Statistical analysis and design of subthreshold operation memories

This thesis presents novel methods based on a combination of well-known statistical techniques for faster estimation of memory yield and their application in the design of energy-efficient subthreshold memories. The emergence of size-constrained Internet-of-Things (IoT) devices and proliferation of the wearable market has brought forward the challenge of achieving the maximum energy efficiency per operation in these battery operated devices. Achieving this sought-after minimum energy operation is possible under sub-threshold operation of the circuit. However, reliable memory operation is currently unattainable at these ultra-low operating voltages because of the memory circuit's vanishing noise margins which shrink further in the presence of random process variations. The statistical methods, presented in this thesis, make the yield optimization of the sub-threshold memories computationally feasible by reducing the SPICE simulation overhead. We present novel modifications to statistical sampling techniques that reduce the SPICE simulation overhead in estimating memory failure probability. These sampling scheme provides 40x reduction in finding most probable failure point and 10x reduction in estimating failure probability using the SPICE simulations compared to the existing proposals. We then provide a novel method to create surrogate models of the memory margins with better extrapolation capability than the traditional regression methods. These models, based on Gaussian process regression, encode the sensitivity of the memory margins with respect to each individual threshold variation source in a one-dimensional kernel. We find that our proposed additive kernel based models have 32% smaller out-of-sample error (that is, better extrapolation capability outside training set) than using the six-dimensional universal kernel like Radial Basis Function (RBF). The thesis also explores the topological modifications to the SRAM bitcell to achieve faster read operation at the sub-threshold operating voltages. We present a ten-transistor SRAM bitcell that achieves 2x faster read operation than the existing ten-transistor sub-threshold SRAM bitcells, while ensuring similar noise margins. The SRAM bitcell provides 70% reduction in dynamic energy at the cost of 42% increase in the leakage energy per read operation. Finally, we investigate the energy efficiency of the eDRAM gain-cells as an alternative to the SRAM bitcells in the size-constrained IoT devices. We find that reducing their write path leakage current is the only way to reduce the read energy at Minimum Energy operation Point (MEP). Further, we study the effect of transistor up-sizing under the presence of threshold voltage variations on the mean MEP read energy by performing statistical analysis based on the ANOVA test of the full-factorial experimental design.Esta tesis presenta nuevos métodos basados en una combinación de técnicas estadísticas conocidas para la estimación rápida del rendimiento de la memoria y su aplicación en el diseño de memorias de energia eficiente de sub-umbral. La aparición de los dispositivos para el Internet de las cosas (IOT) y la proliferación del mercado portátil ha presentado el reto de lograr la máxima eficiencia energética por operación de estos dispositivos operados con baterias. La eficiencia de energía es posible si se considera la operacion por debajo del umbral de los circuitos. Sin embargo, la operación confiable de memoria es actualmente inalcanzable en estos bajos niveles de voltaje debido a márgenes de ruido de fuga del circuito de memoria, los cuales se pueden reducir aún más en presencia de variaciones randomicas de procesos. Los métodos estadísticos, que se presentan en esta tesis, hacen que la optimización del rendimiento de las memorias por debajo del umbral computacionalmente factible mediante la simulación SPICE. Presentamos nuevas modificaciones a las técnicas de muestreo estadístico que reducen la sobrecarga de simulación SPICE en la estimación de la probabilidad de fallo de memoria. Estos esquemas de muestreo proporciona una reducción de 40 veces en la búsqueda de puntos de fallo más probable, y 10 veces la reducción en la estimación de la probabilidad de fallo mediante las simulaciones SPICE en comparación con otras propuestas existentes. A continuación, se proporciona un método novedoso para crear modelos sustitutos de los márgenes de memoria con una mejor capacidad de extrapolación que los métodos tradicionales de regresión. Estos modelos, basados en el proceso de regresión Gaussiano, codifican la sensibilidad de los márgenes de memoria con respecto a cada fuente de variación de umbral individual en un núcleo de una sola dimensión. Los modelos propuestos, basados en kernel aditivos, tienen un error 32% menor que el error out-of-sample (es decir, mejor capacidad de extrapolación fuera del conjunto de entrenamiento) en comparacion con el núcleo universal de seis dimensiones como la función de base radial (RBF). La tesis también explora las modificaciones topológicas a la celda binaria SRAM para alcanzar velocidades de lectura mas rapidas dentro en el contexto de operaciones en el umbral de tensiones de funcionamiento. Presentamos una celda binaria SRAM de diez transistores que consigue aumentar en 2 veces la operación de lectura en comparacion con las celdas sub-umbral de SRAM de diez transistores existentes, garantizando al mismo tiempo los márgenes de ruido similares. La celda binaria SRAM proporciona una reducción del 70% en energía dinámica a costa del aumento del 42% en la energía de fuga por las operaciones de lectura. Por último, se investiga la eficiencia energética de las células de ganancia eDRAM como una alternativa a los bitcells SRAM en los dispositivos de tamaño limitado IOT. Encontramos que la reducción de la corriente de fuga en el path de escritura es la única manera de reducir la energía de lectura en el Punto Mínimo de Energía (MEP). Además, se estudia el efecto del transistor de dimensionamiento en virtud de la presencia de variaciones de voltaje de umbral en la media de energia de lecture MEP mediante el análisis estadístico basado en la prueba de ANOVA del diseño experimental factorial completo.Postprint (published version

