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- Genre: Doctoral Dissertation
- Creators: Yu, Hongbin
- Creators: Xue, Guoliang
Description
A workload-aware low-power neuromorphic controller for dynamic power and thermal management in VLSI systems is presented. The neuromorphic controller predicts future workload and temperature values based on the past values and CPU performance counters and preemptively regulates supply voltage and frequency. System-level measurements from stateof-the-art commercial microprocessors are used to get workload, temperature and CPU performance counter values. The controller is designed and simulated using circuit-design and synthesis tools. At device-level, on-chip planar inductors suffer from low inductance occupying large chip area. On-chip inductors with integrated magnetic materials are designed, simulated and fabricated to explore performance-efficiency trade offs and explore potential applications such as resonant clocking and on-chip voltage regulation. A system level study is conducted to evaluate the effect of on-chip voltage regulator employing magnetic inductors as the output filter. It is concluded that neuromorphic power controller is beneficial for fine-grained per-core power management in conjunction with on-chip voltage regulators utilizing scaled magnetic inductors.
ContributorsSinha, Saurabh (Author) / Cao, Yu (Thesis advisor) / Bakkaloglu, Bertan (Committee member) / Yu, Hongbin (Committee member) / Christen, Jennifer B. (Committee member) / Arizona State University (Publisher)
Created2011
Description
CMOS technology is expected to enter the 10nm regime for future integrated circuits (IC). Such aggressive scaling leads to vastly increased variability, posing a grand challenge to robust IC design. Variations in CMOS are often divided into two types: intrinsic variations and process-induced variations. Intrinsic variations are limited by fundamental physics. They are inherent to CMOS structure, considered as one of the ultimate barriers to the continual scaling of CMOS devices. In this work the three primary intrinsic variations sources are studied, including random dopant fluctuation (RDF), line-edge roughness (LER) and oxide thickness fluctuation (OTF). The research is focused on the modeling and simulation of those variations and their scaling trends. Besides the three variations, a time dependent variation source, Random Telegraph Noise (RTN) is also studied. Different from the other three variations, RTN does not contribute much to the total variation amount, but aggregate the worst case of Vth variations in CMOS. In this work a TCAD based simulation study on RTN is presented, and a new SPICE based simulation method for RTN is proposed for time domain circuit analysis. Process-induced variations arise from the imperfection in silicon fabrication, and vary from foundries to foundries. In this work the layout dependent Vth shift due to Rapid-Thermal Annealing (RTA) are investigated. In this work, we develop joint thermal/TCAD simulation and compact modeling tools to analyze performance variability under various layout pattern densities and RTA conditions. Moreover, we propose a suite of compact models that bridge the underlying RTA process with device parameter change for efficient design optimization.
ContributorsYe, Yun, Ph.D (Author) / Cao, Yu (Thesis advisor) / Yu, Hongbin (Committee member) / Song, Hongjiang (Committee member) / Clark, Lawrence (Committee member) / Arizona State University (Publisher)
Created2011
Description
Semiconductor nanowires (NWs) are one dimensional materials and have size quantization effect when the diameter is sufficiently small. They can serve as optical wave guides along the length direction and contain optically active gain at the same time. Due to these unique properties, NWs are now very promising and extensively studied for nanoscale optoelectronic applications. A systematic and comprehensive optical and microstructural study of several important infrared semiconductor NWs is presented in this thesis, which includes InAs, PbS, InGaAs, erbium chloride silicate and erbium silicate. Micro-photoluminescence (PL) and transmission electron microscope (TEM) were utilized in conjunction to characterize the optical and microstructure of these wires. The focus of this thesis is on optical study of semiconductor NWs in the mid-infrared wavelengths. First, differently structured InAs NWs grown using various methods were characterized and compared. Three main PL peaks which are below, near and above InAs bandgap, respectively, were observed. The octadecylthiol self-assembled monolayer was employed to passivate the surface of InAs NWs to eliminate or reduce the effects of the surface states. The band-edge emission from wurtzite-structured NWs was completely recovered after passivatoin. The passivated NWs showed very good stability in air and under heat. In the second part, mid-infrared optical study was conducted on PbS wires of subwavelength diameter and lasing was demonstrated under optical pumping. The PbS wires were grown on Si substrate using chemical vapor deposition and have a rock-salt cubic structure. Single-mode lasing at the wavelength of ~3000-4000 nm was obtained from single as-grown PbS wire up to the temperature of 115 K. PL characterization was also utilized to demonstrate the highest crystallinity of the vertical arrays of InP and InGaAs/InP composition-graded heterostructure NWs made by a top-down fabrication method. TEM-related measurements were performed to study the crystal structures and elemental compositions of the Er-compound core-shell NWs. The core-shell NWs consist of an orthorhombic-structured erbium chloride silicate shell and a cubic-structured silicon core. These NWs provide unique Si-compatible materials with emission at 1530 nm for optical communications and solid state lasers.
