A precise simulation requires a large amount of input data such as geometrical descriptions of the crystal structure, the external forces and loads, and quantitative properties of the material. Although some powerful applications already exist for research purposes, they are not widely used in education due to complex structure and unintuitive operation. To cater to the generic user base, a front-end application for material simulation software is introduced. With a graphic interface, it provides a more efficient way to conduct the simulation and to educate students who want to enlarge knowledge in relevant fields. We first discuss how we explore the solution for the front-end application and how to develop it on top of the material simulation software developed by mechanical engineering lab from Georgia Tech Lorraine. The user interface design, the functionality and the whole user experience are primary factors determining the product success or failure. This material simulation software helps researchers resolve the motion and the interactions of a large ensemble of dislocations for single or multi-layered 3D materials. However, the algorithm it utilizes is not well optimized and parallelized, so its performance of speedup cannot scale when using more CPUs in the cluster. This problem leads to the second topic on scientific computing, so in this thesis we offer different approaches that attempt to improve the parallelization and optimize the scalability.

The emergence of a multitude of bandwidth hungry multimedia applications has ex- acerbated the need for multi-gigabit wireless solutions and made it out of the reach of conventional WLAN technology (802.11a, b and g). This thesis presents a system on chip which demonstrates the potential of 60GHz transceivers. This system is based on an FPGA board on which a GNU/Linux kernel has been run. This document will give some insight on the design process as well as on the finished product. Both the hardware and the software parts of the design are presented. This document is organized as follow. Chapter I presents an overview of the problem to be solved and some insight on the motivation to work at 60GHz. Chapter II gives a high level view of the multimedia processor that has been designed and implemented. Chapters III and IV respectively give more detail on the hardware parts and on the software components of the pro ject. Finally, Chapter V draws the conclusion of this work and presents the future of the work that has been started to enhance this multimedia processor.

<p>Self-tuning has been an elusive goal for operating systems and is becoming a pressing issue for modern operating systems. Well-trained system administrators are able to tune an operating system to achieve better system performance for a specific system class. Unfortunately, the system class can change when the running applications change. The model for self-tuning operating system is based on a monitor-classify-adjust loop. The idea of this loop is to continuously monitor certain performance metrics, and whenever these change, the system determines the new system class and dynamically adjusts tuning parameters for this new class. This thesis described KernTune, a prototype tool that identifies the system class and improves system performance automatically. A key aspect of KernTune is the notion of Artificial Intelligence oriented performance tuning. Its uses a support vector machine to identify the system class, and tunes the operating system for that specific system class. This thesis presented design and implementation details for KernTune. It showed how KernTune identifies a system class and tunes the operating system for improved performance.</p>

This thesis investigates indexing and partitioning schemes for high dimensional scientific computational problems. Building on the foundation offered by Mathematics of Arrays (MoA) for tensor-based computation, the ultimate contribution of the thesis is a unified partitioning scheme that works invariant of the dataset dimension and shape. Consequently, portability is ensured between different high performance machines, cluster architectures, and potentially computational grids. The Multiple Sequence Alignment (MSA) problem in computational biology has an optimal dynamic programming based solution, but it becomes computationally infeasible as its dimensionality (the number of sequences) increases. Even sub-optimal approximations may be unmanageable for more than eight sequences. Furthermore, no existing MSA algorithms have been formulated in a manner invariant over the number of sequences. This thesis presents an optimal distributed MSA method based on MoA. The latter offers a set of constructs that help represent multidimensional arrays in memory in a linear, concise and efficient way. Using MoA allows the partitioning of the dynamic programming algorithm to be expressed independently of dimension. MSA is the highest dimensional scientific problem considered for MoA-based partitioning to date. Two partitioning schemes are presented: the first is a master/slave approach which is based on both master/slave scheduling and slave/slave coupling. The second approach is a peer-to-peer design, in which the scheduling and dependency communication are calculated independently by each process, with no need for a master scheduler. A search space reduction technique is introduced to cater for the exponential expansion as the problem dimensionality increases. This technique relies on defining a hyper-diagonal through the tensor space, and choosing a band of neighbouring partitions around the diagonal to score. In contrast, other sub-optimal methods in the literature only consider projections on the surface of the hyper-cube. The resulting massively parallel design produces a scalable solution that has been implemented on high performance machines and cluster architectures. Experimental results for these implementations are presented for both simulated and real datasets. Comparisons between the reduced search space technique of this thesis with other sub-optimal methods for the MSA problem are presented.

Thesis (M.S.)--State University of New York at Binghamton, Department of Computer Science, Thomas J. Watson School of Engineering and Applied Science, 2006. / Includes bibliographical references.

Thesis (Ph. D.)--Ohio State University, 2008. / Title from first page of PDF file. Includes bibliographical references (p. 140-144).

Thesis (Ph. D.)--Carleton University, 2004. / Includes bibliographical references (p. 155-166). Also available in electronic format on the Internet.

Thesis (M.S.)--Oregon State University, 2004. / Printout. Includes bibliographical references (leaf 54). Also available on the World Wide Web.

Thesis (M.S.)--Rutgers University, 2007. / "Graduate Program in Electrical and Computer Engineering." Includes bibliographical references (p. 114-115).

Thesis (M. S.)--Electrical and Computer Engineering, Georgia Institute of Technology, 2009. / Committee Member: Chang, Gee-Kung; Committee Member: Hasler, Paul; Committee Member: Laskar, Joy. Part of the SMARTech Electronic Thesis and Dissertation Collection.