Survey and Analysis of Production Distributed Computing Infrastructures

This report has two objectives. First, we describe a set of the production distributed infrastructures currently available, so that the reader has a basic understanding of them. This includes explaining why each infrastructure was created and made available and how it has succeeded and failed. The set is not complete, but we believe it is representative. Second, we describe the infrastructures in terms of their use, which is a combination of how they were designed to be used and how users have found ways to use them. Applications are often designed and created with specific infrastructures in mind, with both an appreciation of the existing capabilities provided by those infrastructures and an anticipation of their future capabilities. Here, the infrastructures we discuss were often designed and created with specific applications in mind, or at least specific types of applications. The reader should understand how the interplay between the infrastructure providers and the users leads to such usages, which we call usage modalities. These usage modalities are really abstractions that exist between the infrastructures and the applications; they influence the infrastructures by representing the applications, and they influence the ap- plications by representing the infrastructures

Formin-dependent TGF-β signaling for epithelial to mesenchymal transition.

The role of distinct actin filament architectures in epithelial plasticity remains incompletely understood. We therefore determined roles for formins and the Arp2/3 complex, which are actin nucleators generating unbranched and branched actin filaments, respectively, in the process of epithelial to mesenchymal transition (EMT). In clonal lung, mammary, and renal epithelial cells, the formin activity inhibitor SMIFH2 but not the Arp2/3 complex activity inhibitor CK666 blocked EMT induced by TGF-β. SMIFH2 prevented the proximal signal of increased Smad2 phosphorylation and hence also blocked downstream EMT markers, including actin filament remodeling, decreased expression of the adherens junction protein E-cadherin, and increased expression of the matrix protein fibronectin and the transcription factor Snail. The short hairpin RNA silencing of formins DIAPH1 and DIAPH3 but not other formins phenocopied SMIFH2 effects and inhibited Smad2 phosphorylation and changes in Snail and cadherin expression. Formin activity was not necessary for the cell surface expression or dimerization of TGF-β receptors, or for nuclear translocation of TAZ, a transcription cofactor in Hippo signaling also regulated by TGF-β. Our findings reveal a previously unrecognized role for formin-dependent actin architectures in proximal TGF-β signaling that is necessary for Smad2 phosphorylation but not for cross-talk to TAZ

Statistical analysis and comparison of 2T and 3T1D e-DRAM minimum energy operation

