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	University of Nevada\\
	Reno
	
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	{\Large \bf A Parallel Linear Octree \\
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		Collision Detection Algorithm}
	
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	A thesis submitted in partial fulfillment of the\\
	requirements for the degree of Master of Science\\
	with a major in Computer Science.
	
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	by
	
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	Benjamin J. Lucchesi
	
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	Dr. Frederick C. Harris, Jr.,  Thesis advisor
	
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	May 2002
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\copyright \ Benjamin James Lucchesi, 2002
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	The thesis of Benjamin J. Lucchesi is approved:

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	Thesis Advisor
	
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	Department Chair
	
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	Dean, Graduate School
	
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	University of Nevada\\
	Reno
	
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	May 2002
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	{\bf Abstract}
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	In this thesis a new collision detection algorithm is presented
	that solves the all-pairs collision detection problem using
	parallel processing. The design of the algorithm is based
	on a linear octree and runs in parallel with a theoretical
	performance of ${\cal O}(( n\ log \ n)/k)$ run time.  The
	algorithm has been implemented as a collision detection system
	using object-oriented design techniques and a client-server
	architecture. The architecture of the collision detection
	system is designed to use the parallel capabilities of both
	shared-memory, multi-processor computers and clusters of networked
	computers. Additionally, the modularity of the collision detection
	system gives application developers the flexibility to choose the
	level at which the collision detection system is integrated into
	an application. Using the collision detection system, experimental
	results have been generated that demonstrate how the algorithm
	performs according to the calculated theoretical performance.

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%	{\bf Dedication} 
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	{\bf Acknowledgements}
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	I would like to thank Professor Harris, my advisor, for his
	generous help and guidance throughout my education, and for
	supporting my research interests in graphics and virtual reality.

	I am very grateful to Professor Wishart and Professor Edberg
	for their valuable time, suggestions, and for serving on my 
	committee.
 
	I would like to thank my parents for supporting me throughout
	my education and for their unique form of encouragement during
	difficult times. I really would like to thank them for not selling
	my car.

	I would like to thank Maggie Jameson for her hard work and
	guidance during the editing stage of this thesis.

	I would also like to thank Professor Harris' wife for her
	willingness to proofread this thesis, and her humorous insights
	and comments.

	Finally, I would like to thank Rong Fan for her moral support
	and endless patience throughout this research project.
