Computer Engineering Commons^™

Memory Optimizations For High-Throughput Computer Systems, Zhiyuan Lu

Dissertations, Master's Theses and Master's Reports

The emergence of new non-volatile memory (NVM) technology and deep neural network (DNN) inferences bring challenges related to off-chip memory access. Ensuring crash consistency leads to additional memory operations and exposes memory update operations on the critical execution path. DNN inference execution on some accelerators suffers from intensive off-chip memory access. The focus of this dissertation is to tackle the issues related to off-chip memory in these high performance computing systems.

The logging operations, required by the crash consistency, impose a significant performance overhead due to the extra memory access. To mitigate the persistence time of log requests, we introduce …

Benchmarking Model Predictive Control And Reinforcement Learning For Legged Robot Locomotion, Shivayogi Akki

Dissertations, Master's Theses and Master's Reports

This research delves into the realm of quadrupedal robotics, focusing on the comparative analysis of Model Predictive Control (MPC) and Reinforcement Learning (RL) as predominant control strategies. Through the comprehensive dataset compiled and the insights derived from this analysis, this research aims to serve as a valuable resource for the legged robotics community, guiding researchers and practitioners in the selection and implementation of control strategies. The ultimate goal is to contribute to the advancement of legged robot capabilities and facilitate their successful deployment in real-world applications.

In this study, we employ the Unitree Go1 quadrupedal robot as a testbed, subjecting …

Neuromorphic Computing Applications In Robotics, Noah Zins

Dissertations, Master's Theses and Master's Reports

Deep learning achieves remarkable success through training using massively labeled datasets. However, the high demands on the datasets impede the feasibility of deep learning in edge computing scenarios and suffer from the data scarcity issue. Rather than relying on labeled data, animals learn by interacting with their surroundings and memorizing the relationships between events and objects. This learning paradigm is referred to as associative learning. The successful implementation of associative learning imitates self-learning schemes analogous to animals which resolve the challenges of deep learning. Current state-of-the-art implementations of associative memory are limited to simulations with small-scale and offline paradigms. Thus, …

Evaluation Of Lidar Uncertainty And Applications Towards Slam In Off-Road Environments, Zachary D. Jeffries

Dissertations, Master's Theses and Master's Reports

Safe and robust operation of autonomous ground vehicles in all types of conditions and environment necessitates complex perception systems and unique, innovative solutions. This work addresses automotive lidar and maximizing the performance of a simultaneous localization and mapping stack. An exploratory experiment and an open benchmarking experiment are both presented. Additionally, a popular SLAM application is extended to use the type of information gained from lidar characterization, demonstrating the performance gains and necessity to tightly couple perception software and sensor hardware. The first exploratory experiment collects data from child-sized, low-reflectance targets over a range from 15 m to 35 m. …

Machine Learning And Deep Learning Approaches For Gene Regulatory Network Inference In Plant Species, Sai Teja Mummadi

Dissertations, Master's Theses and Master's Reports

The construction of gene regulatory networks (GRNs) is vital for understanding the regulation of metabolic pathways, biological processes, and complex traits during plant growth and responses to environmental cues and stresses. The increasing availability of public databases has facilitated the development of numerous methods for inferring gene regulatory relationships between transcription factors and their targets. However, there is limited research on supervised learning techniques that utilize available regulatory relationships of plant species in public databases.

This study investigates the potential of machine learning (ML), deep learning (DL), and hybrid approaches for constructing GRNs in plant species, specifically Arabidopsis thaliana, …

Development And Implementation Of Robot Operating Systems For Undergraduates, Chelsey Spitzner

Dissertations, Master's Theses and Master's Reports

The purpose of this project was to create an undergraduate junior lab to teach students about Robotic Operating System (ROS). The labs were designed to highlight the usefulness of ROS and the process used. Designing algorithms, how to send/receive messages, and the hierarchy of how nodes work with each other are emphasized. Taking packages that are open-source then modifying them is also emphasized. This is done so that students can transfer their knowledge from this course to other robot operating systems.

