An Elitist Non-Dominated Multi-Objective Genetic Algorithm Based Temperature Aware Circuit Synthesis
At sub-nanometre technology, temperature is one of the important design parameters to be taken care of during the target implementation for the circuit for its long term and reliable operation. High device package density leads to high power density that generates high temperatures. The temperature of a chip is directly proportional to the power density of the chip. So, the power density of a chip can be minimized to reduce the possibility of the high temperature generation. Temperature minimization approaches are generally addressed at the physical design level but it incurs high cooling cost. To reduce the cooling cost, the temperature minimization approaches can be addressed at the logic level. In this work, the Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) based multi-objective heuristic approach is proposed to select the efficient input variable polarity of Mixed Polarity Reed-Muller (MPRM) expansion for simultaneous optimization of area, power, and temperature. A Pareto optimal solution set is obtained from the vast solution set of 3n (‘n’ is the number of input variables) different polarities of MPRM. Tabular technique is used for input polarity conversion from Sum-of-Product (SOP) form to MPRM form. Finally, using CADENCE and HotSpot tool absolute temperature, silicon area and power consumption of the synthesized circuits are calculated and are reported. The proposed algorithm saves around 76.20% silicon area, 29.09% power dissipation and reduces 17.06% peak temperature in comparison with the reported values in the literature.
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International Journal of Interactive Multimedia and Artificial Intelligence
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