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.

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Description
In recent years we have witnessed a shift towards multi-processor system-on-chips (MPSoCs) to address the demands of embedded devices (such as cell phones, GPS devices, luxury car features, etc.). Highly optimized MPSoCs are well-suited to tackle the complex application demands desired by the end user customer. These MPSoCs incorporate a

In recent years we have witnessed a shift towards multi-processor system-on-chips (MPSoCs) to address the demands of embedded devices (such as cell phones, GPS devices, luxury car features, etc.). Highly optimized MPSoCs are well-suited to tackle the complex application demands desired by the end user customer. These MPSoCs incorporate a constellation of heterogeneous processing elements (PEs) (general purpose PEs and application-specific integrated circuits (ASICS)). A typical MPSoC will be composed of a application processor, such as an ARM Coretex-A9 with cache coherent memory hierarchy, and several application sub-systems. Each of these sub-systems are composed of highly optimized instruction processors, graphics/DSP processors, and custom hardware accelerators. Typically, these sub-systems utilize scratchpad memories (SPM) rather than support cache coherency. The overall architecture is an integration of the various sub-systems through a high bandwidth system-level interconnect (such as a Network-on-Chip (NoC)). The shift to MPSoCs has been fueled by three major factors: demand for high performance, the use of component libraries, and short design turn around time. As customers continue to desire more and more complex applications on their embedded devices the performance demand for these devices continues to increase. Designers have turned to using MPSoCs to address this demand. By using pre-made IP libraries designers can quickly piece together a MPSoC that will meet the application demands of the end user with minimal time spent designing new hardware. Additionally, the use of MPSoCs allows designers to generate new devices very quickly and thus reducing the time to market. In this work, a complete MPSoC synthesis design flow is presented. We first present a technique \cite{leary1_intro} to address the synthesis of the interconnect architecture (particularly Network-on-Chip (NoC)). We then address the synthesis of the memory architecture of a MPSoC sub-system \cite{leary2_intro}. Lastly, we present a co-synthesis technique to generate the functional and memory architectures simultaneously. The validity and quality of each synthesis technique is demonstrated through extensive experimentation.
ContributorsLeary, Glenn (Author) / Chatha, Karamvir S (Thesis advisor) / Vrudhula, Sarma (Committee member) / Shrivastava, Aviral (Committee member) / Beraha, Rudy (Committee member) / Arizona State University (Publisher)
Created2013
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Description
As technology enhances our communication capabilities, the number of distributed teams has risen in both public and private sectors. There is no doubt that these technological advancements have addressed a need for communication and collaboration of distributed teams. However, is all technology useful for effective collaboration? Are some methods (modalities)

As technology enhances our communication capabilities, the number of distributed teams has risen in both public and private sectors. There is no doubt that these technological advancements have addressed a need for communication and collaboration of distributed teams. However, is all technology useful for effective collaboration? Are some methods (modalities) of communication more conducive than others to effective performance and collaboration of distributed teams? Although previous literature identifies some differences in modalities, there is little research on geographically distributed mobile teams (DMTs) performing a collaborative task. To investigate communication and performance in this context, I developed the GeoCog system. This system is a mobile communications and collaboration platform enabling small, distributed teams of three to participate in a variant of the military-inspired game, "Capture the Flag". Within the task, teams were given one hour to complete as many "captures" as possible while utilizing resources to the advantage of the team. In this experiment, I manipulated the modality of communication across three conditions with text-based messaging only, vocal communication only, and a combination of the two conditions. It was hypothesized that bi-modal communication would yield superior performance compared to either single modality conditions. Results indicated that performance was not affected by modality. Further results, including communication analysis, are discussed within this paper.
ContributorsChampion, Michael (Author) / Cooke, Nancy J. (Thesis advisor) / Shope, Steven (Committee member) / Wu, Bing (Committee member) / Arizona State University (Publisher)
Created2012
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Description
Rapid technology scaling, the main driver of the power and performance improvements of computing solutions, has also rendered our computing systems extremely susceptible to transient errors called soft errors. Among the arsenal of techniques to protect computation from soft errors, Control Flow Checking (CFC) based techniques have gained a reputation