Off Road Autonomous Vehicle Modeling And Repeatability Using Real World Telemetry Via Simulation, Matthew Paul Spencer

Dissertations, Master's Theses and Master's Reports

One approach to autonomous control of high mobility ground vehicle platforms operating on challenging terrain is with the use of predictive simulation. Using a simulated or virtual world, an autonomous system can optimize use of its control systems by predicting interaction between the vehicle and ground as well as the vehicle actuator state. Such a simulation allows the platform to assess multiple possible scenarios before attempting to execute a path. Physically realistic simulations covering all of these domains are currently computationally expensive, and are unable to provide fast execution times when assessing each individual scenario due to the use of …

Design And Analysis Of Marangoni-Driven Robotic Surfers, Mitchel L. Timm

Dissertations, Master's Theses and Master's Reports

We designed and experimentally studied the dynamics of two robotic systems that surf along the water-air interface. The robots were self-propelled by means of creating and maintaining a surface tension gradient resulting from an asymmetric release of isopropyl alcohol (IPA). The imbalance in the distribution of surface tension surrounding the robots generates a propulsive force commonly referred to as Marangoni propulsion. First, we considered a single surfer, which was custom-made with novel control mechanisms that allow for both forward motion and steering to be remotely adjusted solely through the manipulation of local surface stresses. We analyzed the performance of this …

Collective Hydrodynamics Of Robotic Fish, Rohit S. Pandhare

Dissertations, Master's Theses and Master's Reports

Many animals in nature travel in groups either for protection, survival, or endurance. Among these, fish do so under the burden of hydrodynamic loads, which incites questions as to the significance of the multi-body fluid-mediated interactions that facilitate collective swimming. We study such interactions in the idealized setting of a rotational array of robotic fish whose tails undergo a prescribed flapping motion, but whose swimming speed is determined as a natural result of the hydrodynamic effects. Specifically, we examine how the measured collective speed of the swimmers varies with the imposed frequency and amplitude of their tail flapping, and with …

Adapting Deep Learning For Underwater Acoustic Communication Channel Modeling, Li Wei

Dissertations, Master's Theses and Master's Reports

The recent emerging applications of novel underwater systems lead to increasing demand for underwater acoustic (UWA) communication and networking techniques. However, due to the challenging UWA channel characteristics, conventional wireless techniques are rarely applicable to UWA communication and networking. The cognitive and software-defined communication and networking are considered promising architecture of a novel UWA system design. As an essential component of a cognitive communication system, the modeling and prediction of the UWA channel impulse response (CIR) with deep generative models are studied in this work.

Firstly, an underwater acoustic communication and networking testbed is developed for conducting various simulations and …

An Experimental Study Towards Underwater Propulsion System Using Structure Borne Traveling Waves, Shreyas Suhas Gadekar

Dissertations, Master's Theses and Master's Reports

The method of generating steady-state structure-borne traveling waves underwater in an infinite media creates abundant opportunities in the field of propulsive applications, and they are gaining attention from several researchers. This experimental study provides a framework for harnessing traveling waves in a 1D beam immersed under quiescent water using two force input methods and providing a motion to an object floating on the surface of the water.

In this study, underwater traveling waves are tailored using structural vibrations at five different frequencies in the range of 10Hz to 300Hz. The resulting fluid motion provides a propulsive thrust that moves a …

An Analysis Of Compressive Convolutional Autoencoders For Image Archiving In Medical Informatics, Charles Warren

Dissertations, Master's Theses and Master's Reports

Within a given enterprise network, an array of data types needs to be communicated. These network transmissions consist of images, videos, text, and binaries that have unique requirements of bandwidth and computational overhead to transmit. With respect to medical informatics, these include a multitude of varying subjects, standards, and modalities which are communicated to and from imaging equipment, clinicians, and medical archives. To reduce the required bandwidth to transmit, or provide adequate storage capacity for archival purposes, the data may be compressed in such a way that reduces the size of the image when it is transferred or stored. The …

Eager Scheduling Of Dependent Instructions, Kurush Kasad

Dissertations, Master's Theses and Master's Reports

Modern superscalar processors are able to potentially issue and execute multiple instructions per cycle. Several techniques over the years have focused on increasing the Instruction Level Parallelism (ILP) that a processor can exploit. However, there are many limitations of ILP that hinder performance, chief of them being the chain of dependencies between instructions that stops instructions from being executed in parallel.

