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.

Creator

• Skjerven, Brian M.

Contributors

• Walker, Homer F.

Degree

• MS

Unit

• Mathematical Sciences

Publisher

• Worcester Polytechnic Institute

Language

• English

Identifier

• etd-060507-172337

Keyword

• High-performance computing
• Scientific computation
• Computational biology
• Visualization
• Numerical analysis

Advisor

• Walker, Homer F.

Defense date

• 2007-06-11

Year

• 2007

Date created

• 2007-06-05

Resource type

• Report

Rights statement

• In Copyright