ContributorsSun, Minghua (Author) / Ning, Cun-Zheng (Thesis advisor) / Yu, Hongbin (Committee member) / Carpenter, Ray W. (Committee member) / Johnson, Shane (Committee member) / Arizona State University (Publisher)
Created2011
Description
Multi-task learning (MTL) aims to improve the generalization performance (of the resulting classifiers) by learning multiple related tasks simultaneously. Specifically, MTL exploits the intrinsic task relatedness, based on which the informative domain knowledge from each task can be shared across multiple tasks and thus facilitate the individual task learning. It is particularly desirable to share the domain knowledge (among the tasks) when there are a number of related tasks but only limited training data is available for each task. Modeling the relationship of multiple tasks is critical to the generalization performance of the MTL algorithms. In this dissertation, I propose a series of MTL approaches which assume that multiple tasks are intrinsically related via a shared low-dimensional feature space. The proposed MTL approaches are developed to deal with different scenarios and settings; they are respectively formulated as mathematical optimization problems of minimizing the empirical loss regularized by different structures. For all proposed MTL formulations, I develop the associated optimization algorithms to find their globally optimal solution efficiently. I also conduct theoretical analysis for certain MTL approaches by deriving the globally optimal solution recovery condition and the performance bound. To demonstrate the practical performance, I apply the proposed MTL approaches on different real-world applications: (1) Automated annotation of the Drosophila gene expression pattern images; (2) Categorization of the Yahoo web pages. Our experimental results demonstrate the efficiency and effectiveness of the proposed algorithms.
ContributorsChen, Jianhui (Author) / Ye, Jieping (Thesis advisor) / Kumar, Sudhir (Committee member) / Liu, Huan (Committee member) / Xue, Guoliang (Committee member) / Arizona State University (Publisher)
Created2011
Description
With increasing demand for System on Chip (SoC) and System in Package (SiP) design in computer and communication technologies, integrated inductor which is an essential passive component has been widely used in numerous integrated circuits (ICs) such as in voltage regulators and RF circuits. In this work, soft ferromagnetic core material, amorphous Co-Zr-Ta-B, was incorporated into on-chip and in-package inductors in order to scale down inductors and improve inductors performance in both inductance density and quality factor. With two layers of 500 nm Co-Zr-Ta-B films a 3.5X increase in inductance and a 3.9X increase in quality factor over inductors without magnetic films were measured at frequencies as high as 1 GHz. By laminating technology, up to 9.1X increase in inductance and more than 5X increase in quality factor (Q) were obtained from stripline inductors incorporated with 50 nm by 10 laminated films with a peak Q at 300 MHz. It was also demonstrated that this peak Q can be pushed towards high frequency as far as 1GHz by a combination of patterning magnetic films into fine bars and laminations. The role of magnetic vias in magnetic flux and eddy current control was investigated by both simulation and experiment using different patterning techniques and by altering the magnetic via width. Finger-shaped magnetic vias were designed and integrated into on-chip RF inductors improving the frequency of peak quality factor from 400 MHz to 800 MHz without sacrificing inductance enhancement. Eddy current and magnetic flux density in different areas of magnetic vias were analyzed by HFSS 3D EM simulation. With