This paper presents a new approach for automatic computation of matching constraints for analog sizing. The method automatically analyzes a circuit netlist to generate sizing constraints. These sizing constraints are considered during a subsequent numerical optimization. It is the first method that computes symmetry constraints for sizing, based on the hierarchical structure of the circuit and a qualitative signal flow. As a unique feature, the method is capable of handling multiple signal and feedback paths, leading to multiple symmetry axes. It can be applied to linear and nonlinear circuits and any available sizing algorithm. Experimental results show that the runtime of analog sizing, as well as of result quality, are greatly improved.

This paper presents a new method to automatically generate hierarchical placement rules, which are crucial for a successful analog placement. The method is based on a novel symmetry computation method, introducing the structural signal flow graph. Five types of proximity, matching and symmetry constraints are determined. According to the priority of the constraint types, a constraint requirement graph and a hierarchical partitioning of the circuit into matching, proximity and symmetry groups is then automatically computed. Based on experimental results with a state-of-the-art placement tool, we show that the new approach generates more placement rules and can lead to better circuit performance and parametric yield according to post-layout simulation.

This paper presents a new method to automatically generate hierarchical placement rules, which are crucial for a successful analog placement.

The analog placement algorithm Plantage, presented in this paper, generates placements for analog circuits with comprehensive placement constraints. Plantage is based on a hierarchically bounded enumeration of basic building blocks, using B*-trees. The practically relevant solution space is thereby enumerated quasi-complete. The sets of possible placements of the basic building blocks are represented and combined in a new efficient way, using enhanced shape functions. The result of Plantage is the Pareto front of placements with respect to different aspect ratios. The whole approach is deterministic, in contrast to existing analog placement algorithms.