Striving for performance of discrete optimisation via memetic agent-based systems in a hybrid CPU/GPU environment

摘要

Agent-based memetic computational systems have been proven to be an efficient concept for solving complex computational problems. In this paper, we propose and evaluate a new hybrid architecture for such systems that effectively utilise CPU and GPGPU processing power by delegating parallel part of computations to GPGPU. The paper illustrates how to design and implement particular parts of the systems and discusses required conditions for evolutionary parameters and memetic operators. The concept is illustrated with one of the complex discrete problems LABS. (C) 2019 Elsevier B.V. All rights reserved.