VictorJuiz/thesis huggingface dataset:
Memory optimizations of embedded applications for energy efficiency [electronic resource]

The current embedded processors often do not satisfy increasingly demanding computation requirements of embedded applications within acceptable energy efficiency, whereas application-specific integrated circuits require excessive design costs. In the Stanford Elm project, it was identified that instruction and data delivery, not computation, dominate the energy consumption of embedded processors. Consequently, the energy efficiency of delivering instructions and data must be sufficiently improved to close the efficiency gap between application-specific integrated circuits and programmable embedded processors. This dissertation demonstrates that the compiler and run-time system can play a crucial role in improving the energy efficiency of delivering instructions and data. Regarding instruction delivery, I present a compiler algorithm that manages L0 instruction scratch-pad memories that reside between processor cores and L1 caches. Despite the lack of tags, the scratch-pad memories with our algorithm can achieve lower miss rates than caches with the same capacities, saving significant instruction delivery energy. Regarding data delivery, I present methods that minimize memory-space requirements for parallelizing stream applications, applications that are commonly found in the embedded domain. When stream applications are parallelized in pipelining, large enough buffers are required between pipeline stages to sustain the throughput (e.g., double buffering). For static stream applications where production and consumption rates of stages are close to compile-time constants, a compiler analysis is presented, which computes the minimum buffer capacity that maximizes the throughput. Based on this analysis, a new static streamscheduling algorithm is developed, which yields considerable speed-up and data delivery energy saving compared to a previous algorithm. For dynamic stream applications, I present a dynamically-sized array-based queue design that achieves speed-up and data delivery energy saving compared to a linked-list based queue design.

Keywords: Electrical Engineering
Advisor: Dally William
Lam Monica S. primary advisor. Thesis advisor
Kozyrakis Christoforos
Mercury reaction chemistry in combustion flue gases from experiments and theory [electronic resource]

Emissions from coal combustion processes constitute a significant amount of the elemental mercury released into the atmosphere today. Coal-fired power plants in the United States, with the capacity of just over 300GW, are the greatest anthropogenic source of mercury emissions. Mercury exists in coal combustion flue gas in a variety of forms depending on the coal type and combustion conditions; i.e., elemental, oxidized and particulate. Particulate mercury in the flue gas can be removed using air pollution control devices such as electrostatic precipitators and fabric filters. Oxidized mercury is easily captured by wet flue gas desulfurization scrubbers, while gaseous elemental mercury passes through the scrubbers readily. Activated carbon, when injected into the gas stream of coal-fired boilers, is effective in capturing both elemental and oxidized mercury through adsorption processes. However, the mechanism by which mercury adsorbs on activated carbon is not exactly known and its understanding is crucial to the design and fabrication of effective capture technologies for mercury. The objective of the current study is to apply theoretical-based cluster modeling to examine the possible binding mechanism of mercury on activated carbon. The effects of activated carbon's different surface functional groups and halogens on elemental mercury adsorption have been examined. Also, a thermodynamic approach is followed to examine the binding mechanism of mercury and its oxidized species such as HgCl and HgCl2 on a simulated carbon surface with and without Cl. Energies of different possible surface complexes and possible products are compared and dominant pathways are determined relatively. Since different methods are employed to capture varying forms of mercury, understanding mercury speciation during combustion and how the transformations occur between different forms is essential to developing an effective control mechanism for removing mercury from flue gas. In this study, homogeneous oxidation of mercury via chlorine is examined experimentally in a simulated flue gas environment. Mercury and chlorine are introduced into a laminar premixed methane-air flame. Cooled flue gas is sampled and sent to a custom-built electron ionization quadrupole mass spectrometer specially designed for mercury measurement on the order of parts per billion (ppb) in flue gas. The use of a mass spectrometer allows for distinguishing between the different forms of oxidized mercury (Hg+, Hg+2). By directly measuring mercury species accurately, one can determine the actual extent of mercury oxidation in the flue gas, which will aid in further developing mercury control technologies.

