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Description
Reliable extraction of human pose features that are invariant to view angle and body shape changes is critical for advancing human movement analysis. In this dissertation, the multifactor analysis techniques, including the multilinear analysis and the multifactor Gaussian process methods, have been exploited to extract such invariant pose features from

Reliable extraction of human pose features that are invariant to view angle and body shape changes is critical for advancing human movement analysis. In this dissertation, the multifactor analysis techniques, including the multilinear analysis and the multifactor Gaussian process methods, have been exploited to extract such invariant pose features from video data by decomposing various key contributing factors, such as pose, view angle, and body shape, in the generation of the image observations. Experimental results have shown that the resulting pose features extracted using the proposed methods exhibit excellent invariance properties to changes in view angles and body shapes. Furthermore, using the proposed invariant multifactor pose features, a suite of simple while effective algorithms have been developed to solve the movement recognition and pose estimation problems. Using these proposed algorithms, excellent human movement analysis results have been obtained, and most of them are superior to those obtained from state-of-the-art algorithms on the same testing datasets. Moreover, a number of key movement analysis challenges, including robust online gesture spotting and multi-camera gesture recognition, have also been addressed in this research. To this end, an online gesture spotting framework has been developed to automatically detect and learn non-gesture movement patterns to improve gesture localization and recognition from continuous data streams using a hidden Markov network. In addition, the optimal data fusion scheme has been investigated for multicamera gesture recognition, and the decision-level camera fusion scheme using the product rule has been found to be optimal for gesture recognition using multiple uncalibrated cameras. Furthermore, the challenge of optimal camera selection in multi-camera gesture recognition has also been tackled. A measure to quantify the complementary strength across cameras has been proposed. Experimental results obtained from a real-life gesture recognition dataset have shown that the optimal camera combinations identified according to the proposed complementary measure always lead to the best gesture recognition results.
ContributorsPeng, Bo (Author) / Qian, Gang (Thesis advisor) / Ye, Jieping (Committee member) / Li, Baoxin (Committee member) / Spanias, Andreas (Committee member) / Arizona State University (Publisher)
Created2011
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Description
Ever reducing time to market, along with short product lifetimes, has created a need to shorten the microprocessor design time. Verification of the design and its analysis are two major components of this design cycle. Design validation techniques can be broadly classified into two major categories: simulation based approaches and

Ever reducing time to market, along with short product lifetimes, has created a need to shorten the microprocessor design time. Verification of the design and its analysis are two major components of this design cycle. Design validation techniques can be broadly classified into two major categories: simulation based approaches and formal techniques. Simulation based microprocessor validation involves running millions of cycles using random or pseudo random tests and allows verification of the register transfer level (RTL) model against an architectural model, i.e., that the processor executes instructions as required. The validation effort involves model checking to a high level description or simulation of the design against the RTL implementation. Formal techniques exhaustively analyze parts of the design but, do not verify RTL against the architecture specification. The focus of this work is to implement a fully automated validation environment for a MIPS based radiation hardened microprocessor using simulation based approaches. The basic framework uses the classical validation approach in which the design to be validated is described in a Hardware Definition Language (HDL) such as VHDL or Verilog. To implement a simulation based approach a number of random or pseudo random tests are generated. The output of the HDL based design is compared against the one obtained from a "perfect" model implementing similar functionality, a mismatch in the results would thus indicate a bug in the HDL based design. Effort is made to design the environment in such a manner that it can support validation during different stages of the design cycle. The validation environment includes appropriate changes so as to support architecture changes which are introduced because of radiation hardening. The manner in which the validation environment is build is highly dependent on the specifications of the perfect model used for comparisons. This work implements the validation environment for two MIPS simulators as the reference model. Two bugs have been discovered in the RTL model, using simulation based approaches through the validation environment.
ContributorsSharma, Abhishek (Author) / Clark, Lawrence (Thesis advisor) / Holbert, Keith E. (Committee member) / Shrivastava, Aviral (Committee member) / Arizona State University (Publisher)
Created2011
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Description
As the complexity of robotic systems and applications grows rapidly, development of high-performance, easy to use, and fully integrated development environments for those systems is inevitable. Model-Based Design (MBD) of dynamic systems using engineering software such as Simulink® from MathWorks®, SciCos from Metalau team and SystemModeler® from Wolfram® is quite

