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Zero-Change Netlist Transformations: A New Technique for Placement Benchmarking

By Andrew B. Kahng and Sherief Reda


In this paper we introduce the concept of zero-change netlist transformations to (1) quantify the suboptimality of existing placers on artificially constructed instances, and (2) “partially ” quantify the suboptimality of placers on synthesized netlists from arbitrary netlists by giving lower bounds to the suboptimality gap. Given a netlist and its placement from a placer, we formally define a class of netlist transformations that synthesize a different netlist from the given netlist but yet the new netlist has the same Half-Perimeter Wire Length (HPWL) on the given placement. Furthermore, and more importantly, the optimal HPWL value of the new netlist is no less than that of the original netlist. By applying our transformations and re-executing the placer, we can interpret any deviation in HPWL as a lower bound to the gap from the optimal HPWL value of the new synthesized netlist. Our transformations allow us to (1) increase the cardinality of hyperedges, (2) reduce the number of hyperedges, and (3) increase the number of two-pin edges, while maintaining the placement HPWL constant. We also develop methods that apply zero-change netlist transformations to synthesize netlists having typical netlist statistics. Furthermore, we extend our approach to estimate suboptimality of other metrics such as rectilinear minimum-spanning tree (RMST) and minimum-Steiner tree. Using these transformations, the suboptimality of some of the existing academic placers (FengShui [35], Capo [4], mPL [10], Drago

Year: 2011
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