested in DEQ. Adaptive Greedy Dynamic Equipartitioning(AGDEQ) operates the same way as DEQ except that the next cpu allocation is done by using the utilization rate of the previous task execution. In terms of response time, AGDEQ has the lowest response time. This is followed by DEQ and lastly EQ. In terms of power consumption, while Geometric power distribution can improve the response time, it also consumes the most power. The scheme that has the lowest power consumed is equal power distribution among processors. Bachelor of Engineering (Computer Science) 2011-05-25T09:05:59Z 2011-05-25T09:05:59Z 2011 2011 Final Year Project (FYP) http://hdl.handle.net/10356/44096 en Nanyang Technological University 49 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Computer science and engineering::Computer systems organization::Computer-communication networks
spellingShingle DRNTU::Engineering::Computer science and engineering::Computer systems organization::Computer-communication networks
Song, Lee Yong.
Scheduling algorithms for multi-core and GPU
description Multiprocessor systems are now widely used as solution to the performance limitation and power problem currently limiting single processor systems. However to fully exploit the job parallelism on these systems, its resources(processors) must be assigned efficiently. In addition to improving the program's performance, the power consumption must also be minimized. In this project, adaptive scheduling and algorithms to reduce the power consumption will be studied. The algorithms are evaluated based on the response time and power consumption. Equiparttioning (EQ) divide the number of processors equally to every job. Dynamic Equiparttioning (DEQ) operates the same way as EQ with a slight difference. Jobs are never allocated more than what was requested in DEQ. Adaptive Greedy Dynamic Equipartitioning(AGDEQ) operates the same way as DEQ except that the next cpu allocation is done by using the utilization rate of the previous task execution. In terms of response time, AGDEQ has the lowest response time. This is followed by DEQ and lastly EQ. In terms of power consumption, while Geometric power distribution can improve the response time, it also consumes the most power. The scheme that has the lowest power consumed is equal power distribution among processors.
author2 Hsu Wen Jing
author_facet Hsu Wen Jing
Song, Lee Yong.
format Final Year Project
author Song, Lee Yong.
author_sort Song, Lee Yong.
title Scheduling algorithms for multi-core and GPU
title_short Scheduling algorithms for multi-core and GPU
title_full Scheduling algorithms for multi-core and GPU
title_fullStr Scheduling algorithms for multi-core and GPU
title_full_unstemmed Scheduling algorithms for multi-core and GPU
title_sort scheduling algorithms for multi-core and gpu
publishDate 2011
url http://hdl.handle.net/10356/44096
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