Two-layer coarse-fine-grid network model for bio-inspired computing systems development

In the last decade or so, biologically inspired techniques have gained a great acceptance as possible solutions for a wide range of challenges in high performance grid-computing systems development. In topic with this novel development paradigm the paper presents a Field Programmable Gate Array (FPGA) processors network-based grid-computing hardware system implementation. This bio-inspired computing platform has been conceived upon a tissue-topology configuration by introducing a novel two-dimensional on two-layer coarse-fine-grid network model (2D2L-CFG). By choosing a design strategy relying on a multi-cellular concept which outlines the versatility of biologically inspired technologies, task allocation, communication, or fault-tolerance problems are solved with high efficiency. Moreover, careful real-time simulations prove that by implementing methods that imitate biological processes, such architectures could be considered to be “intelligent” because of their capability to adapting in response to changes of their surrounding environment. The benefits of this approach are also confirmed by experiments performed on a laboratory-prototype VLSI hardware platform. The results underline that techniques which imitate biological phenomena can offer viable solutions in key areas of grid-computing systems development.