We propose a new micro-architecture design which extends the superscalar pipeline with a data-flow pipeline where the dataflow part identifies immediately dependent instructions and executes them early. The dataflow pipeline is able to identify redundant instructions, track changes in …

Integration Of Robotic And Electro-Pneumatic Systems Using Advanced Control And Communication Schemes, Chinmay Kondekar

Dissertations, Master's Theses and Master's Reports

Modern industrial automation systems are designed by interconnecting various subsystems which work together to perform a process. The thesis project aims to integrate fragmented subsystems into a flexible and reconfigurable system through advanced communication protocols and perform a process to demonstrate the effectiveness of interconnected systems.

The system consists of three six-axis robots, one electro-pneumatic robot, and two conveyors connected using EthernetIP communication and hardwired connections. The interconnected system works together to perform machining of a workpiece using advanced control methods of CAD to robot path generation, central control through a PLC, and process control through HMI.

Standardized programming blocks …

Open-Source Tig-Based Metal 3d-Printing, Shane Oberloier

Dissertations, Master's Theses and Master's Reports

Metal 3-D printing has been relegated to high-cost proprietary high-resolution systems and low-resolution low-cost metal inert gas (MIG) systems. In order to provide a path to high-resolution, low-cost, metal 3-D printing, this manuscript proposes a new open source metal 3-D printer design based around a low-cost tungsten inert gas (TIG) welder coupled to a commercial open source self replicating rapid prototyper. Optimal printing parameters for the machine are acquired using a novel computational intelligence software. TIG has many advantages over MIG, such as having a low heat input, clean beads, and the potential for both high-resolution prints as well as …

Optimal Mission Planning Of Autonomous Mobile Agents For Applications In Microgrids, Sensor Networks, And Military Reconnaissance, Casey D. Majhor

Dissertations, Master's Theses and Master's Reports

As technology advances, the use of collaborative autonomous mobile systems for various applications will become evermore prevalent. One interesting application of these multi-agent systems is for autonomous mobile microgrids. These systems will play an increasingly important role in applications such as military special operations for mobile ad-hoc power infrastructures and for intelligence, surveillance, and reconnaissance missions. In performing these operations with these autonomous energy assets, there is a crucial need to optimize their functionality according to their specific application and mission. Challenges arise in determining mission characteristics such as how each resource should operate, when, where, and for how long. …

Dynamic Dependency Collapsing, Görkem Aşılıoğlu

Dissertations, Master's Theses and Master's Reports

In this dissertation, we explore the concept of dynamic dependency collapsing. Performance increases in computer architecture are always introduced by exploiting additional parallelism when the clock speed is fixed. We show that further improvements are possible even when the available parallelism in programs are exhausted. This performance improvement is possible due to executing instructions in parallel that would ordinarily have been serialized. We call this concept dependency collapsing. We explore existing techniques that exploit parallelism and show which of them fall under the umbrella of dependency collapsing. We then introduce two dependency collapsing techniques of our own. The first technique …

Demand-Driven Execution Using Future Gated Single Assignment Form, Omkar Javeri

Dissertations, Master's Theses and Master's Reports

This dissertation discusses a novel, previously unexplored execution model called Demand-Driven Execution (DDE), which executes programs starting from the outputs of the program, progressing towards the inputs of the program. This approach is significantly different from prior demand-driven reduction machines as it can execute a program written in an imperative language using the demand-driven paradigm while extracting both instruction and data level parallelism. The execution model relies on an executable Single Assignment Form which serves both as the internal representation of the compiler as well as the Instruction Set Architecture (ISA) of the machine. This work develops the instruction set …

High-Performance Spectral Methods For Computer-Aided Design Of Integrated Circuits, Zhiqiang Zhao