Keywords: Energy Resources Engineering
Advisor: Wilcox Jennifer
Brown G. E. (Gordon E.)
Kovscek Anthony R. (Anthony Robert) advisor. Thesis advisor
Mesh adaption strategies for vortex-dominated flows [electronic resource]

A new adaptive mesh refinement strategy that is based on a coupled feature-detection and error-estimation approach is developed. The overall goal is to apply the proper degree of refinement to key vortical features in aircraft and rotorcraft wakes. The refinement paradigm is based on a two-stage process wherein the vortical regions are initially identified for refinement using feature-detection, and then the appropriate resolution is determined by the local solution error. The feature-detection scheme uses a local normalization procedure that allows it to automatically identify regions for refinement with threshold values that are not dependent upon the convective scales of the problem. An error estimator, based on the Richardson Extrapolation method, then supplies the identified features with appropriate levels of refinement. The estimator is shown to be well-behaved for steady-state and time-accurate aerodynamic flows. The above strategy is implemented within the Helios code, which features a dual-mesh paradigm of unstructured grids in the near-body domain, and adaptive Cartesian grids in the off-body domain. A main objective of this work is to control the adaption process so that high fidelity wake resolution is obtained in the off-body domain. The approach is tested on several theoretical and practical vortex-dominated flow-fields in an attempt to resolve wingtip vortices and rotor wakes. Accuracy improvements to rotorcraft performance metrics and increased wake resolution are simultaneously documented.

Keywords: Aeronautics and Astronautics
Advisor: Jameson Antony
Wissink Andrew M. advisor. Thesis advisor
MacCormack R. W. (Robert William)
Methods and applications for position-specific evolutionary features in clinical genomics [electronic resource]

One of the grand challenges in genomic medicine is to translate fundamental scientific discoveries regarding the structure, variation, and function of the genomes of individuals and populations towards improved health outcomes. The main hypothesis of this thesis is that all forms of human genetic variation contributing to the etiology and pathophysiology of modern human diseases have distinct and quantifiable evolutionary histories, which can be computed for every position in the human genome independent of human population characteristics, and used as informative quantitative priors in the discovery and assessment of variants of clinical importance in modern human populations. To enable robust evaluation of the specific questions posed by this thesis, I first explore the necessary properties and theoretical basis for a null evolutionary hypothesis for Evolutionary Genomic Medicine, and conclude that the well-established Neutral Theory of Molecular Evolution provides a sound theoretical and methodological basis for evaluating alternative hypothesis in Evolutionary Genomic Medicine. Due to advances in multiplex genotyping technologies, genome-wide associations studies (GWAS), have emerged as the premier modality for discovery and assessment clinical genomic variation. Although these efforts have been successful in revealing thousands variants robustly associated with a broad spectrum of clinical phenotypes, the variants established by the GWAS approach have so far failed to explain large proportions of the known genetic variance associated with important clinical traits such as Type 2 Diabetes and Hypertension. Because disease-associated variation is linked with genomic loci of functional importance which have undergone evolutionary selection, and even the proxy loci (e.g. tagging SNPs) used to probe for disease associated loci themselves have quantifiable evolutionary histories, I evaluate a compendium of disease-associated variants to evaluate the effect of long-term evolutionary histories on the discovery of disease-associated variants. Through this work I demonstrate that disease-associated variants have distinct evolutionary properties, and that evolutionary features of positions can be incorporated as priors to improve discovery of disease-associated variants. A similar approach is applied to evaluate pharmacogenomics variants associated with warfarin, demonstrating that evolutionary features of genomic positions improve clinical assessment of pharmacogenomics variation. Through the findings and insights gained from efforts in pursuit of my thesis which are reported here, my collaborators and I clearly demonstrate that quantitative evolutionary features can be estimated for each position in the human genome across species, and then applied to modern human population data to improve discovery and assessment of genomic variation associated with clinical phenotypes.