optimized magnetic vias, high frequency response of up to 2 GHz was achieved. Furthermore, the effect of applied magnetic field on on-chip inductors was investigated for high power applications. It was observed that as applied magnetic field along the hard axis (HA) increases, inductance maintains similar value initially at low fields, but decreases at larger fields until the magnetic films become saturated. The high frequency quality factor showed an opposite trend which is correlated to the reduction of ferromagnetic resonant absorption in the magnetic film. In addition, experiments showed that this field-dependent inductance change varied with different patterned magnetic film structures, including bars/slots and fingers structures. Magnetic properties of Co-Zr-Ta-B films on standard organic package substrates including ABF and polyimide were also characterized. Effects of substrate roughness and stress were analyzed and simulated which provide strategies for integrating Co-Zr-Ta-B into package inductors and improving inductors performance. Stripline and spiral inductors with Co-Zr-Ta-B films were fabricated on both ABF and polyimide substrates. Maximum 90% inductance increase in hundreds MHz frequency range were achieved in stripline inductors which are suitable for power delivery applications. Spiral inductors with Co-Zr-Ta-B films showed 18% inductance increase with quality factor of 4 at frequency up to 3 GHz.
ContributorsWu, Hao (Author) / Yu, Hongbin (Thesis advisor) / Bakkaloglu, Bertan (Committee member) / Cao, Yu (Committee member) / Chickamenahalli, Shamala (Committee member) / Arizona State University (Publisher)
Created2013
Description
Zinc oxide (ZnO), a naturally n-type semiconductor has been identified as a promising candidate to replace indium tin oxide (ITO) as the transparent electrode in solar cells, because of its wide bandgap (3.37 eV), abundant source materials and suitable refractive index (2.0 at 600 nm). Spray deposition is a convenient and low cost technique for large area and uniform deposition of semiconductor thin films. In particular, it provides an easier way to dope the film by simply adding the dopant precursor into the starting solution. In order to reduce the resistivity of undoped ZnO, many works have been done by doping in the ZnO with either group IIIA elements or VIIA elements using spray pyrolysis. However, the resistivity is still too high to meet TCO's resistivity requirement. In the present work, a novel co-spray deposition technique is developed to bypass a fundamental limitation in the conventional spray deposition technique, i.e. the deposition of metal oxides from incompatible precursors in the starting solution. With this technique, ZnO films codoped with one cationic dopant, Al, Cr, or Fe, and an anionic dopant, F, have been successfully synthesized, in which F is incompatible with all these three cationic dopants. Two starting solutions were prepared and co-sprayed through two separate spray heads. One solution contained only the F precursor, NH 4F. The second solution contained the Zn and one cationic dopant precursors, Zn(O 2CCH 3) 2 and AlCl 3, CrCl 3, or FeCl 3. The deposition was carried out at 500 °C; on soda-lime glass in air. Compared to singly-doped ZnO thin films, codoped ZnO samples showed better electrical properties. Besides, a minimum sheet resistance, 55.4 Ω/sq, was obtained for Al and F codoped ZnO films after vacuum annealing at 400 °C;, which was lower than singly-doped ZnO with either Al or F. The transmittance for the Al and F codoped ZnO samples was above 90% in the visible range. This co-spray deposition technique provides a simple and cost-effective way to synthesize metal oxides from incompatible precursors with improved properties.
