Parallel and Distributed Computing Techniques in Biomedical Engineering

i Declaration The experiments in this thesis constitute work carried out by the candidate unless otherwise stated. The thesis is less than 30,000 words in length, exclusive of tables, figures, bibliography and appendices, and complies with the stipulations set out for the degree of Master of Engineering by the National University of Singapore. well as technical and non-technical advices have always been an important support for my research. Special thanks to him for helping me through my difficult time of supervisor change. I would also like to express sincere thanks to Duc Duong-Hong for helping me through many questions regarding biofluid and especially fiber suspensions modelling. Most importantly, my special thanks to my family and my girlfriend. Without your support, nothing could be achievable. Abstract Biomedical Engineering, usually known as Bioengineering, is among the fastest growing and most promising interdisciplinary fields today. It connects biology, physics, and electrical engineering, for all of which biological and medical phenomena, computation, and data management play critical roles. Computation methods are widely used in the research of bioengineering. Typical applications range from numerical modellings and computer simulations, to image processing and resource management and sharing. The complex nature of biological process determines that the corresponding computation problems usually have a high complexity and require extraordinary computing capability to solve them. Parallel and Distributed computing techniques have proved to be effective in tackling the problem with high computational complexity in a wide range of domains, including areas of computational bioengineering. Furthermore, recent development of cluster computing has made low-cost supercomputer built from commodity components not only possible but also very powerful. Development of modern distributed computing technologies now allows aggregating and utilizing idle computing capability of loosely-connected computers or even supercomputers. This means employing parallel and distributed computing techniques to support computational bioengineering is not only feasible but also cost-effective. In this thesis, we introduce our effort to utilize computer cluster for 2 types of computational bioengineering problems, namely intensive numerical simulations of National University of Singapore vii fiber suspension modelling, and multiple-frame laser speckle image processing. Focus has been put on identifying the main obstacles of using low-end computer clusters to meet the application requirements, and techniques to overcome these problems. Efforts have also been made to generate easy and reusable application frameworks and guidelines on which similar bioengineering problems can be systematically formulated and solved without loss of performance. Our experiments and observations …