Iterative placement improvement by network flow methods

We describe an efficient iterative improvement procedure for row-based cell placement with special emphasis on the objective function used to model net lengths. Two new net models are introduced and we prove theoretically that the net models are accurate approximations of the widely used half perimeter of a rectangle enclosing all pins of a net. In addition, unlike the half perimeter model, our net models allow us to compute costs for assigning cells to locations independently for all cells to be placed simultaneously. This offers our algorithm an important advantage compared to other iterative improvement techniques: many cells can be placed simultaneously by formulating placement as a network flow problem. This makes our algorithm more independent from a processing sequence than standard iterative improvement techniques. Finally, we compare our method to some existing algorithms including TimberWolfSC 5.4. We ran all of the algorithms on the SIGDA Benchmark Suite. We found that our method produced solutions with up to 23% less layout area while using an order of magnitude less running time compared to TimberWolfSC 5.4