Flexibly Coupled Multiprocessors for Image Processing

Abstract Two hardware mechanisms are mainly used for data sharing among processing elements in multiprocessors: message passing in loosely coupled multiprocessors and shared memory in tightly coupled multiprocessors. The former has communication overhead and the latter has shared memory contention. Moreover, in image processing, inefficient data input and output schemes are also limitations on performance. In this paper, Flexibly (Tightly/Loosely) Coupled Multiprocessors (FCM) for image processing are proposed in order to alleviate these disadvantages. A variable space memory scheme , in which a set of adjacent memory modules can be merged by a dynamically partitionable bus, is proposed to realize FCM. These architectures are quantitatively analyzed and simulated on the iPSC/1 (Intel's Personal SuperComputer), a hypercube multiprocessor. Parallel algorithms for region labeling and median filtering are simulated on the proposed architectures. The performance of FCM shows remarkable improvement over that of iPSC/1.