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MogaMap: An application of multi-objective genetic algorithm for LUT-based FPGA technology mapping

In this paper we present MogaMap, an algorithm based on pre-selection of cuts and multiobjective genetic algorithm to solve the problem of Look-Up Table (LUT) Technology Mapping for FPGA. Besides that, a new cost function is proposed in the clustering phase to reduce the energy consumption within the FPGA. The simulation results show that, on average, our technique is able to reduce the critical path by 35% while reduces the energy consumption by 8% when compared to WireMap with toggle optimization for area and AAPack in VTR flow.