Systolic Opportunities for Multidimensional Data Streams

Authors:
Sek M. Chai;D. Scott Wills
Affiliations:
Motorola Labs, Schaumburg, IL;Georgia Institute of Technology, Atlanta
Venue:
IEEE Transactions on Parallel and Distributed Systems
Year:
2002

Citing 19
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Abstract

Portable image processing applications require an efficient, scalable platform with localized computing regions. This paper presents a new class of area I/O systolic architecture to exploit the physical data locality of planar data streams by processing data where it falls. A synthesis technique using dependence graphs, data partitioning, and computation mapping is developed to handle planar data streams and to systematically design arrays with area I/O. Simulation results show that the use of area I/O provides a 16 times speedup over systems with perimeter I/O. Performance comparisons for a set of signal processing algorithms show that systolic arrays that consider planar data streams in the design process are up to three times faster than traditional arrays.