As the complexity of robotic systems and applications grows rapidly, development of high-performance, easy to use, and fully integrated development environments for those systems is inevitable. Model-Based Design (MBD) of dynamic systems using engineering software such as Simulink® from MathWorks®, SciCos from Metalau team and SystemModeler® from Wolfram® is quite popular nowadays. They provide tools for modeling, simulation, verification and in some cases automatic code generation for desktop applications, embedded systems and robots. For real-world implementation of models on the actual hardware, those models should be converted into compilable machine code either manually or automatically. Due to the complexity of robotic systems, manual code translation from model to code is not a feasible optimal solution so we need to move towards automated code generation for such systems. MathWorks® offers code generation facilities called Coder® products for this purpose. However in order to fully exploit the power of model-based design and code generation tools for robotic applications, we need to enhance those software systems by adding and modifying toolboxes, files and other artifacts as well as developing guidelines and procedures. In this thesis, an effort has been made to propose a guideline as well as a Simulink® library, StateFlow® interface API and a C/C++ interface API to complete this toolchain for NAO humanoid robots. Thus the model of the hierarchical control architecture can be easily and properly converted to code and built for implementation.
ContributorsRaji Kermani, Ramtin (Author) / Fainekos, Georgios (Thesis advisor) / Lee, Yann-Hang (Committee member) / Sarjoughian, Hessam S. (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Stream computing has emerged as an importantmodel of computation for embedded system applications particularly in the multimedia and network processing domains. In recent past several programming languages and embedded multi-core processors have been proposed for streaming applications. This thesis examines the execution and dynamic scheduling of stream programs on embedded

Stream computing has emerged as an importantmodel of computation for embedded system applications particularly in the multimedia and network processing domains. In recent past several programming languages and embedded multi-core processors have been proposed for streaming applications. This thesis examines the execution and dynamic scheduling of stream programs on embedded multi-core processors. The thesis addresses the problem in the context of a multi-tasking environment with a time varying allocation of processing elements for a particular streaming application. As a solution the thesis proposes a two step approach where the stream program is compiled to gather key application information, and to generate re-targetable code. A light weight dynamic scheduler incorporates the second stage of the approach. The dynamic scheduler utilizes the static information and available resources to assign or partition the application across the multi-core architecture. The objective of the dynamic scheduler is to maximize the throughput of the application, and it is sensitive to the resource (processing elements, scratch-pad memory, DMA bandwidth) constraints imposed by the target architecture. We evaluate the proposed approach by compiling and scheduling benchmark stream programs on a representative embedded multi-core processor. We present experimental results that evaluate the quality of the solutions generated by the proposed approach by comparisons with existing techniques.
ContributorsLee, Haeseung (Author) / Chatha, Karamvir (Thesis advisor) / Vrudhula, Sarma (Committee member) / Chakrabarti, Chaitali (Committee member) / Wu, Carole-Jean (Committee member) / Arizona State University (Publisher)
Created2013
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Description
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

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 to model processor power consumption, there is a lack of such models to capture power consumption at the task-level. Task-level energy models are a requirement for an operating system (OS) to perform real-time power management as OS time multiplexes tasks to enable sharing of hardware resources. I propose a detailed design methodology for constructing an architecture agnostic task-level power model and incorporating it into a modern operating system to build an online task-level power profiler. The profiler is implemented inside the latest Linux kernel and validated for Intel Sandy Bridge processor. It has a negligible overhead of less than 1\% hardware resource consumption. The profiler power prediction was demonstrated for various application benchmarks from SPEC to PARSEC with less than 4\% error. I also demonstrate the importance of the proposed profiler for emerging architectural techniques through use case scenarios, which include heterogeneous computing and fine grained per-core DVFS. Along with architectural enhancement in general purpose processors to improve energy efficiency, hardware accelerators like Coarse Grain reconfigurable architecture (CGRA) are gaining popularity. Unlike vector processors, which rely on data parallelism, CGRA can provide greater flexibility and compiler level control making it more suitable for present SoC environment. To provide streamline development environment for CGRA, I propose a flexible framework in Linux to do design space exploration for CGRA. With accurate and flexible hardware models, fine grained integration with accurate architectural simulator, and Linux memory management and DMA support, a user can carry out limitless experiments on CGRA in full system environment.
ContributorsDesai, Digant Pareshkumar (Author) / Vrudhula, Sarma (Thesis advisor) / Chakrabarti, Chaitali (Committee member) / Wu, Carole-Jean (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Situations of sensory overload are steadily becoming more frequent as the ubiquity of technology approaches reality--particularly with the advent of socio-communicative smartphone applications, and pervasive, high speed wireless networks. Although the ease of accessing information has improved our communication effectiveness and efficiency, our visual and auditory modalities--those modalities that today's

