Computer Engineering Commons^™

Exploring Computational Chemistry On Emerging Architectures, David Dewayne Jenkins

Doctoral Dissertations

Emerging architectures, such as next generation microprocessors, graphics processing units, and Intel MIC cards, are being used with increased popularity in high performance computing. Each of these architectures has advantages over previous generations of architectures including performance, programmability, and power efficiency. With the ever-increasing performance of these architectures, scientific computing applications are able to attack larger, more complicated problems. However, since applications perform differently on each of the architectures, it is difficult to determine the best tool for the job. This dissertation makes the following contributions to computer engineering and computational science. First, this work implements the computational chemistry variational …

Parallel For Loops On Heterogeneous Resources, Frederick Edward Weber

Doctoral Dissertations

In recent years, Graphics Processing Units (GPUs) have piqued the interest of researchers in scientific computing. Their immense floating point throughput and massive parallelism make them ideal for not just graphical applications, but many general algorithms as well. Load balancing applications and taking advantage of all computational resources in a machine is a difficult challenge, especially when the resources are heterogeneous. This dissertation presents the clUtil library, which vastly simplifies developing OpenCL applications for heterogeneous systems. The core focus of this dissertation lies in clUtil's ParallelFor construct and our novel PINA scheduler which can efficiently load balance work onto multiple …

Kernel-Assisted And Topology-Aware Mpi Collective Communication Among Multicore Or Many-Core Clusters, Teng Ma

Doctoral Dissertations

Multicore or many-core clusters have become the most prominent form of High Performance Computing (HPC) systems. Hardware complexity and hierarchies not only exist in the inter-node layer, i.e., hierarchical networks, but also exist in internals of multicore compute nodes, e.g., Non Uniform Memory Accesses (NUMA), network-style interconnect, and memory and shared cache hierarchies.

Message Passing Interface (MPI), the most widely adopted in the HPC communities, suffers from decreased performance and portability due to increased hardware complexity of multiple levels. We identified three critical issues specific to collective communication: The first problem arises from the gap between logical collective topologies and …

Extending Structural Learning Paradigms For High-Dimensional Machine Learning And Analysis, Christopher Todd Symons

Doctoral Dissertations

Structure-based machine-learning techniques are frequently used in extensions of supervised learning, such as active, semi-supervised, multi-modal, and multi-task learning. A common step in many successful methods is a structure-discovery process that is made possible through the addition of new information, which can be user feedback, unlabeled data, data from similar tasks, alternate views of the problem, etc. Learning paradigms developed in the above-mentioned fields have led to some extremely flexible, scalable, and successful multivariate analysis approaches. This success and flexibility offer opportunities to expand the use of machine learning paradigms to more complex analyses. In particular, while information is often …

Dynamic Task Execution On Shared And Distributed Memory Architectures, Asim Yarkhan

Doctoral Dissertations

Multicore architectures with high core counts have come to dominate the world of high performance computing, from shared memory machines to the largest distributed memory clusters. The multicore route to increased performance has a simpler design and better power efficiency than the traditional approach of increasing processor frequencies. But, standard programming techniques are not well adapted to this change in computer architecture design.

In this work, we study the use of dynamic runtime environments executing data driven applications as a solution to programming multicore architectures. The goals of our runtime environments are productivity, scalability and performance. We demonstrate productivity by …

Validation Of Weak Form Thermal Analysis Algorithms Supporting Thermal Signature Generation, Elton Lewis Freeman

Masters Theses

Extremization of a weak form for the continuum energy conservation principle differential equation naturally implements fluid convection and radiation as flux Robin boundary conditions associated with unsteady heat transfer. Combining a spatial semi-discretization via finite element trial space basis functions with time-accurate integration generates a totally node-based algebraic statement for computing. Closure for gray body radiation is a newly derived node-based radiosity formulation generating piecewise discontinuous solutions, while that for natural-forced-mixed convection heat transfer is extracted from the literature. Algorithm performance, mathematically predicted by asymptotic convergence theory, is subsequently validated with data obtained in 24 hour diurnal field experiments for …

Hard And Soft Error Resilience For One-Sided Dense Linear Algebra Algorithms, Peng Du

Doctoral Dissertations

Dense matrix factorizations, such as LU, Cholesky and QR, are widely used by scientific applications that require solving systems of linear equations, eigenvalues and linear least squares problems. Such computations are normally carried out on supercomputers, whose ever-growing scale induces a fast decline of the Mean Time To Failure (MTTF). This dissertation develops fault tolerance algorithms for one-sided dense matrix factorizations, which handles Both hard and soft errors.