Rapid technology scaling, the main driver of the power and performance improvements of computing solutions, has also rendered our computing systems extremely susceptible to transient errors called soft errors. Among the arsenal of techniques to protect computation from soft errors, Control Flow Checking (CFC) based techniques have gained a reputation of effective, yet low-cost protection mechanism. The basic idea is that, there is a high probability that a soft-fault in program execution will eventually alter the control flow of the program. Therefore just by making sure that the control flow of the program is correct, significant protection can be achieved. More than a dozen techniques for CFC have been developed over the last several decades, ranging from hardware techniques, software techniques, and hardware-software hybrid techniques as well. Our analysis shows that existing CFC techniques are not only ineffective in protecting from soft errors, but cause additional power and performance overheads. For this analysis, we develop and validate a simulation based experimental setup to accurately and quantitatively estimate the architectural vulnerability of a program execution on a processor micro-architecture. We model the protection achieved by various state-of-the-art CFC techniques in this quantitative vulnerability estimation setup, and find out that software only CFC protection schemes (CFCSS, CFCSS+NA, CEDA) increase system vulnerability by 18% to 21% with 17% to 38% performance overhead. Hybrid CFC protection (CFEDC) increases vulnerability by 5%, while the vulnerability remains almost the same for hardware only CFC protection (CFCET); notwithstanding the hardware overheads of design cost, area, and power incurred in the hardware modifications required for their implementations.
ContributorsRhisheekesan, Abhishek (Author) / Shrivastava, Aviral (Thesis advisor) / Colbourn, Charles Joseph (Committee member) / Wu, Carole-Jean (Committee member) / Arizona State University (Publisher)
Created2013
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Description
We are expecting hundreds of cores per chip in the near future. However, scaling the memory architecture in manycore architectures becomes a major challenge. Cache coherence provides a single image of memory at any time in execution to all the cores, yet coherent cache architectures are believed will not scale

We are expecting hundreds of cores per chip in the near future. However, scaling the memory architecture in manycore architectures becomes a major challenge. Cache coherence provides a single image of memory at any time in execution to all the cores, yet coherent cache architectures are believed will not scale to hundreds and thousands of cores. In addition, caches and coherence logic already take 20-50% of the total power consumption of the processor and 30-60% of die area. Therefore, a more scalable architecture is needed for manycore architectures. Software Managed Manycore (SMM) architectures emerge as a solution. They have scalable memory design in which each core has direct access to only its local scratchpad memory, and any data transfers to/from other memories must be done explicitly in the application using Direct Memory Access (DMA) commands. Lack of automatic memory management in the hardware makes such architectures extremely power-efficient, but they also become difficult to program. If the code/data of the task mapped onto a core cannot fit in the local scratchpad memory, then DMA calls must be added to bring in the code/data before it is required, and it may need to be evicted after its use. However, doing this adds a lot of complexity to the programmer's job. Now programmers must worry about data management, on top of worrying about the functional correctness of the program - which is already quite complex. This dissertation presents a comprehensive compiler and runtime integration to automatically manage the code and data of each task in the limited local memory of the core. We firstly developed a Complete Circular Stack Management. It manages stack frames between the local memory and the main memory, and addresses the stack pointer problem as well. Though it works, we found we could further optimize the management for most cases. Thus a Smart Stack Data Management (SSDM) is provided. In this work, we formulate the stack data management problem and propose a greedy algorithm for the same. Later on, we propose a general cost estimation algorithm, based on which CMSM heuristic for code mapping problem is developed. Finally, heap data is dynamic in nature and therefore it is hard to manage it. We provide two schemes to manage unlimited amount of heap data in constant sized region in the local memory. In addition to those separate schemes for different kinds of data, we also provide a memory partition methodology.
ContributorsBai, Ke (Author) / Shrivastava, Aviral (Thesis advisor) / Chatha, Karamvir (Committee member) / Xue, Guoliang (Committee member) / Chakrabarti, Chaitali (Committee member) / Arizona State University (Publisher)
Created2014
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Description
In this thesis we deal with the problem of temporal logic robustness estimation. We present a dynamic programming algorithm for the robust estimation problem of Metric Temporal Logic (MTL) formulas regarding a finite trace of time stated sequence. This algorithm not only tests if the MTL specification is satisfied by

