VLSI cell placement on arbitrarily-shaped rectilinear regions using neural networks with calibration nodes

Abstract

In VLSI or PCB layout, one often encounters a region that is either of rectilinear shape or can be approximated by a rectilinear region. Although many placement methods have been proposed, most of them are applicable only to rectangular regions. For these algorithms to be applied to a rectilinear region, two processing steps, region partitioning and rectangular region cell placement are necessary. Hence, the placement results are so far dependent on the locations of the regions partitioned and frequently become trapped in local minima. Recently, neural networks have been suggested as a new way to resolve the cell placement problem. This paper proposed a unified modeling method that uses a neural net model with additional calibration nodes to model rectilinear region cell placement. In this method, the ideal distance between cells is preserved to simultaneously minimize both the total wire length and the module overlap. Unlike traditional approaches, the proposed algorithm requires only a single processing step. Experiments have been conducted to verify the performance of the proposed algorithm. The total wire length obtained by our method is shorter than those generated by previous methods.