Performance evaluation and optimization in low-cost cellular SIMD systems

Low-cost massively parallel architectures are generally characterized by a number of processors which is often far lower that the size of the data set, and by a limited amount of memory owned by each Processing Element. As a consequence, low-cost mesh-connected architectures can utilize only a specific processor virtualization mechanism which is based on the sequential scanning of the data set stored in an external memory. As a consequence of this virtualization mechanism, applications must be developed according to some precise criteria. This paper presents the optimization of some key parameters for the improvement of system performance. These optimizations are validated through an image processing case study.