Optimization by simulated evolution with applications to standard cell placement

A mathematical formulation is presented of the simulated evolution algorithm, a novel optimization technique, followed by a thorough analysis of the associated Markov-chain model. A hierarchical approach is used to solve the placement problem for medium to large circuits which incorporates elements of both placement and circuit partitioning in a single algorithm. It is found that the new hierarchical method not only reduces the overall execution time but also significantly increases the quality of the final result. Its success can be attributed to the fact that it reduces the number of local minima that the optimization algorithm encounters. Therefore, the global structure of the placement can be optimized first, regardless of intermediate limitations imposed by local constraints. By gradually refining the granularity of the optimization method, a solution close to the global minimum can be achieved. A standard cell placement program is described based on the new approach whose preliminary results are comparable to the best simulated annealing algorithms