A Three-Dimensional Computational Model for the Growth of Multicellular Tissues and Its Parallel Implementation on a Cluster

Candidate: Lenny Tang
Type: Master of Science (MSc), School of Interactive Arts and Technology
Date: May 10, 2007
Senior Supervisor: Dr. Belgacem Ben Youssef
Thesis: Download Thesis Document

Abstract

We report the development of a computational model for the growth of multicellular tissues using a discrete approach based on cellular automata to study the tissue growth rates and population dynamics of two different populations of migrating and proliferating mammalian cells. Cell migration is modeled using a discrete-time Markov chain approach and each population of cells has its own division and motion characteristics based on experimental data. A large number of parameters allow for a detailed study of the population dynamics. This permits the exploration of the relative influence of various system parameters on the proliferation rate as well as the average cell-population speed of locomotion. In addition to a sequential implementation, we developed efficient parallel code for a Beowulf Cluster using the Message Passing Interface (MPI). We present the sequential and parallel results and compute the speedup and efficiency of the parallel algorithm on the Cluster.