Keywords: Biomedical Informatics.
Advisor: Butte Atul J. primary advisor. Thesis advisor
Kumar S. (Sudhir)
Petrov Dmitri Alex
Methods of study integration in multiplex molecular medicine [electronic resource]

The acquisition of biomedical research data is continually expanding, both in the number of variables measured in any single experiment and the number of experiments being done. To bring the fruits of all this labor into medical practice, we need to develop techniques for integrating high dimensional assays across experimental studies. In this thesis, I develop and demonstrate several approaches to multiplex meta-analysis, the synthesis multiple of high dimensional studies. I discuss the development of an overall expression map, examining the properties of gene expression dynamics across thousands of studies. I use this analysis of gene expression dynamics to develop methods of integrating highly parallelized gene expression studies to both identify new biomarkers of disease process, and to prioritize genes likely to contribute to disease risk. Finally, I demonstrate a method for clinical genomics, integrating disease linked genetic variants across an entire genome for translation into medical practice.

Keywords: Biomedical Informatics.
Advisor: Butte Atul J. primary advisor. Thesis advisor
Ashley Euan A. advisor. Thesis advisor
Brunet Anne
Methylation of the retinoblastoma tumor suppressor by SMYD2 and functional interactions between retinoblastoma and C-MYC in a mouse model of hepatocellular carcinoma [electronic resource]

The retinoblastoma tumor suppressor RB is a central cell cycle regulator. Here we demonstrate that RB can be methylated by SMYD2 at lysine 860, a highly conserved and novel site of modification. This methylation event occurs in vitro and in cells and is regulated during cell cycle progression, cellular differentiation, and in response to DNA damage. Furthermore, we show that RB mono-methylation at lysine 860 provides a direct binding site for the methyl-binding domain of the transcriptional repressor L3MBTL1. This modification may be crucial for regulating the function of RB as a tumor suppressor. Inactivation of RB and activation of the MYC family of oncogenes are frequent events in a large spectrum of human cancers. Here, we sought to also test whether loss of RB function would affect cancer development in a mouse model of c-MYC-induced hepatocellular carcinoma (HCC). We found that RB inactivation has minimal effects on the cell cycle, cell death, and differentiation features of liver tumors driven by increased levels of c-MYC. However, combined loss of RB and activation of c-MYC led to an increase in polyploidy in mature hepatocytes before the development of tumors and a trend for decreased survival after cancer initiation.

Keywords: Cancer Biology.
Advisor: Sage Julien primary advisor. Thesis advisor
Artandi Steven E. advisor. Thesis advisor
Lipsick Joseph Steven
Wysocka Joanna
Microbial pollution at the land-sea interface [electronic resource] : fate and transport of fecal indicators and human pathogens in beach sands and sediments

This research investigates the role of beach sands and sediments as reservoirs of fecal indicator bacteria and human pathogens using both laboratory microcosms and field experiments. Fecal indicator bacteria (FIB) are used to predict the presence of pathogens and to minimize the potential health risks associated with pathogens in recreational waters. This research reveals that FIB are nearly ubiquitous in California beach sands. In a field study...Ninety-one percent of the beaches sampled had detectable Enterococcus spp. (ENT) while 62% had detectable E. coli (EC) in their sands. A field study was used to investigate the role of waves and tides as a physical connection through which fecal indicators can be transported from beach sands to the coastal ocean. The process of "over-beach" transport is documented at Lovers Point Beach, California, suggesting that resuspension of ENT from beach sands can instigate beach advisories. It is also shown that naturally occurring ENT can replicate (0.20 - 0.63 per day) in Lovers Point beach sands under environmentally relevant conditions. A follow up survey of beaches along the CA coast documents the presence of the human-specific fecal marker in Bacteriodales spp. and human pathogens in beach sands. At least one human pathogen was detected at 27% of the beaches surveyed along the California coast, suggesting that contact with beach sands may lead to increased human health risks. Follow-up persistence studies were conducted for pathogens and indicators and revealed that that many of the pathogens and indicators we tested for in the field study can persist upward of 10 - 15 d in sands. Finally, we extended our knowledge of FIB in beach sands to sediments and investigated the potential for river sediments and soils to act as sources of microbial contaminants to the Hanalei River (Kauai, HI). A mass balance model that accounted for losses due to deposition of FIB-laden sediments, sources due to resuspension of FIB-laden sediment, and losses due to bacterial inactivation was used to explore the cause of the observed sources and sinks along the river. The model indicated that the resuspension or deposition of FIB-laden river sediments accounted for less than 1% of the observed EC and ENT loadings along the river. The research presented in this dissertation ties together multiple microbiological methods and engineering principles to shed light on the fate and transport of FIB and human pathogens in natural environmental systems.