In this thesis we deal with the problem of temporal logic robustness estimation. We present a dynamic programming algorithm for the robust estimation problem of Metric Temporal Logic (MTL) formulas regarding a finite trace of time stated sequence. This algorithm not only tests if the MTL specification is satisfied by the given input which is a finite system trajectory, but also quantifies to what extend does the sequence satisfies or violates the MTL specification. The implementation of the algorithm is the DP-TALIRO toolbox for MATLAB. Currently it is used as the temporal logic robust computing engine of S-TALIRO which is a tool for MATLAB searching for trajectories of minimal robustness in Simulink/ Stateflow. DP-TALIRO is expected to have near linear running time and constant memory requirement depending on the structure of the MTL formula. DP-TALIRO toolbox also integrates new features not supported in its ancestor FW-TALIRO such as parameter replacement, most related iteration and most related predicate. A derivative of DP-TALIRO which is DP-T-TALIRO is also addressed in this thesis which applies dynamic programming algorithm for time robustness computation. We test the running time of DP-TALIRO and compare it with FW-TALIRO. Finally, we present an application where DP-TALIRO is used as the robustness computation core of S-TALIRO for a parameter estimation problem.
ContributorsYang, Hengyi (Author) / Fainekos, Georgios (Thesis advisor) / Sarjoughian, Hessam S. (Committee member) / Shrivastava, Aviral (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Research on priming has shown that exposure to the concept of fast food can have an effect on human behavior by inducing haste and impatience (Zhong & E. DeVoe, 2010). This research suggests that thinking about fast food makes individuals impatient and strengthens their desire to complete tasks such as

Research on priming has shown that exposure to the concept of fast food can have an effect on human behavior by inducing haste and impatience (Zhong & E. DeVoe, 2010). This research suggests that thinking about fast food makes individuals impatient and strengthens their desire to complete tasks such as reading and decision making as quickly and efficiently as possible. Two experiments were conducted in which the effects of fast food priming were examined using a driving simulator. The experiments examined whether fast food primes can induce impatient driving. In experiment 1, 30 adult drivers drove a course in a driving simulator after being exposed to images by rating aesthetics of four different logos. Experiment 1 did not yield faster driving speeds nor an impatient and faster break at the yellow light in the fast food logo prime condition. In experiment 2, 30 adult drivers drove the same course from experiment 1. Participants did not rate logos on their aesthetics prior to the drive, instead billboards were included in the simulation that had either fast food or diner logos. Experiment 2 did not yielded faster driving speeds, however there was a significant effect of faster breaking and a higher number of participants running the yellow light.
ContributorsTaggart, Mistey. L (Author) / Branaghan, Russell (Thesis advisor) / Cooke, Nancy J. (Committee member) / Song, Hyunjin (Committee member) / Arizona State University (Publisher)
Created2014
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Description
Software has a great impact on the energy efficiency of any computing system--it can manage the components of a system efficiently or inefficiently. The impact of software is amplified in the context of a wearable computing system used for activity recognition. The design space this platform opens up is immense

Software has a great impact on the energy efficiency of any computing system--it can manage the components of a system efficiently or inefficiently. The impact of software is amplified in the context of a wearable computing system used for activity recognition. The design space this platform opens up is immense and encompasses sensors, feature calculations, activity classification algorithms, sleep schedules, and transmission protocols. Design choices in each of these areas impact energy use, overall accuracy, and usefulness of the system. This thesis explores methods software can influence the trade-off between energy consumption and system accuracy. In general the more energy a system consumes the more accurate will be. We explore how finding the transitions between human activities is able to reduce the energy consumption of such systems without reducing much accuracy. We introduce the Log-likelihood Ratio Test as a method to detect transitions, and explore how choices of sensor, feature calculations, and parameters concerning time segmentation affect the accuracy of this method. We discovered an approximate 5X increase in energy efficiency could be achieved with only a 5% decrease in accuracy. We also address how a system's sleep mode, in which the processor enters a low-power state and sensors are turned off, affects a wearable computing platform that does activity recognition. We discuss the energy trade-offs in each stage of the activity recognition process. We find that careful analysis of these parameters can result in great increases in energy efficiency if small compromises in overall accuracy can be tolerated. We call this the ``Great Compromise.'' We found a 6X increase in efficiency with a 7% decrease in accuracy. We then consider how wireless transmission of data affects the overall energy efficiency of a wearable computing platform. We find that design decisions such as feature calculations and grouping size have a great impact on the energy consumption of the system because of the amount of data that is stored and transmitted. For example, storing and transmitting vector-based features such as FFT or DCT do not compress the signal and would use more energy than storing and transmitting the raw signal. The effect of grouping size on energy consumption depends on the feature. For scalar features energy consumption is proportional in the inverse of grouping size, so it's reduced as grouping size goes up. For features that depend on the grouping size, such as FFT, energy increases with the logarithm of grouping size, so energy consumption increases slowly as grouping size increases. We find that compressing data through activity classification and transition detection significantly reduces energy consumption and that the energy consumed for the classification overhead is negligible compared to the energy savings from data compression. We provide mathematical models of energy usage and data generation, and test our ideas using a mobile computing platform, the Texas Instruments Chronos watch.
ContributorsBoyd, Jeffrey Michael (Author) / Sundaram, Hari (Thesis advisor) / Li, Baoxin (Thesis advisor) / Shrivastava, Aviral (Committee member) / Turaga, Pavan (Committee member) / Arizona State University (Publisher)
Created2014
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Description
Coarse-Grained Reconfigurable Architectures (CGRA) are a promising fabric for improving the performance and power-efficiency of computing devices. CGRAs are composed of components that are well-optimized to execute loops and rotating register file is an example of such a component present in CGRAs. Due to the rotating nature of register indexes

