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Evolutionary computing assisting in the construction of variability tolerant designs

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If you have a question about this talk, please contact Leandro Minku.

Host: Prof. Xin Yao

Field programmable gate arrays (FPGAs) are widely used in applications where on-line reconfigurable signal processing is required. Speed and function density of FPG As are increasing as transistor sizes shrink to the nano-scale. As these transistors reduce in size, intrinsic variability becomes more of a problem, as every physical instance of a design behaves differently, resulting in a decrease in fabrication yield. This talk describes a software environment that takes into account device variability during the design stages and illustrates how bio-inspired techniques can assist, The talk will continue by describing an adaptive architecture that allows for correction and optimisation of circuits directly in hardware using bio-inspired techniques. Similar to FPG As, the programmable analogue and digital array (PAnDA) architecture introduced here can be reconfigured on a digital level for circuit design. Accessing additional configuration options of the underlying analogue level enables continuous adjustment of circuit characteristics at runtime, which enables dynamic optimisation of the mapped design’s performance. Moreover, the yield of devices can be improved post-fabrication via reconfiguration at the analogue level, which can overcome faults caused by variability and process defects.

This talk is part of the Artificial Intelligence and Natural Computation seminars series.

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