Dissertations, Master's Theses and Master's Reports

Recent research shows that by leveraging the key spectral properties of eigenvalues and eigenvectors of graph Laplacians, more efficient algorithms can be developed for tackling many graph-related computing tasks. In this dissertation, spectral methods are utilized for achieving faster algorithms in the applications of very-large-scale integration (VLSI) computer-aided design (CAD)

First, a scalable algorithmic framework is proposed for effective-resistance preserving spectral reduction of large undirected graphs. The proposed method allows computing much smaller graphs while preserving the key spectral (structural) properties of the original graph. Our framework is built upon the following three key components: a spectrum-preserving node aggregation and …

Hometracker: A Household Information Feedback System For Food/Energy/Water Metabolism, Nichole Mackey

Dissertations, Master's Theses and Master's Reports

The Food, Energy and Water Conscious (FEWCON) project seeks to understand how food, energy and water (FEW) as independent resources within households are connected. In the main study of the project, intervention messages that link household FEW consumption to equivalent climate consequences are pushed to the households. The goal of the FEWCON study is to determine potential intervention messages that influence household FEW consumption behavior.

A key component of the FEWCON study is a web application named HomeTracker (Household Metabolism Tracker) which collects FEW consumption data within households, then uses this data to select consumption-specific feedback to the homeowners. To …

Estimation Of Multi-Directional Ankle Impedance As A Function Of Lower Extremity Muscle Activation, Lauren Knop

Dissertations, Master's Theses and Master's Reports

The purpose of this research is to investigate the relationship between the mechanical impedance of the human ankle and the corresponding lower extremity muscle activity. Three experimental studies were performed to measure the ankle impedance about multiple degrees of freedom (DOF), while the ankle was subjected to different loading conditions and different levels of muscle activity. The first study determined the non-loaded ankle impedance in the sagittal, frontal, and transverse anatomical planes while the ankle was suspended above the ground. The subjects actively co-contracted their agonist and antagonistic muscles to various levels, measured using electromyography (EMG). An Artificial Neural Network …

Estimation And Prediction Of The Human Gait Dynamics For The Control Of An Ankle-Foot Prosthesis, Guilherme Aramizo Ribeiro

Dissertations, Master's Theses and Master's Reports

With the growing population of amputees, powered prostheses can be a solution to improve the quality of life for many people. Powered ankle-foot prostheses can be made to behave similar to the lost limb via controllers that emulate the mechanical impedance of the human ankle. Therefore, the understanding of human ankle dynamics is of major significance. First, this work reports the modulation of the mechanical impedance via two mechanisms: the co-contraction of the calf muscles and a change of mean ankle torque and angle. Then, the mechanical impedance of the ankle was determined, for the first time, as a multivariable …

Extending Maneuverability Of Internally Actuated Underwater Gliders, An Attempt To Develop An Open Platform For Research And Education, Saeedeh Ziaeefard

Dissertations, Master's Theses and Master's Reports

Increasing maneuverability of internally actuated Underwater Gliders (UGs) is inevitable due to high demands in underwater surveillance and reconnaissance missions where agility and stealthiness are the keys to success. High maneuverability is needed to provide the opportunity for optimal trajectory planning, planar motion smoothness, and re-planning adapting to the dynamic environments.

This work explores extending the maneuverability of underwater gliders through coupled improvement in mechanical design, efficient use of internal actuation, and motion planning strategy utilizing flight concatenation. The existence of five flight patterns ``advanced flight", inspired by air gliders, enabled solely by utilizing internal actuation are investigated: Circle, Oval …

Resource Optimization In Wireless Sensor Networks For An Improved Field Coverage And Cooperative Target Tracking, Husam Sweidan

Dissertations, Master's Theses and Master's Reports

There are various challenges that face a wireless sensor network (WSN) that mainly originate from the limited resources a sensor node usually has. A sensor node often relies on a battery as a power supply which, due to its limited capacity, tends to shorten the life-time of the node and the network as a whole. Other challenges arise from the limited capabilities of the sensors/actuators a node is equipped with, leading to complication like a poor coverage of the event, or limited mobility in the environment. This dissertation deals with the coverage problem as well as the limited power and …

Mitigating The Effect Of Misspeculations In Superscalar Processors, Zhaoxiang Jin

Dissertations, Master's Theses and Master's Reports

Modern superscalar processors highly rely on the speculative execution which speculatively executes instructions and then verifies. If the prediction is different from the execution result, a misspeculation recovery is performed. Misspeculation recovery penalties still account for a substantial amount of performance reduction. This work focuses on the techniques to mitigate the effect of recovery penalties and proposes practical mechanisms which are thoroughly implemented and analyzed.