Coarse-Grained Reconfigurable Architectures (CGRA) are a promising fabric for improving the performance and power-efficiency of computing devices. CGRAs are composed of components that are well-optimized to execute loops and rotating register file is an example of such a component present in CGRAs. Due to the rotating nature of register indexes in rotating register file, it is very challenging, if at all possible, to hold and properly index memory addresses (pointers) and static values. In this Thesis, different structures for CGRA register files are investigated. Those structures are experimentally compared in terms of performance of mapped applications, design frequency, and area. It is shown that a register file that can logically be partitioned into rotating and non-rotating regions is an excellent choice because it imposes the minimum restriction on underlying CGRA mapping algorithm while resulting in efficient resource utilization.
ContributorsSaluja, Dipal (Author) / Shrivastava, Aviral (Thesis advisor) / Lee, Yann-Hang (Committee member) / Wu, Carole-Jean (Committee member) / Arizona State University (Publisher)
Created2014
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Description
When discussing human factors and performance, researchers recognize stress as a factor, but overlook mood as contributing factor. To explore the relationship between mood, stress and cognitive performance, a field study was conducted involving fire fighters engaged in a fire response simulation. Firefighter participants completed a stress questionnaire, an emotional

When discussing human factors and performance, researchers recognize stress as a factor, but overlook mood as contributing factor. To explore the relationship between mood, stress and cognitive performance, a field study was conducted involving fire fighters engaged in a fire response simulation. Firefighter participants completed a stress questionnaire, an emotional state questionnaire, and a cognitive task. Stress and cognitive task performance scores were examined before and after the firefighting simulation for individual cognitive performance depreciation caused by stress or mood. They study revealed that existing stress was a reliable predictor of the pre-simulation cognitive task score, that, as mood becomes more positive, perceived stress scores decrease, and that negative mood and pre-simulation stress are also positively and significantly correlated.
ContributorsGomez-Herbert, Maria Elena (Author) / Cooke, Nancy J. (Thesis advisor) / Becker, Vaughn (Committee member) / Branaghan, Russell (Committee member) / Hyunjin, Song (Committee member) / Arizona State University (Publisher)
Created2014
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Description
Preoperative team briefings have been suggested to be important for improving team performance in the operating room. Many high risk environments have accepted team briefings; however healthcare has been slower to follow. While applying briefings in the operating room has shown positive benefits including improved communication and perceptions of teamwork,

Preoperative team briefings have been suggested to be important for improving team performance in the operating room. Many high risk environments have accepted team briefings; however healthcare has been slower to follow. While applying briefings in the operating room has shown positive benefits including improved communication and perceptions of teamwork, most research has only focused on feasibility of implementation and not on understanding how the quality of briefings can impact subsequent surgical procedures. Thus, there are no formal protocols or methodologies that have been developed.

The goal of this study was to relate specific characteristics of team briefings back to objective measures of team performance. The study employed cognitive interviews, prospective observations, and principle component regression to characterize and model the relationship between team briefing characteristics and non-routine events (NREs) in gynecological surgery. Interviews were conducted with 13 team members representing each role on the surgical team and data were collected for 24 pre-operative team briefings and 45 subsequent surgical cases. The findings revealed that variations within the team briefing are associated with differences in team-related outcomes, namely NREs, during the subsequent surgical procedures. Synthesis of the data highlighted three important trends which include the need to promote team communication during the briefing, the importance of attendance by all surgical team members, and the value of holding a briefing prior to each surgical procedure. These findings have implications for development of formal briefing protocols.

Pre-operative team briefings are beneficial for team performance in the operating room. Future research will be needed to continue understanding this relationship between how briefings are conducted and team performance to establish more consistent approaches and as well as for the continuing assessment of team briefings and other similar team-related events in the operating room.
ContributorsHildebrand, Emily A (Author) / Branaghan, Russell J (Thesis advisor) / Cooke, Nancy J. (Committee member) / Hallbeck, M. Susan (Committee member) / Bekki, Jennifer M (Committee member) / Blocker, Renaldo C (Committee member) / Arizona State University (Publisher)
Created2014