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With the proliferation of parallel computing, parallel computer-aided design (CAD) has received significant research interests. Transient transistor-level circuit simulation plays an important role in digital/analog circuit design and verification. Increased VLSI design complexity has made circuit simulation an ever growing bottleneck, making parallel processing an appealing solution for addressing this challenge. In this thesis, we propose and develop a parallel and distributed multi-algorithm approach to leverage the power of multi-core computer clusters for speeding up transistor-level circuit simulation. The targeted multi-algorithm approach provides a natural paradigm for exploiting parallelism for circuit simulation. Parallel circuit simulation is facilitated through the exploration of algorithm diversity where multiple simulation algorithms collaboratively work on a single simulation task. To utilize computer clusters comprising of multi-core processors, each algorithm is executed on a separate node with sufficient system resource such as processing power, memory and I/O bandwidth. We propose two communication schemes, namely master-slave and peer-to-peer schemes, to allow for inter-algorithm communication. Compared with the shared-memory based multi-algorithm implementation, the proposed simulation approach alleviates cache/memory contention as a result of multi-algorithm execution and provides further runtime speedups.

In recent years there has been increased interest in the development of sensorless switched reluctance machine drives. The proper operation of a switched reluctance machine (SRM) requires knowledge of the position of the rotor of the machine. The inclusion of a physical position sensor compromises the inherent robustness of this type of machine. Thus, there has been a need to develop techniques to estimate the position of the rotor in SRM drives. Switched reluctance machines are able to operate over a large range in speed. A fully loaded SRM is typically designed to saturate the ferromagnetic material that comprises the stator and rotor of the machine whereas a lightly loaded machine does not. Therefore, the model of the machine should be able to handle both a large range in frequency and input excitation levels of the magnetic material in the machine. The development of a new dynamic circuit-based ferromagnetic model is described in this thesis. The investigation of the behaviour of 24 gauge M19 silicon steel led to the conclusion that, for this material, a circuit model that has static parameters is unable to accurately reproduce the behaviour of the actual material over a large range of input frequencies and excitation levels without resorting to retuning the parameters of the model. This thesis provides two new mechanisms that dynamically adjust the resistance values of the flux tubes of the model. Comparisons using a normalized vertical least-squares metric between the newly proposed dynamic model and a model that has static resistance values clearly show the improvement that is gained by using these mechanisms. A practical implementation of the new model is also given. Timing using a general purpose CPU shows that this implementation of the model will most likely be able to be used as part of a multi-phase lumped parameter model for a SRM in realtime.

Thesis (M.S.) -- Worcester Polytechnic Institute. / Keywords: statistical model; mismatch; bipolar transistor. Includes bibliographical references (p.29).

Thesis (Ph. D.)--University of Washington, 1997. / Vita. Includes bibliographical references (leaves [117]-123).

Thesis (M. S.)--Chemical Engineering, Georgia Institute of Technology, 2009. / Committee Chair: Kohl, Paul; Committee Member: Bidstrup Allen, Sue Ann; Committee Member: Fuller, Thomas; Committee Member: Hesketh, Peter; Committee Member: Hess, Dennis; Committee Member: Meindl, James.

Thesis (Ph. D.)--University of Washington, 2005. / Vita. Includes bibliographical references (leaves 110-118).