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Cooperative multitasking for GPU‐accelerated grid systems
Author(s) -
Ino Fumihiko,
Ogita Akihiro,
Oita Kentaro,
Hagihara Kenichi
Publication year - 2012
Publication title -
concurrency and computation: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.309
H-Index - 67
eISSN - 1532-0634
pISSN - 1532-0626
DOI - 10.1002/cpe.1722
Subject(s) - computer science , graphics , rendering (computer graphics) , human multitasking , frame rate , throughput , computer graphics (images) , parallel computing , general purpose computing on graphics processing units , computational science , operating system , artificial intelligence , psychology , wireless , cognitive psychology
SUMMARY This paper presents a cooperative multitasking method for concurrent execution of scientific and graphics applications on the graphics processing unit (GPU). Our method is designed to accelerate compute unified device architecture‐based applications using idle GPU cycles in the office. To prevent significant slow‐down of graphics applications, the method divides scientific tasks into smaller pieces, which are then sequentially executed at the appropriate intervals. The method also has flexibility in finding the best tradeoff point between scientific applications and graphics applications. Experimental results show that the proposed method is useful to control the frame rate of the graphics application and the throughput of the scientific application. For example, biological sequence alignment can be processed at approximately 30% of the dedicated throughput while achieving interactive rendering at 58 frames per second. We also show that matrix multiplication can be efficiently processed at 60% of the dedicated throughput during word processing and web browsing. Copyright © 2011 John Wiley & Sons, Ltd.