Physical Sciences and Mathematics Commons^™

The Synthesis Of Memristive Neuromorphic Circuits, Austin Richard Wyer

Masters Theses

As Moores Law has come to a halt, it has become necessary to explore alternative forms of computation that are not limited in the same ways as traditional CMOS technologies and the Von Neumann architecture. Neuromorphic computing, computing inspired by the human brain with neurons and synapses, has been proposed as one of these alternatives. Memristors, non-volatile devices with adjustable resistances, have emerged as a candidate for implementing neuromorphic computing systems because of their low power and low area overhead. This work presents a C++ simulator for an implementation of a memristive neuromorphic circuit. The simulator is used within a …

Developing Leading And Lagging Indicators To Enhance Equipment Reliability In A Lean System, Dhanush Agara Mallesh

Masters Theses

With increasing complexity in equipment, the failure rates are becoming a critical metric due to the unplanned maintenance in a production environment. Unplanned maintenance in manufacturing process is created issues with downtimes and decreasing the reliability of equipment. Failures in equipment have resulted in the loss of revenue to organizations encouraging maintenance practitioners to analyze ways to change unplanned to planned maintenance. Efficient failure prediction models are being developed to learn about the failures in advance. With this information, failures predicted can reduce the downtimes in the system and improve the throughput.

The goal of this thesis is to predict …

Automated Program Profiling And Analysis For Managing Heterogeneous Memory Systems, Adam Palmer Howard

Masters Theses

Many promising memory technologies, such as non-volatile, storage-class memories and high-bandwidth, on-chip RAMs, are beginning to emerge. Since each of these new technologies present tradeoffs distinct from conventional DRAMs, next-generation systems are likely to include multiple tiers of memory storage, each with their own type of devices. To efficiently utilize the available hardware, such systems will need to alter their data management strategies to consider the performance and capabilities provided by each tier.

This work explores a variety of cross-layer strategies for managing application data in heterogeneous memory systems. We propose different program profiling-based techniques to automatically partition program allocation …

A Gpu Implementation Of Distance-Driven Computed Tomography, Ryan D. Wagner

Masters Theses

Computed tomography (CT) is used to produce cross-sectional images of an object via noninvasive X-ray scanning of the object. These images have a wide range of uses including threat detection in checked baggage at airports. The projection data collected by the CT scanner must be reconstructed before the image may be viewed. In comparison to filtered backprojection methods of reconstruction, iterative reconstruction algorithms have been shown to increase overall image quality by incorporating a more complete model of the underlying physics. Unfortunately, iterative algorithms are generally too slow to meet the high throughput demands of this application. It is therefore …

On The Role Of Genetic Algorithms In The Pattern Recognition Task Of Classification, Isaac Ben Sherman

Masters Theses

In this dissertation we ask, formulate an apparatus for answering, and answer the following three questions: Where do Genetic Algorithms fit in the greater scheme of pattern recognition? Given primitive mechanics, can Genetic Algorithms match or exceed the performance of theoretically-based methods? Can we build a generic universal Genetic Algorithm for classification? To answer these questions, we develop a genetic algorithm which optimizes MATLAB classifiers and a variable length genetic algorithm which does classification based entirely on boolean logic. We test these algorithms on disparate datasets rooted in cellular biology, music theory, and medicine. We then get results from these …

Efficient Simulation Of A Simple Evolutionary System, Mahendra Duwal Shrestha

Masters Theses

An infinite population model is considered for diploid evolution under the influence of crossing over and mutation. The evolution equations show how Vose’s haploid model for Genetic Algorithms extends to the diploid case, thereby making feasible simulations which otherwise would require excessive resources. This is illustrated through computations confirming the convergence of finite diploid population short-term behaviour to the behaviour predicted by the infinite diploid model. The results show the distance between finite and infinite population evolutionary trajectories can decrease in practice like the reciprocal of the square root of population size.

Under necessary and sufficient conditions (NS) concerning mutation …