ContributorsZhou, Bin (Author) / Tao, Meng (Thesis advisor) / Goryll, Michael (Committee member) / Vasileska, Dragica (Committee member) / Yu, Hongbin (Committee member) / Arizona State University (Publisher)
Created2013
Description
Sparsity has become an important modeling tool in areas such as genetics, signal and audio processing, medical image processing, etc. Via the penalization of l-1 norm based regularization, the structured sparse learning algorithms can produce highly accurate models while imposing various predefined structures on the data, such as feature groups or graphs. In this thesis, I first propose to solve a sparse learning model with a general group structure, where the predefined groups may overlap with each other. Then, I present three real world applications which can benefit from the group structured sparse learning technique. In the first application, I study the Alzheimer's Disease diagnosis problem using multi-modality neuroimaging data. In this dataset, not every subject has all data sources available, exhibiting an unique and challenging block-wise missing pattern. In the second application, I study the automatic annotation and retrieval of fruit-fly gene expression pattern images. Combined with the spatial information, sparse learning techniques can be used to construct effective representation of the expression images. In the third application, I present a new computational approach to annotate developmental stage for Drosophila embryos in the gene expression images. In addition, it provides a stage score that enables one to more finely annotate each embryo so that they are divided into early and late periods of development within standard stage demarcations. Stage scores help us to illuminate global gene activities and changes much better, and more refined stage annotations improve our ability to better interpret results when expression pattern matches are discovered between genes.
ContributorsYuan, Lei (Author) / Ye, Jieping (Thesis advisor) / Wang, Yalin (Committee member) / Xue, Guoliang (Committee member) / Kumar, Sudhir (Committee member) / Arizona State University (Publisher)
Created2013
Description
Characterization of standard cells is one of the crucial steps in the IC design. Scaling of CMOS technology has lead to timing un-certainties such as that of cross coupling noise due to interconnect parasitic, skew variation due to voltage jitter and proximity effect of multiple inputs switching (MIS). Due to increased operating frequency and process variation, the probability of MIS occurrence and setup / hold failure within a clock cycle is high. The delay variation due to temporal proximity of MIS is significant for multiple input gates in the standard cell library. The shortest paths are affected by MIS due to the lack of averaging effect. Thus, sensitive designs such as that of SRAM row and column decoder circuits have high probability for MIS impact. The traditional static timing analysis (STA) assumes single input switching (SIS) scenario which is not adequate enough to capture gate delay accurately, as the delay variation due to temporal proximity of the MIS is ~15%-45%. Whereas, considering all possible scenarios of MIS for characterization is computationally intensive with huge data volume. Various modeling techniques are developed for the characterization of MIS effect. Some techniques require coefficient extraction through multiple spice simulation, and do not discuss speed up approach or apply models with complicated algorithms to account for MIS effect. The STA flow accounts for process variation through uncertainty parameter to improve product yield. Some of the MIS delay variability models account for MIS variation through table look up approach, resulting in huge data volume or do not consider propagation of RAT in the design flow. Thus, there is a need for a methodology to model MIS effect with less computational resource, and integration of such effect into design flow without trading off the accuracy. A finite-point based analytical model for MIS effect is proposed for multiple input logic gates and similar approach is extended for setup/hold characterization of sequential elements. Integration of MIS variation into design flow is explored. The proposed methodology is validated using benchmark circuits at 45nm technology node under process variation. Experimental results show significant reduction in runtime and data volume with ~10% error compared to that of SPICE simulation.
