A programming and simulation model of a SIMD-MIMD architecture for image processing

Typical real time computer vision tasks require huge amount of processing power, larger than can be achieved by current state of the art workstations. Parallel processing appears to be the only solution (economically) to obtain sufficient processing power for handling real time computer vision applications. The nature of processing in a typical computer vision algorithm usually ranges from many large small arithmetic operations (fine grain parallelism) to symbolic operations (coarse grain parallelism). Yet, normal general purpose parallel computers usually only suit one type of processing, not the whole range. The ESPRIT basic research project SM-IMP looks at a scalable combined SIMD-MIMD architecture for image processing, suiting both fine grain and coarse grain parallelism and capable of offering sufficient processing performance for real time computer vision applications. A programming model and simulation model for this SIMD-MIMD architecture are proposed.