Machine-independent image processing: Performance of apply on diverse architectures

✍ Scribed by Richard S. Wallace; Jon A. Webb; I-Chen Wu

• Publisher: Elsevier Science
• Year: 1989
• Weight: 571 KB
• Volume: 48
• Category: Article
• ISSN: 0734-189X
• DOI: 10.1016/s0734-189x(89)80041-6

✦ Synopsis

One of the most important obstacles standing in the way of widespread use of parallel computers for low-level vision is the lack of a programming language that can be mapped efficiently onto different computer architectures which is suited for low-level vision. The Apply language has been designed and implemented to perform such operations. We demonstrate its capabilities by comparing the performance of the Hughes HBA, the Carnegie Mellon Warp machine, and the Sun 3 on a large set of low-level vision programs. In order to demonstrate its efficiency, we also compare performance of the Sun code with routines of similar function written by professional programmers.