Systolic opportunities for multidimensional data streams

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.