MGAP applications in machine perception

Since image processing tasks in machine perception are computationally intensive, massively parallel processing is often employed to exploit the inherent parallelism. Some pioneering researchers have developed massively parallel processing systems including the CLIP family, the MPP, and the CM. All of these systems, however, are hard to use in machine perception systems because of their expensiveness and physical size. To tackle these problems we developed an inexpensive and easily portable massively parallel processing system, the MGAP (Micro Grained Array Processor). The MGAP is a very fine-grained, massively parallel, programmable array processor which is designed to be used as a low-cost massively parallel co-processor board in a desk-top workstation. In this paper, we discuss the versatile applications of the MGAP for image processing subtasks including an efficient histogramming algorithm, the systolic 2-D Discrete Cosine Transform (DCT), and the Dynamic Space Warping Algorithm (DSWA).