Self organization is the property of some natural systems to organize themselves without a central coordination unit to perform specific tasks. Swarm Intelligence is a bioinspired paradigm coming from the observation of natural swarms, such as honey bees and bird flocks. Swarms exploit self organization to achieve coordination, speed-up and fault tolerance. This interesting paradigm has been applied in different research fields, mainly in robotics and optimization algorithms. Our pioneering studies about the application of this powerful paradigm to digital VLSI systems demonstrated that Swarm Intelligence can be applied to the design of scalable computing architectures composed of a large set of self-coordinated hardware agents. In this Chapter we present this approach with a review of our research works in this field from the first explorations to the latest results: the FPGA implementation of a coprocessing architecture expressly conceived resorting to the Swarm Intelligence principles. Some experimental results are presented to evaluate the main features of this innovative approach, which shows interesting performance improvements without any programming effort and without complex tools for compilation and mapping, compared to other state-of-the-art coprocessing architectures.
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|Titolo:||Self-coordinated on-chip parallel computing: A swarm intelligence approach|
|Data di pubblicazione:||2010|
|Tipologia:||2.1 Contributo in volume (Capitolo o Saggio)|