<title>Software development tools for implementing vision systems on multiprocessors</title>

Abstract

Parallel processing has been widely accepted as the approach to providing the necessary computational power to solve computer vision systems problems. Although several projects are underway to develop new architectures for computer vision, tools to effectively use those systems or commercially available multiprocessors are limited or non-existent. Unless we can develop efficient methods for mapping vision algorithms and developing programs on these architectures, the performance gains from parallel processing will be limited, and will be beyond the reach of a non-expert in parallel processing. This paper presents a design for a software development environment (SDE) for implementing vision systems applications on multiprocessors. The SDE design exploits characteristics of vision systems, and uses a classification scheme for vision algorithms to develop a parallelization and performance evaluation tool. These tools use databases that store knowledge of parallelization for different known computations on common architectures. The parallelization and performance evaluation tools use this knowledge to guide a user interactively parallelize algorithms. Some parts of SDE are currently operational and others still need to be developed.