ContributorsSubramaniam, Anupama R (Author) / Cao, Yu (Thesis advisor) / Chakrabarti, Chaitali (Committee member) / Roveda, Janet (Committee member) / Yu, Hongbin (Committee member) / Arizona State University (Publisher)
Created2012
Description
A principal goal of this dissertation is to study stochastic optimization and real-time scheduling in cyber-physical systems (CPSs) ranging from real-time wireless systems to energy systems to distributed control systems. Under this common theme, this dissertation can be broadly organized into three parts based on the system environments. The first part investigates stochastic optimization in real-time wireless systems, with the focus on the deadline-aware scheduling for real-time traffic. The optimal solution to such scheduling problems requires to explicitly taking into account the coupling in the deadline-aware transmissions and stochastic characteristics of the traffic, which involves a dynamic program that is traditionally known to be intractable or computationally expensive to implement. First, real-time scheduling with adaptive network coding over memoryless channels is studied, and a polynomial-time complexity algorithm is developed to characterize the optimal real-time scheduling. Then, real-time scheduling over Markovian channels is investigated, where channel conditions are time-varying and online channel learning is necessary, and the optimal scheduling policies in different traffic regimes are studied. The second part focuses on the stochastic optimization and real-time scheduling involved in energy systems. First, risk-aware scheduling and dispatch for plug-in electric vehicles (EVs) are studied, aiming to jointly optimize the EV charging cost and the risk of the load mismatch between the forecasted and the actual EV loads, due to the random driving activities of EVs. Then, the integration of wind generation at high penetration levels into bulk power grids is considered. Joint optimization of economic dispatch and interruptible load management is investigated using short-term wind farm generation forecast. The third part studies stochastic optimization in distributed control systems under different network environments. First, distributed spectrum access in cognitive radio networks is investigated by using pricing approach, where primary users (PUs) sell the temporarily unused spectrum and secondary users compete via random access for such spectrum opportunities. The optimal pricing strategy for PUs and the corresponding distributed implementation of spectrum access control are developed to maximize the PU's revenue. Then, a systematic study of the nonconvex utility-based power control problem is presented under the physical interference model in ad-hoc networks. Distributed power control schemes are devised to maximize the system utility, by leveraging the extended duality theory and simulated annealing.
ContributorsYang, Lei (Author) / Zhang, Junshan (Thesis advisor) / Tepedelenlioğlu, Cihan (Committee member) / Xue, Guoliang (Committee member) / Ying, Lei (Committee member) / Arizona State University (Publisher)
Created2012
Description
One dimensional (1D) and quasi-one dimensional quantum wires have been a subject of both theoretical and experimental interest since 1990s and before. Phenomena such as the "0.7 structure" in the conductance leave many open questions. In this dissertation, I study the properties and the internal electron states of semiconductor quantum wires with the path integral Monte Carlo (PIMC) method. PIMC is a tool for simulating many-body quantum systems at finite temperature. Its ability to calculate thermodynamic properties and various correlation functions makes it an ideal tool in bridging experiments with theories. A general study of the features interpreted by the Luttinger liquid theory and observed in experiments is first presented, showing the need for new PIMC calculations in this field. I calculate the DC conductance at finite temperature for both noninteracting and interacting electrons. The quantized conductance is identified in PIMC simulations without making the same approximation in the Luttinger model. The low electron density regime is subject to strong interactions, since the kinetic energy decreases faster than the Coulomb interaction at low density. An electron state called the Wigner crystal has been proposed in this regime for quasi-1D wires. By using PIMC, I observe the zig-zag structure of the Wigner crystal. The quantum fluctuations suppress the long range correla- tions, making the order short-ranged. Spin correlations are calculated and used to evaluate the spin coupling strength in a zig-zag state. I also find that as the density increases, electrons undergo a structural phase transition to a dimer state, in which two electrons of opposite spins are coupled across the two rows of the zig-zag. A phase diagram is sketched for a range of densities and transverse confinements. The quantum point contact (QPC) is a typical realization of quantum wires. I study the QPC by explicitly simulating a system of electrons in and around a Timp potential (Timp, 1992). Localization of a single electron in the middle of the channel is observed at 5 K, as the split gate voltage increases. The DC conductance is calculated, which shows the effect of the Coulomb interaction. At 1 K and low electron density, a state similar to the Wigner crystal is found inside the channel.
ContributorsLiu, Jianheng, 1982- (Author) / Shumway, John B (Thesis advisor) / Schmidt, Kevin E (Committee member) / Chen, Tingyong (Committee member) / Yu, Hongbin (Committee member) / Ros, Robert (Committee member) / Arizona State University (Publisher)
Created2012