The CLA-EC is a model obtained by combining the concepts of cellular learning automata and evolutionary algorithms. The parallel structure of the CLA-EC makes it suitable for hardware-based applications including evolvable hardware. In this paper, based on the SIMD model, a parallel architecture is proposed and implemented on FPGA. Simulation results show that the proposed architecture can solve optimization problems thousands times faster than the sequential implementations.
['Arash Hariri', 'Reza Rastegar', 'Morteza Saheb Zamani', 'Mohammad Reza Meybodi']
Parallel hardware implementation of cellular learning automata based evolutionary computing (CLA-EC) on FPGA