Expert Systems for the Scheduling of Image Processing Tasks on a Parallel Processing System
Abstract
The algorithms used in image processing are becoming longer and more complex as researchers strive to create vision systems whose performance rivals that of the human's. The size and complexity of these algorithms, however, generally do not allow them to be run in 'real time' on any sequential (Von Neumann) machine. Image processing algorithms tend to be highly parallel in nature. One can hope, therefore, that the recent advances in parallel computing will bring significant speed-ups in the execution times of image processing algorithms. However, it is usually the case that image processing systems are extremely computationally intensive. Even with speed-ups brought about by parallel computers, there is a demand for an advisory system that optimizes the execution time of image processing algorithms. A reasonable goal for such a system is as follows. Given a list of all the subtasks that need to be run for a given image processing task, produce an initial schedule and configuration and then adjust the schedule and configuration during runtime based on the current configuration and intermediate processing results. The proposed work will proceed towards this goal on several fronts. Theses.
Document Details
- Document Type
- Technical Report
- Publication Date
- Dec 01, 1986
- Accession Number
- ADA208613
Entities
People
- Francis J. Weil
Organizations
- Purdue University