用神经网络求解性能驱动的电路划分问题

文中考虑一种以连线代价最小目标的，以面积和时延为约束的，划分块与划分块之间有确定和拓扑关系的电路划分问题，提出了一个性能驱动电路划分的均场退火算法。算法通过换拉矩阵把问题映射为神经网络，并建立了包含优化目标项，面积约束项和时延约束项的能量函数，再用均场退火方程失代求解。

A NEURAL NETWORK APPROACH FOR PERFORMANCE-DRIVEN CIRCUIT PARTITIONING

Here proposed is a mean field annealing approach to the performance driven circuit partitioning, in which the object is to minimize the total routing cost between cells, the constraints are timing and area, and the partitions have intrinsic topological relationships. In the algorithm, a permute matrix is used to map the problem to neural network,and the energy function including object item, area constrained item,and the timing constrained item is presented, and then iteration procedure is put into practice with the mean annealing equation. Normalization of neurons proves that one cell only can be assigned to one partition. The algorithm is programmed with Visual C , and experimental result shows that it is an effective method. In addition, the human and machine combined partitioning conception is also discussed.