Advisor: Boehm Alexandria primary advisor. Thesis advisor
Criddle Craig advisor. Thesis advisor
Francis Christopher advisor. Thesis advisor
Minimum-residual methods for sparse least-squares using Golub-Kahan bidiagonalization [electronic resource]

For 30 years, LSQR and its theoretical equivalent CGLS have been the standard iterative solvers for large rectangular systems of linear equations and least-squares problems. They are analytically equivalent to symmetric CG on the corresponding normal equation, and they reduce the residual norm monotonically. The techniques pioneered in the development of LSQR allow better algorithms to be developed for a wider range of problems. We derive LSMR, an algorithm that is similar to LSQR but exhibits better convergence properties. LSMR is equivalent to applying MINRES to the normal equation, so that the error, the residual, and the residual of the normal equation all decrease monotonically. In practice we observe that the Stewart backward error is usually monotonic and very close to optimal. LSMR has essentially the same computational cost per iteration as LSQR, but the Stewart backward error is always smaller. Thus if iterations need to be terminated early, it is safer to use LSMR. LSQR and LSMR are based on Golub-Kahan bidiagonalization. Following the analysis of LSMR, we leverage the techniques used there to construct algorithm AMRES for negatively-damped least-squares systems, again using Golub-Kahan bidiagonalization. Such problems arise in total least-squares, Rayleigh quotient iteration (RQI), and Curtis-Reid scaling for rectangular sparse matrices. Our solver AMRES provides a stable method for these problems. AMRES allows caching and reuse of the Golub-Kahan vectors across RQIs, and can be used to compute any of the singular vectors of A, given a reasonable estimate of the singular vector or an accurate estimate of the singular value.

Advisor: Saunders Michael
Gerritsen Margot (Margot G.) advisor. Thesis advisor
Murray Walter advisor. Thesis advisor
Mixed equation-simulation circuit optimization [electronic resource]

One of the main challenges in designing analog circuits today is to cope with the complex behaviors of modern devices. For example, the drain current of a deep- submicron MOSFET device can no longer be predicted by the long-channel models, due to various effects including carrier velocity saturation, vertical-field induced mobility degradation, drain-induced barrier lowering (DIBL), and narrow channel effects, to name only a few. In addition, the characteristics of each individual device can be further affected by random variability and proximity effects. As a result, it is extremely difficult to design an optimal circuit at the presence of these complex phenomena without relying on computational aids, e.g. circuit optimizers. However, many circuit optimizers based on global optimization techniques such as simulated annealing or evolutionary algorithms may also have difficulties unless they are provided with good initial guesses. This research focuses on building a circuit optimizer that leverages designer's intent to help the simulation-based optimizers find solutions quickly. The technique is inspired by continuation techniques in numerical analysis where a difficult problem is solved by constructing an easier problem first and gradually refining its solution to that of the hard problem. In a circuit optimization context, the designer's simplified equations for the circuit serve as the easier problem. These simplified design equations are easy to write as they need not be completely accurate and have solutions that are easy to reason about. While these design equations may not generate a good initial design for optimizing real circuits directly, they can help guide the optimizer towards an optimal solution by constructing and solving a series of intermediate problems that gradually change from the initial problem based on design equations to the real circuit problem with accurate device models. Assuming that the solutions to these intermediate problems change only gradually along this path, each problem can be solved very efficiently via local optimization methods, using the solution to the previous problem as a starting point. Although more problems have to be solved, since each is solved very efficiently, the overall computational costs can be lower than that of solving the final problem directly. We apply our circuit optimization approach to several design examples and investigate the importance of the initial designer's equations by comparing our optimizer's performances against those of a local optimizer and a generic continuation- based optimizer. We extend this basic idea to leverage hierarchy to help optimize large circuits, and demonstrate this technique with a PLL design example. Besides the runtime benefit, performing optimization hierarchically is also intuitive and more in line with how a circuit designer would approach designing a large circuit problem like the PLL.

