DeMOR: Decentralized model order reduction of linear networks with massive ports

Model order reduction is an efficient technique to reduce the system complexity while producing a good approximation of the input-output behavior. However, the efficiency of reduction degrades as the number of ports increases, which remains a long-standing problem. The reason for the degradation is that existing approaches are based on a centralized framework, where each input-output pair is implicitly assumed to be equally interacted and the matrix-valued transfer function has to be assumed to be fully populated. In this paper, a decentralized model order reduction scheme is proposed, where a multi-input multi-output (MIMO) system is decoupled into a number of subsystems and each subsystem corresponds to one output and several dominant inputs. The decoupling process is based on the relative gain array (RGA), which measures the degree of interaction of each input-output pair. Our experimental results on a number of interconnect circuits show that most of the input- output interactions are usually insignificant, which can lead to extremely compact models even for systems with massive ports. The reduction scheme is very amenable for parallel computing as each decoupled subsystem can be reduced independently.