Title :
Mapping computer-vision-related tasks onto reconfigurable parallel-processing systems
Author :
Siegel, Howard Jay ; Armstrong, James B. ; Watson, Daniel W.
Author_Institution :
Sch. of Electr. Eng., Purdue Univ., West Lafayette, IN, USA
Abstract :
A tutorial overview of how selected computer-vision-related algorithms can be mapped onto reconfigurable parallel-processing systems is presented. The reconfigurable parallel-processing system assumed for the discussions is a multiprocessor system capable of mixed-mode parallelism; that is, it can operate in either the SIMD or MIMD modes of parallelism and can dynamically switch between modes at instruction-level granularity with generally negligible overhead. In addition, it can be partitioned into independent or communicating submachines, each having the same characteristics as the original machine. Furthermore, this reconfigurable system model uses a flexible multistage cube interconnection network, which allows the connection patterns among the processors to be varied. It is demonstrated how reconfigurability can be used by reviewing and examining five computer-vision-related algorithms, each one emphasizing a different aspect of reconfigurability.<>
Keywords :
computer vision; multiprocessor interconnection networks; parallel machines; parallel programming; MIMD; SIMD; communicating submachines; computer-vision-related algorithms; flexible multistage cube interconnection network; instruction-level granularity; mixed-mode parallelism; multiprocessor system; reconfigurable parallel-processing systems; tutorial overview; Algorithm design and analysis; Computer vision; Concurrent computing; Discrete Fourier transforms; Hardware; Parallel processing; Partitioning algorithms; Prototypes; Switches; Very large scale integration;