Algorithms for massively parallel image processing architectures

Abstract

The complexity of efficiently programming massively parallel machines is illustrated by presenting a number of new algorithms. These algorithms deal with computational geometry, data histogramming, list manipulation, and other problems or operations that arise in computer vision tasks. All of the algorithms presented use a divide-and-conquer strategy, and they all use routines that solve a problem of size M using a machine of size N, where M < N. In some of the algorithms, the extra processors are used to perform more than M calculations in parallel. In other algorithms, the extra processors are used to improve the speed of interprocessor communication.