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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.


Date Range
2013 2019


Mobile platforms are becoming highly heterogeneous by combining a powerful multiprocessor system-on-chip (MpSoC) with numerous resources including display, memory, power management IC (PMIC), battery and wireless modems into a compact package. Furthermore, the MpSoC itself is a heterogeneous resource that integrates many processing elements such as CPU cores, GPU, video, image, and audio processors. As a result, optimization approaches targeting mobile computing needs to consider the platform at various levels of granularity. Platform energy consumption and responsiveness are two major considerations for mobile systems since they determine the battery life and user satisfaction, respectively. In this work, the models for …

Contributors
Gupta, Ujjwal, Ogras, Umit Y., Ozev, Sule, et al.
Created Date
2014

Object tracking is an important topic in multimedia, particularly in applications such as teleconferencing, surveillance and human-computer interface. Its goal is to determine the position of objects in images continuously and reliably. The key steps involved in object tracking are foreground detection to detect moving objects, clustering to enable representation of an object by its centroid, and tracking the centroids to determine the motion parameters. In this thesis, a low cost object tracking system is implemented on a hardware accelerator that is a warp based processor for SIMD/Vector style computations. First, the different foreground detection techniques are explored to figure …

Contributors
Sasikumar, Asha, Chakrabarti, Chaitali, Ogras, Umit, et al.
Created Date
2015

Three dimensional (3-D) ultrasound is safe, inexpensive, and has been shown to drastically improve system ease-of-use, diagnostic efficiency, and patient throughput. However, its high computational complexity and resulting high power consumption has precluded its use in hand-held applications. In this dissertation, algorithm-architecture co-design techniques that aim to make hand-held 3-D ultrasound a reality are presented. First, image enhancement methods to improve signal-to-noise ratio (SNR) are proposed. These include virtual source firing techniques and a low overhead digital front-end architecture using orthogonal chirps and orthogonal Golay codes. Second, algorithm-architecture co-design techniques to reduce the power consumption of 3-D SAU imaging systems …

Contributors
Yang, Ming, Chakrabarti, Chaitali, Papandreou-Suppappola, Antonia, et al.
Created Date
2015

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

Nearly 60% of the world population uses a mobile phone, which is typically powered by a system-on-chip (SoC). While the mobile platform capabilities range widely, responsiveness, long battery life and reliability are common design concerns that are crucial to remain competitive. Consequently, state-of-the-art mobile platforms have become highly heterogeneous by combining a powerful SoC with numerous other resources, including display, memory, power management IC, battery and wireless modems. Furthermore, the SoC itself is a heterogeneous resource that integrates many processing elements, such as CPU cores, GPU, video, image, and audio processors. Therefore, CPU cores do not dominate the platform power …

Contributors
Gupta, Ujjwal, Ogras, Umit Y., Chakrabarti, Chaitali, et al.
Created Date
2018

Vision processing on traditional architectures is inefficient due to energy-expensive off-chip data movements. Many researchers advocate pushing processing close to the sensor to substantially reduce data movements. However, continuous near-sensor processing raises the sensor temperature, impairing the fidelity of imaging/vision tasks. The work characterizes the thermal implications of using 3D stacked image sensors with near-sensor vision processing units. The characterization reveals that near-sensor processing reduces system power but degrades image quality. For reasonable image fidelity, the sensor temperature needs to stay below a threshold, situationally determined by application needs. Fortunately, the characterization also identifies opportunities -- unique to the needs …

Contributors
Kodukula, Venkatesh, LiKamWa, Robert, Chakrabarti, Chaitali, et al.
Created Date
2019

Stream processing has emerged as an important model of computation especially in the context of multimedia and communication sub-systems of embedded System-on-Chip (SoC) architectures. The dataflow nature of streaming applications allows them to be most naturally expressed as a set of kernels iteratively operating on continuous streams of data. The kernels are computationally intensive and are mainly characterized by real-time constraints that demand high throughput and data bandwidth with limited global data reuse. Conventional architectures fail to meet these demands due to their poorly matched execution models and the overheads associated with instruction and data movements. This work presents StreamWorks, …

Contributors
Panda, Amrit Kumar, Chatha, Karam S., Wu, Carole-Jean, et al.
Created Date
2014

With increasing transistor volume and reducing feature size, it has become a major design constraint to reduce power consumption also. This has given rise to aggressive architectural changes for on-chip power management and rapid development to energy efficient hardware accelerators. Accordingly, the objective of this research work is to facilitate software developers to leverage these hardware techniques and improve energy efficiency of the system. To achieve this, I propose two solutions for Linux kernel: Optimal use of these architectural enhancements to achieve greater energy efficiency requires accurate modeling of processor power consumption. Though there are many models available in literature …

Contributors
Desai, Digant, Vrudhula, Sarma, Chakrabarti, Chaitali, et al.
Created Date
2013

Multicore processors have proliferated in nearly all forms of computing, from servers, desktop, to smartphones. The primary reason for this large adoption of multicore processors is due to its ability to overcome the power-wall by providing higher performance at a lower power consumption rate. With multi-cores, there is increased need for dynamic energy management (DEM), much more than for single-core processors, as DEM for multi-cores is no more a mechanism just to ensure that a processor is kept under specified temperature limits, but also a set of techniques that manage various processor controls like dynamic voltage and frequency scaling (DVFS), …

Contributors
Hanumaiah, Vinay, Vrudhula, Sarma, Chatha, Karamvir, et al.
Created Date
2013