In general, we can divide the misspeculation penalty into four parts: misspeculation detection delay; stale instruction elimination delay; state restoration delay and pipeline fill delay. This dissertation does not consider the detection delay, instead, we …

Mpart: Miss Ratio Curve Guided Partitioning In Key-Value Stores, Daniel Byrne

Dissertations, Master's Theses and Master's Reports

Web applications employ key-value stores to cache the data that is most commonly accessed. The cache improves an web application’s performance by serving its requests from memory, avoiding fetching them from the backend database. Since the memory space is limited, maximizing the memory utilization is a key to delivering the best performance possible. This has lead to the use of multi-tenant systems, allowing applications to share cache space. In addition, application data access patterns change over time, so the system should be adaptive in its memory allocation. In this thesis, we address both multi-tenancy (where a single cache is used …

Implementing Write Compression In Flash Memory Using Zeckendorf Two-Round Rewriting Codes, Vincent T. Druschke

Dissertations, Master's Theses and Master's Reports

Flash memory has become increasingly popular as the underlying storage technology for high-performance nonvolatile storage devices. However, while flash offers several benefits over alternative storage media, a number of limitations still exist within the current technology. One such limitation is that programming (altering a bit from its default value) and erasing (returning a bit to its default value) are asymmetric operations in flash memory devices: a flash memory can be programmed arbitrarily, but can only be erased in relatively large batches of storage bits called blocks, with block sizes ranging from 512K up to several megabytes. This creates a situation …

Anomaly Inference Based On Heterogeneous Data Sources In An Electrical Distribution System, Yachen Tang

Dissertations, Master's Theses and Master's Reports

Harnessing the heterogeneous data sets would improve system observability. While the current metering infrastructure in distribution network has been utilized for the operational purpose to tackle abnormal events, such as weather-related disturbance, the new normal we face today can be at a greater magnitude. Strengthening the inter-dependencies as well as incorporating new crowd-sourced information can enhance operational aspects such as system reconfigurability under extreme conditions. Such resilience is crucial to the recovery of any catastrophic events. In this dissertation, it is focused on the anomaly of potential foul play within an electrical distribution system, both primary and secondary networks as …

Applications Of Robot Operating System (Ros) To Mobile Microgrid Formation Outdoors, John Naglak

Dissertations, Master's Theses and Master's Reports

Application of mobile robots to microgrid formation has value for disaster response and service of forward operating bases. This thesis describes the development, testing and demonstration of broad effort across multiple disciplines to enable outdoor positioning and connection of mobile microgrids for the first time. This work includes an outdoor waypoint controller for a UGV agent, specifically the Clearpath Husky. It details sensor fusion of 2D LiDAR and stereo vision, and fusion of odometry sources using an Extended Kalman Filter. Development of these software tools entails integration of many of the packages available through the Robot Operating System (ROS), with …

Control Of A Powered Ankle-Foot Prosthesis: From Perception To Impedance Modulation, Guilherme Aramizo Ribeiro

Dissertations, Master's Theses and Master's Reports

Active ankle prostheses controllers are demonstrating gaining smart features to improve the safety and comfort offor users. The perception of user intention to modulate the ankle dynamics is a well-known example of such feature. But not much work focused on the perception of the environment, nor how the environment should be included in the mechanical design and control of the prosthesisprostheses. The proposed work aims to improve the feasibility of integrate the environment perception integration intoto the prostheses controllersler, and to define the desired ankle dynamics, as mechanical impedance, duringof the human walk on different environmental settings. As a preliminary …