摘要
文中提出了一个宏单元布局的均场退火网络求解方法．算法用一个三维二值换位矩阵将问题映射为神经网络，建立包含时延约束、重叠约束和优化目标的能量函数，再用均场退火方程迭代求解．每个单元只能放置在布局平面一个位置上的约束用神经元归一化的方法解决．算法能支持各种来自实际应用的需要，如单元可变长宽比、单元的翻转与旋转、引出端位置和任意单元的形状等．该算法已用ＶｉｓｕａｌＣ＋ ＋ 编程实现，实验结果表明。
In this paper, a mean field annealing neural network approach for the timing driven macro cell placement problem is proposed. In the algorithm, a three dimensional permute matrix of binary variables is used to map the problem to the neural network, the energy function including object item, overlap constrained item, and timing constrained item is presented, and then iteration procedure is put into practice with the mean annealing equation. Normalization of neurons proves that only one cell can be assigned to one position in the placement grid. Some practical constraints such as variable block aspect ratio, rotations and reflections, terminal locations, and block shape, can be supported. The algorithm is programmed with Visual C++ language, and experimental result shows that it is an effective method.
出处
《计算机研究与发展》
EI
CSCD
北大核心
2000年第1期23-29,共7页
Journal of Computer Research and Development
基金
浙江省自然科学基金!(项目编号961207257-002)