Situations of sensory overload are steadily becoming more frequent as the ubiquity of technology approaches reality--particularly with the advent of socio-communicative smartphone applications, and pervasive, high speed wireless networks. Although the ease of accessing information has improved our communication effectiveness and efficiency, our visual and auditory modalities--those modalities that today's computerized devices and displays largely engage--have become overloaded, creating possibilities for distractions, delays and high cognitive load; which in turn can lead to a loss of situational awareness, increasing chances for life threatening situations such as texting while driving. Surprisingly, alternative modalities for information delivery have seen little exploration. Touch, in particular, is a promising candidate given that it is our largest sensory organ with impressive spatial and temporal acuity. Although some approaches have been proposed for touch-based information delivery, they are not without limitations including high learning curves, limited applicability and/or limited expression. This is largely due to the lack of a versatile, comprehensive design theory--specifically, a theory that addresses the design of touch-based building blocks for expandable, efficient, rich and robust touch languages that are easy to learn and use. Moreover, beyond design, there is a lack of implementation and evaluation theories for such languages. To overcome these limitations, a unified, theoretical framework, inspired by natural, spoken language, is proposed called Somatic ABC's for Articulating (designing), Building (developing) and Confirming (evaluating) touch-based languages. To evaluate the usefulness of Somatic ABC's, its design, implementation and evaluation theories were applied to create communication languages for two very unique application areas: audio described movies and motor learning. These applications were chosen as they presented opportunities for complementing communication by offloading information, typically conveyed visually and/or aurally, to the skin. For both studies, it was found that Somatic ABC's aided the design, development and evaluation of rich somatic languages with distinct and natural communication units.
ContributorsMcDaniel, Troy Lee (Author) / Panchanathan, Sethuraman (Thesis advisor) / Davulcu, Hasan (Committee member) / Li, Baoxin (Committee member) / Santello, Marco (Committee member) / Arizona State University (Publisher)
Created2012
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Description
Performance improvements have largely followed Moore's Law due to the help from technology scaling. In order to continue improving performance, power-efficiency must be reduced. Better technology has improved power-efficiency, but this has a limit. Multi-core architectures have been shown to be an additional aid to this crusade of increased power-efficiency.

Performance improvements have largely followed Moore's Law due to the help from technology scaling. In order to continue improving performance, power-efficiency must be reduced. Better technology has improved power-efficiency, but this has a limit. Multi-core architectures have been shown to be an additional aid to this crusade of increased power-efficiency. Accelerators are growing in popularity as the next means of achieving power-efficient performance. Accelerators such as Intel SSE are ideal, but prove difficult to program. FPGAs, on the other hand, are less efficient due to their fine-grained reconfigurability. A middle ground is found in CGRAs, which are highly power-efficient, but largely programmable accelerators. Power-efficiencies of 100s of GOPs/W have been estimated, more than 2 orders of magnitude greater than current processors. Currently, CGRAs are limited in their applicability due to their ability to only accelerate a single thread at a time. This limitation becomes especially apparent as multi-core/multi-threaded processors have moved into the mainstream. This limitation is removed by enabling multi-threading on CGRAs through a software-oriented approach. The key capability in this solution is enabling quick run-time transformation of schedules to execute on targeted portions of the CGRA. This allows the CGRA to be shared among multiple threads simultaneously. Analysis shows that enabling multi-threading has very small costs but provides very large benefits (less than 1% single-threaded performance loss but nearly 300% CGRA throughput increase). By increasing dynamism of CGRA scheduling, system performance is shown to increase overall system performance of an optimized system by almost 350% over that of a single-threaded CGRA and nearly 20x faster than the same system with no CGRA in a highly threaded environment.
ContributorsPager, Jared (Author) / Shrivastava, Aviral (Thesis advisor) / Gupta, Sandeep (Committee member) / Speyer, Gil (Committee member) / Arizona State University (Publisher)
Created2011
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Description
Limited Local Memory (LLM) multicore architectures are promising powerefficient architectures will scalable memory hierarchy. In LLM multicores, each core can access only a small local memory. Accesses to a large shared global memory can only be made explicitly through Direct Memory Access (DMA) operations. Standard Template Library (STL) is a

