Efficient Implementation of Image Processing Algorithms on Linear Processor Arrays Using the Data Parallel Language IDC

SIMD linear processor arrays (LPAs) have received a great deal of interest as a suitable parallel architecture for image processing. However, few possess a high level programming environment support, and tlie range of image processing tasks which can be efficiently i~nplenlented is unclear. In this paper, we first describe a data parallel language succinctly designed for a virtual LPA, and also a compiler for an existing LPA. Next, we provide a guideline for pamllel SIMD linear array algorithm developnlent using the language. The guideline is consisted of five hasic parallelizing methods, I>y using which efficient implementations are shown for each category of low to intermediate level image operations. We also suggest that further improvement of performance on LPAs can be acliicvcd, I>y architectural supports for reducing the control overhead of some parallelizing methods.