APPLICATION OF SELF-ORGANIZING NEURAL NETWORK IN TIMING-DRIVEN PLACEMENT
Kohonen神经网络在时延驱动布局中的应用

In this paper, a timing-driven placement algorithm using Kohonen self-organizing is proposed. The object function of the algorithm is to minimize the critical nets. In the algorithm, net-based similarity vector is presented. Compared with the cell-based similarity vector, net-based similarity vector not only can directly deal with the multi-terminal nets, but also can describe the information about timing. The experimental result shows that it is a effective method.