Limited Local Memory (LLM) multicore architectures are promising powerefficient architectures will scalable memory hierarchy. In LLM multicores, each core can access only a small local memory. Accesses to a large shared global memory can only be made explicitly through Direct Memory Access (DMA) operations. Standard Template Library (STL) is a powerful programming tool and is widely used for software development. STLs provide dynamic data structures, algorithms, and iterators for vector, deque (double-ended queue), list, map (red-black tree), etc. Since the size of the local memory is limited in the cores of the LLM architecture, and data transfer is not automatically supported by hardware cache or OS, the usage of current STL implementation on LLM multicores is limited. Specifically, there is a hard limitation on the amount of data they can handle. In this article, we propose and implement a framework which manages the STL container classes on the local memory of LLM multicore architecture. Our proposal removes the data size limitation of the STL, and therefore improves the programmability on LLM multicore architectures with little change to the original program. Our implementation results in only about 12%-17% increase in static library code size and reasonable runtime overheads.
ContributorsLu, Di (Author) / Shrivastava, Aviral (Thesis advisor) / Chatha, Karamvir (Committee member) / Dasgupta, Partha (Committee member) / Arizona State University (Publisher)
Created2012
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Description
The ubiquity of embedded computational systems has exploded in recent years impacting everything from hand-held computers and automotive driver assistance to battlefield command and control and autonomous systems. Typical embedded computing systems are characterized by highly resource constrained operating environments. In particular, limited energy resources constrain performance in embedded systems

The ubiquity of embedded computational systems has exploded in recent years impacting everything from hand-held computers and automotive driver assistance to battlefield command and control and autonomous systems. Typical embedded computing systems are characterized by highly resource constrained operating environments. In particular, limited energy resources constrain performance in embedded systems often reliant on independent fuel or battery supplies. Ultimately, mitigating energy consumption without sacrificing performance in these systems is paramount. In this work power/performance optimization emphasizing prevailing data centric applications including video and signal processing is addressed for energy constrained embedded systems. Frameworks are presented which exchange quality of service (QoS) for reduced power consumption enabling power aware energy management. Power aware systems provide users with tools for precisely managing available energy resources in light of user priorities, extending availability when QoS can be sacrificed. Specifically, power aware management tools for next generation bistable electrophoretic displays and the state of the art H.264 video codec are introduced. The multiprocessor system on chip (MPSoC) paradigm is examined in the context of next generation many-core hand-held computing devices. MPSoC architectures promise to breach the power/performance wall prohibiting advancement of complex high performance single core architectures. Several many-core distributed memory MPSoC architectures are commercially available, while the tools necessary to effectively tap their enormous potential remain largely open for discovery. Adaptable scalability in many-core systems is addressed through a scalable high performance multicore H.264 video decoder implemented on the representative Cell Broadband Engine (CBE) architecture. The resulting agile performance scalable system enables efficient adaptive power optimization via decoding-rate driven sleep and voltage/frequency state management. The significant problem of mapping applications onto these architectures is additionally addressed from the perspective of instruction mapping for limited distributed memory architectures with a code overlay generator implemented on the CBE. Finally runtime scheduling and mapping of scalable applications in multitasking environments is addressed through the introduction of a lightweight work partitioning framework targeting streaming applications with low latency and near optimal throughput demonstrated on the CBE.
ContributorsBaker, Michael (Author) / Chatha, Karam S. (Thesis advisor) / Raupp, Gregory B. (Committee member) / Vrudhula, Sarma B. K. (Committee member) / Shrivastava, Aviral (Committee member) / Arizona State University (Publisher)
Created2011
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Description
Threshold logic has long been studied as a means of achieving higher performance and lower power dissipation, providing improvements by condensing simple logic gates into more complex primitives, effectively reducing gate count, pipeline depth, and number of interconnects. This work proposes a new physical implementation of threshold logic, the threshold

Threshold logic has long been studied as a means of achieving higher performance and lower power dissipation, providing improvements by condensing simple logic gates into more complex primitives, effectively reducing gate count, pipeline depth, and number of interconnects. This work proposes a new physical implementation of threshold logic, the threshold logic latch (TLL), which overcomes the difficulties observed in previous work, particularly with respect to gate reliability in the presence of noise and process variations. Simple but effective models were created to assess the delay, power, and noise margin of TLL gates for the purpose of determining the physical parameters and assignment of input signals that achieves the lowest delay subject to constraints on power and reliability. From these models, an optimized library of standard TLL cells was developed to supplement a commercial library of static CMOS gates. The new cells were then demonstrated on a number of automatically synthesized, placed, and routed designs. A two-stage 2's complement integer multiplier designed with CMOS and TLL gates utilized 19.5% less area, 28.0% less active power, and 61.5% less leakage power than an equivalent design with the same performance using only static CMOS gates. Additionally, a two-stage 32-instruction 4-way issue queue designed with CMOS and TLL gates utilized 30.6% less area, 31.0% less active power, and 58.9% less leakage power than an equivalent design with the same performance using only static CMOS gates.
ContributorsLeshner, Samuel (Author) / Vrudhula, Sarma (Thesis advisor) / Chatha, Karamvir (Committee member) / Clark, Lawrence (Committee member) / Shrivastava, Aviral (Committee member) / Arizona State University (Publisher)
Created2010