For hard errors, we propose methods based on diskless checkpointing and Algorithm Based Fault Tolerance (ABFT) to provide full matrix protection, including the left and right factor that are normally seen in …

Vision-Based Robot Control In The Context Of Human-Machine Interactions, Andrzej Nycz

Doctoral Dissertations

This research has explored motion control based on visual servoing – in the context of complex human-machine interactions and operations in realistic environments. Two classes of intelligent robotic systems were studied in this context: operator assistance with a high dexterity telerobotic manipulator performing remote tooling-centric tasks, and a bio-robot for X-ray imaging of lower extremity human skeletal joints during natural walking. The combination of human-machine interactions and practical application scenarios has led to the following fundamental contributions: 1) exploration and evaluation of a new concept of acquiring fluoroscope images of musculoskeletal features of interest during natural human motion, 2) creation …

Air: Adaptive Dynamic Precision Iterative Refinement, Jun Kyu Lee

Doctoral Dissertations

In high performance computing, applications often require very accurate solutions while minimizing runtimes and power consumption. Improving the ratio of the number of logic gates implementing floating point arithmetic operations to the total number of logic gates enables greater efficiency, potentially with higher performance and lower power consumption. Software executing on the fixed hardware in Von-Neuman architectures faces limitations on improving this ratio, since processors require extensive supporting logic to fetch and decode instructions while employing arithmetic units with statically defined precision. This dissertation explores novel approaches to improve computing architectures for linear system applications not only by designing application-specific …

Coalition Formation And Execution In Multi-Robot Tasks, Yu Zhang

Doctoral Dissertations

In this research, I explore several related problems in distributed robot systems that must be addressed in order to achieve multi-robot tasks, in which individual robots may not possess all the required capabilities. While most previous research work on multi-robot cooperation mainly concentrates on loosely-coupled multi-robot tasks, a more challenging problem is to also address tightly-coupled multi- robot tasks involving close robot interactions, which often require capability sharing. Three related topics towards addressing these tasks are discussed, as follows:

Forming coalitions, which determines how robots should form into subgroups (i.e., coalitions) to address individual tasks. To achieve system autonomy, the …

Real-Time Mobile Stereo Vision, Bryan Hale Bodkin

Masters Theses

Computer stereo vision is used extract depth information from two aligned cameras and there are a number of hardware and software solutions to solve the stereo correspondence problem. However few solutions are available for inexpensive mobile platforms where power and hardware are major limitations. This Thesis will proposes a method that competes with an existing OpenCV stereo correspondence method in speed and quality, and is able to run on generic multi core CPU’s.

Track Prediction For Border Security Using A Discrete Kalman Filter, Jonathan William Hickerson

Masters Theses

Border security systems are a critical component in the prevention of the transnational trafficking of unlawful goods. For economic, environmental, and public safety related reasons, it is obviously desirable to prevent the transfer of materials such as illicit drugs, nuclear material, and unlawfully present individuals across borders; however, the deployment of trafficking countermeasures is a daunting task, wrought with unique challenges, such as unfamiliar terrain, long distances, and a potentially harsh environment.

The purpose of this thesis is to suggest a method to combine three different types of sensor systems to accurately track an individual as he crosses a field …

Meal Helper, Jacob Taylor Peek, David Prenshaw, Matthew Burnett, Ian Harmon

Chancellor’s Honors Program Projects

No abstract provided.

Deep Machine Learning With Spatio-Temporal Inference, Thomas Paul Karnowski

Doctoral Dissertations

Deep Machine Learning (DML) refers to methods which utilize hierarchies of more than one or two layers of computational elements to achieve learning. DML may draw upon biomemetic models, or may be simply biologically-inspired. Regardless, these architectures seek to employ hierarchical processing as means of mimicking the ability of the human brain to process a myriad of sensory data and make meaningful decisions based on this data. In this dissertation we present a novel DML architecture which is biologically-inspired in that (1) all processing is performed hierarchically; (2) all processing units are identical; and (3) processing captures both spatial and …

Line Following Navigation, Nicole Marie Pennington

Chancellor’s Honors Program Projects

No abstract provided.

A Framework For Federated Two-Factor Authentication Enabling Cost-Effective Secure Access To Distributed Cyberinfrastructure, Matthew Allan Ezell

Masters Theses

As cyber attacks become increasingly sophisticated, the security measures used to mitigate the risks must also increase in sophistication. One time password (OTP) systems provide strong authentication because security credentials are not reusable, thus thwarting credential replay attacks. The credential changes regularly, making brute-force attacks significantly more difficult. In high performance computing, end users may require access to resources housed at several different service provider locations. The ability to share a strong token between multiple computing resources reduces cost and complexity.

The National Science Foundation (NSF) Extreme Science and Engineering Discovery Environment (XSEDE) provides access to digital resources, including supercomputers, …