Keywords: Electrical Engineering
Advisor: Horowitz Mark (Mark Alan) primary advisor. Thesis advisor
Boyd Stephen P. advisor. Thesis advisor
Murmann Boris advisor. Thesis advisor
A mixture model approach to empirical Bayes testing and estimation [electronic resource]

Many modern statistical problems require making similar decisions or estimates for many different entities. For example, we may ask whether each of 10,000 genes is associated with some disease, or try to measure the degree to which each is associated with the disease. As in this example, the entities can often be divided into a vast majority of "null" objects and a small minority of interesting ones. Empirical Bayes is a useful technique for such situations, but finding the right empirical Bayes method for each problem can be difficult. Mixture models, however, provide an easy and effective way to apply empirical Bayes. This thesis motivates mixture models by analyzing a simple high-dimensional problem, and shows their practical use by applying them to detecting single nucleotide polymorphisms.

Keywords: Statistics
Advisor: Efron Bradley primary advisor. Thesis advisor
Tibshirani Robert advisor. Thesis advisor
Zhang Nancy R. (Nancy Ruonan) advisor. Thesis advisor
Modeling aircraft contrails and emission plumes for climate impacts [electronic resource]

Aircraft emissions lead to contrails and change cloud coverage in the upper troposphere/lower stratosphere, but their quantitative impact on climate is highly uncertain. As environmental policy turns toward regulating anthropogenic climate change components, it will be necessary to improve quantification of the climate impacts of aviation. Toward this end, we present two models of aircraft emissions. The first model is a large eddy simulation (LES) with three-dimensional, eddy-resolving flow physics and ice deposition/sublimation microphysics. Modeled ice properties, cloud optical depths, and contrail width growth rates are consistent with observational field studies. A series of sensitivity cases shows the effect of various parameters over twenty minutes of simulation time. The analysis focuses on properties such as contrail optical depth and cross-sectional width that are relevant to climate impacts. Vertical wind shear is found to have the strongest effect on these properties through the kinematic spreading of the contrail. In cases with no shear, optical depth is most sensitive to aircraft type and ambient humidity. One model parameter, the effective emission index of ice crystals, is also found to affect optical depth. A subset of the LES cases is run for two hours of simulation time to approach the scale of dynamical time steps modeled by global climate simulations. These cases use more realistic ice microphysics, including sedimentation, and forced ambient turbulence, both of which are processes that control contrail development at late times. The second model is a simple, low cost parameterization of aircraft plume dynamics, intended to be used as a subgrid plume model (SPM) within large scale atmospheric simulations. The SPM provides basic plume cross-section time advancement that has been used as a dilution model within a coupled global atmosphere-ocean climate simulation to study the effects of aviation on air quality and climate. Comparison to the twenty-minute and two-hour LES results demonstrates that the SPM captures important plume development characteristics under the effect of vertical shear and atmospheric turbulence.

Keywords: Aeronautics and Astronautics
Advisor: Lele Sanjiva K. (Sanjiva Keshava)
Alonso Juan José
Jacobson Mark Z. (Mark Zachary) advisor. Thesis advisor