Efficient Model Order Reduction of Electrical Networks with Many Ports.

摘要

Model order reduction of electrical networks plays a key role in accelerating circuit simulations. Traditional reduction methods, however, do not scale well with network size and number of ports, since they utilize dense matrix manipulations that require a lot of memory and CPU time. In addition, the obtained reduced models are dense and thus inefficient in subsequent simulations. In this thesis, we propose TurboMOR, an efficient reduction technique for RC networks with many ports. TurboMOR performs reduction efficiently by avoiding dense matrix manipulations. TurboMOR overcomes the scalability and accuracy limitations of previously proposed methods. TurboMOR guarantees passivity by construction and leads to sparse models that run efficiently in conventional circuit simulators.