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A Multiple Model Reference Adaptive Control (MMRAC) with Genetic Algorithm (GA) based model selection scheme for a F-16 flight surface control system has been proposed. It is an extension of previously reported work . It simulates all three rotation motion controls such as pitch, roll and yaw. It then incorporates numerical solution of differential equation using 4th order Runge-Kutta algorithm in the simulation. This paper focuses on implementation of the proposed algorithm on a 4-core-Architecture of Intel® i5 CPU. The sequential code was first written in C++ on .NET Framework 4. Parallel processing approaches were exploited for parallelization of the control system. Several optimization techniques were used to achieve the maximum speed up. The parallelized algorithm is appropriate for real time computation.