Warp as a machine for low-level vision

Abstract

Warp is a programmable systolic array processor. One of its objectives is to support computer vision research. This paper shows how the Warp architecture can be used to fulfill the computational needs of low-level vision. We study the characteristics of low-level vision algorithms and show how they lead to requirements for computer architecture. These requirements are met by Warp. We then describe how the Warp system can be used. Warp programs can be classified in two ways: chained versus severed, and heterogeneous versus homogeneous. Chained and severed characterize the degree of interprocessor dependency, while heterogeneous and homogeneous characterize the degree of similarity between programs on individual processors. Taken in combination, these classes give four user models. Sophisticated programming tools are needed to support these user models.