Document Type masters report Author Name Skjerven, Brian M. URN etd-060507-172337 Title A Parallel Implementation of an Agent-Based Brain Tumor Model Degree MS Department Mathematical Sciences Advisors Homer Walker, Advisor Keywords Visualization Numerical analysis Computational biology Scientific computation High-performance computing Date of Presentation/Defense 2007-06-11 Availability unrestricted
The complex growth patterns of malignant brain tumors can present challenges in developing accurate models. In particular, the computational costs associated with modeling a realistically sized tumor can be prohibitive. The use of high-performance computing (HPC) and novel mathematical techniques can help to overcome this barrier. This paper presents a parallel implementation of a model for the growth of glioma, a form of brain cancer, and discusses how HPC is being used to take a first step toward realistically sized tumor models. Also, consideration is given to the visualization process involved with large-scale computing. Finally, simulation data is presented with a focus on scaling.
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