Development of a parallel stochastic method with learning for large-scale optimization based on biological evolution

本课题研究了一种新的基于生物机制的并行随机方法的开发，并将其应用于VLSI布局中。该方法在并行计算机上进行了大规模的并行计算，并将其应用于VLSI布局布图问题。仿真实验验证了该方法的有效性和实用性。

The project has studied the development of a new parallel stochastic method based on biological mechanism and applied to VLSI layout.Practically speaking, we combined a genetic algorithm (GA) with immune mechanism. This combination makes it possible to search a global minimum in the cost landscape with high accuracy.The proposed method has made massive parallel computation using a parallel computer.We applied it to floorplan problems of VLSI layout. The simulation experiments verified the effectiveness and the usefulness of the proposed method.