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ASU Electronic Theses and Dissertations


This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.

In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.

Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.


Subject
Date Range
2011 2019


With the massive multithreading execution feature, graphics processing units (GPUs) have been widely deployed to accelerate general-purpose parallel workloads (GPGPUs). However, using GPUs to accelerate computation does not always gain good performance improvement. This is mainly due to three inefficiencies in modern GPU and system architectures. First, not all parallel threads have a uniform amount of workload to fully utilize GPU’s computation ability, leading to a sub-optimal performance problem, called warp criticality. To mitigate the degree of warp criticality, I propose a Criticality-Aware Warp Acceleration mechanism, called CAWA. CAWA predicts and accelerates the critical warp execution by allocating larger execution …

Contributors
Lee, Shin-Ying, Wu, Carole-Jean, Chakrabarti, Chaitali, et al.
Created Date
2017

Deep neural networks (DNN) have shown tremendous success in various cognitive tasks, such as image classification, speech recognition, etc. However, their usage on resource-constrained edge devices has been limited due to high computation and large memory requirement. To overcome these challenges, recent works have extensively investigated model compression techniques such as element-wise sparsity, structured sparsity and quantization. While most of these works have applied these compression techniques in isolation, there have been very few studies on application of quantization and structured sparsity together on a DNN model. This thesis co-optimizes structured sparsity and quantization constraints on DNN models during training. …

Contributors
Srivastava, Gaurav, Seo, Jae-Sun, Chakrabarti, Chaitali, et al.
Created Date
2018

The Internet of Things (IoT) has become a more pervasive part of everyday life. IoT networks such as wireless sensor networks, depend greatly on the limiting unnecessary power consumption. As such, providing low-power, adaptable software can greatly improve network design. For streaming live video content, Wireless Video Sensor Network Platform compatible Dynamic Adaptive Streaming over HTTP (WVSNP-DASH) aims to revolutionize wireless segmented video streaming by providing a low-power, adaptable framework to compete with modern DASH players such as Moving Picture Experts Group (MPEG-DASH) and Apple’s Hypertext Transfer Protocol (HTTP) Live Streaming (HLS). Each segment is independently playable, and does not …

Contributors
Khan, Zarah, Reisslein, Martin, Seema, Adolph, et al.
Created Date
2018

Many real-time vision applications require accurate estimation of optical flow. This problem is quite challenging due to extremely high computation and memory requirements. This thesis focuses on designing low complexity dense optical flow algorithms. First, a new method for optical flow that is based on Semi-Global Matching (SGM), a popular dynamic programming algorithm for stereo vision, is presented. In SGM, the disparity of each pixel is calculated by aggregating local matching costs over the entire image to resolve local ambiguity in texture-less and occluded regions. The proposed method, Neighbor-Guided Semi-Global Matching (NG-fSGM) achieves significantly less complexity compared to SGM, by …

Contributors
Xiang, Jiang, Chakrabarti, Chaitali, Karam, Lina, et al.
Created Date
2017

Access Networks provide the backbone to the Internet connecting the end-users to the core network thus forming the most important segment for connectivity. Access Networks have multiple physical layer medium ranging from fiber cables, to DSL links and Wireless nodes, creating practically-used hybrid access networks. We explore the hybrid access network at the Medium ACcess (MAC) Layer which receives packets segregated as data and control packets, thus providing the needed decoupling of data and control plane. We utilize the Software Defined Networking (SDN) principle of centralized processing with segregated data and control plane to further extend the usability of our …

Contributors
Mercian, Anu, Reisslein, Martin, McGarry, Michael P, et al.
Created Date
2015

Users often join an online social networking (OSN) site, like Facebook, to remain social, by either staying connected with friends or expanding social networks. On an OSN site, users generally share variety of personal information which is often expected to be visible to their friends, but sometimes vulnerable to unwarranted access from others. The recent study suggests that many personal attributes, including religious and political affiliations, sexual orientation, relationship status, age, and gender, are predictable using users' personal data from an OSN site. The majority of users want to remain socially active, and protect their personal data at the same …

Contributors
Gundecha, Pritam Sureshlal, Liu, Huan, Ahn, Gail-Joon, et al.
Created Date
2015

This work presents a communication paradigm, using a context-aware mixed reality approach, for instructing human workers when collaborating with robots. The main objective of this approach is to utilize the physical work environment as a canvas to communicate task-related instructions and robot intentions in the form of visual cues. A vision-based object tracking algorithm is used to precisely determine the pose and state of physical objects in and around the workspace. A projection mapping technique is used to overlay visual cues on tracked objects and the workspace. Simultaneous tracking and projection onto objects enables the system to provide just-in-time instructions …

Contributors
Kalpagam Ganesan, Ramsundar, Ben Amor, Hani, Yang, Yezhou, et al.
Created Date
2017

The availability of a wide range of general purpose as well as accelerator cores on modern smartphones means that a significant number of applications can be executed on a smartphone simultaneously, resulting in an ever increasing demand on the memory subsystem. While the increased computation capability is intended for improving user experience, memory requests from each concurrent application exhibit unique memory access patterns as well as specific timing constraints. If not considered, this could lead to significant memory contention and result in lowered user experience. This work first analyzes the impact of memory degradation caused by the interference at the …

Contributors
SHINGARI, DAVESH, Wu, Carole-Jean, Vrudhula, Sarma, et al.
Created Date
2016

General-purpose processors propel the advances and innovations that are the subject of humanity’s many endeavors. Catering to this demand, chip-multiprocessors (CMPs) and general-purpose graphics processing units (GPGPUs) have seen many high-performance innovations in their architectures. With these advances, the memory subsystem has become the performance- and energy-limiting aspect of CMPs and GPGPUs alike. This dissertation identifies and mitigates the key performance and energy-efficiency bottlenecks in the memory subsystem of general-purpose processors via novel, practical, microarchitecture and system-architecture solutions. Addressing the important Last Level Cache (LLC) management problem in CMPs, I observe that LLC management decisions made in isolation, as in …

Contributors
Arunkumar, Akhil, Wu, Carole-Jean, Shrivastava, Aviral, et al.
Created Date
2018

Multi-sensor fusion is a fundamental problem in Robot Perception. For a robot to operate in a real world environment, multiple sensors are often needed. Thus, fusing data from various sensors accurately is vital for robot perception. In the first part of this thesis, the problem of fusing information from a LIDAR, a color camera and a thermal camera to build RGB-Depth-Thermal (RGBDT) maps is investigated. An algorithm that solves a non-linear optimization problem to compute the relative pose between the cameras and the LIDAR is presented. The relative pose estimate is then used to find the color and thermal texture …

Contributors
Krishnan, Aravindhan K., Saripalli, Srikanth, Klesh, Andrew, et al.
Created Date
2016