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Optimizing Scheduling and Intercluster Connection for Application-Specific DSP Processors.

Authors :
Cathy Qun Xu
Chun Jason Xue
Jingtong Hu
Edwin Hsing-Mean Sha
Source :
IEEE Transactions on Signal Processing; Nov2009, Vol. 57 Issue 11, p4538-4547, 10p, 4 Black and White Photographs, 1 Chart
Publication Year :
2009

Abstract

Signal processing applications have high instruction level parallelism (ILP) and real-time performance requirements. Embedded and application specific multicluster architecture is desirable to provide the large computation power that these applications need. As technology moves to deep submicron level, it becomes more important and challenging to design an efficient intercluster connection network to satisfy the rapid growing intercluster data transfer needs under the power and cost constraints. This paper addresses the automatic generation of intercluster connection network with partially connected buses. An application specific approach is proposed in this paper to determine the minimum number of required partially connected buses without performance degradation for a given schedule in polynomial time. The intercluster connection topology is then generated with the determined minimum number of partially connected buses to minimize the connection bus segments. Further, a scheduling algorithm is presented in this paper to minimize the intercluster communication needs for the given application and to reduce the minimum number of partially connected buses required in the interciuster connection network under schedule length constraint. Experimental results indicate that an average reduction up to 50.6% in the number of minimum required buses and an average reduction of 64.5% in bus segments can be achieved compared to commonly used intercluster communication aware scheduling techniques and as soon as possible (ASAP) data transfer scheme. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
1053587X
Volume :
57
Issue :
11
Database :
Complementary Index
Journal :
IEEE Transactions on Signal Processing
Publication Type :
Academic Journal
Accession number :
45441580
Full Text :
https://doi.org/10.1109/TSP.2009.2024870