Integrated Task Clustering, Mapping and Scheduling for Heterogeneous Computing Systems
This paper presents a new approach for mapping and scheduling task graphs for heterogeneous hardware/software computing systems using heuristic search. Task mapping and scheduling are vital in hardware/software codesign and previous approaches that treat them separately lead to suboptimal solutions....
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Published in | International journal of computer science & information technology Vol. 4; no. 1; p. 127 |
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Main Author | |
Format | Journal Article |
Language | English |
Published |
29.02.2012
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Subjects | |
Online Access | Get full text |
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Summary: | This paper presents a new approach for mapping and scheduling task graphs for heterogeneous hardware/software computing systems using heuristic search. Task mapping and scheduling are vital in hardware/software codesign and previous approaches that treat them separately lead to suboptimal solutions. In this paper, we propose two techniques to enhance the speedup of mapping/scheduling solutions: (1) an integrated technique combining task clustering, mapping, and scheduling, and (2) a multiple neighborhood function strategy. Our approach is demonstrated by case studies involving 40 randomly generated task graphs, as well as six applications. Experimental results show that our proposed approach outperforms a separate approach in terms of speedup by up to 18.3% for a system with a microprocessor, a floating-point digital signal processor, and an FPGA. |
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Bibliography: | ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 23 |
ISSN: | 0975-4660 0975-3826 |
DOI: | 10.5121/ijcsit.2012.4111 |