Bio-medical wearable devices restricted to their small-capacity embedded-battery require energy-efficiency of the highest order. However, minimum-energy point (MEP) at sub-threshold voltages is unattainable with SRAM memory, which fails to hold below 0.3V because of its vanishing noise margins. This paper examines the minimum-energy operation point of 2T and 3T1D e-DRAM gain cells at the 32-nm technology node with different design points: up-sizing transistors, using high- V th transistors, read/write wordline assists; as well as operating conditions (i.e., temperature). First, the e-DRAM cells are evaluated without considering any process variations. Then, a full-factorial statistical analysis of e-DRAM cells is performed in the presence of threshold voltage variations and the effect of upsizing on mean MEP is reported. Finally, it is shown that the product of the read and write lengths provides a knob to tradeoff energy-efficiency for reliable MEP energy operation.Peer ReviewedPostprint (author's final draft

Analyzing stability concerns in the presence of variations in Subthreshold SRAM

In this work, we analyse the stability of the SRAM bitcells when operating in subthreshold supply voltages.We propose a new bit cell with higher stability than 6T Bitcell,that is able to discharge the bit lines in 41% less time than the 6T as it's discharge path is only of single transistor

Brain MRI: a useful tool for screening of hypertensive patients for silent cerebro-vascular damage

Background: Worldwide hypertension is an important public-health challenge because of its high frequency and concomitant risks of cardiovascular, renal, cerebrovascular disease and death. Current guidelines for the management of hypertension mainly recommend the search for preclinical damage to the heart and kidneys. However, extending this search to other organs, for instance the brain, might improve risk stratification, might optimize antihypertensive therapy and might, in the end help to further reduce the burden of disease attributable to hypertension.Methods: 84 consecutive hypertensive patients with no target organ damage were enrolled in study to find out silent brain damage over a period of one year.Results: Mean body mass index (BMI) of the study population was 28.4±2.5 kg/m2 (range 23.2 to 35.3kg/m2). 33 (39.3%) subjects had white matter lesions. 13 (15.47%) study subjects were found to have vascular changes which included micro angiopathic changes, infarcts and reduced/slow blood flow. 33 (39.3%) subjects were found to have normal brain MRI in the study. Early brain MRI was found to be beneficial in patients who had uncontrolled blood pressure either due to lack of treatment or irregular use of anti-hypertensive treatment. This was true for every age group in general and particularly in subjects above the age of 50 years.Conclusions: The screening of hypertensive patients for silent cerebrovascular damage with brain MRI may be useful in stratifying the risk of future cerebrovascular disease

Cloud computing for the architecture, engineering & construction sector: requirements, prototype & experience

The Architecture, Engineering \& Construction (AEC) sector is a highly fragmented, data intensive, project based industry, involving a number of very different professions and organisations. Projects carried out within this sector involve collaboration between various people, using a variety of different systems. This, along with the industry's strong data sharing and processing requirements, means that the management of building data is complex and challenging. This paper presents a solution to data sharing requirements of the AEC sector by utilising Cloud Computing. Our solution presents two key contributions, first a governance model for building data, based on extensive research and industry consultation. Second, a prototype implementation of this governance model, utilising the CometCloud autonomic cloud computing engine based on the Master/Work paradigm. we have integrated our prototype with the 3D modelling software Google Sketchup. The approach and prototype presented has applicability in a number of other eScience related applications involving multi-disciplinary, collaborative working using Cloud computing infrastructure

Feedback-control & queueing theory-based resource management for streaming applications

Recent advances in sensor technologies and instrumentation have led to an extraordinary growth of data sources and streaming applications. A wide variety of devices, from smart phones to dedicated sensors, have the capability of collecting and streaming large amounts of data at unprecedented rates. A number of distinct streaming data models have been proposed. Typical applications for this include smart cites & built environments for instance, where sensor-based infrastructures continue to increase in scale and variety. Understanding how such streaming content can be processed within some time threshold remains a non-trivial and important research topic. We investigate how a cloud-based computational infrastructure can autonomically respond to such streaming content, offering Quality of Service guarantees. We propose an autonomic controller (based on feedback control and queueing theory) to elastically provision virtual machines to meet performance targets associated with a particular data stream. Evaluation is carried out using a federated Cloud-based infrastructure (implemented using CometCloud) – where the allocation of new resources can be based on: (i) differences between sites, i.e. types of resources supported (e.g. GPU vs. CPU only), (ii) cost of execution; (iii) failure rate and likely resilience, etc. In particular, we demonstrate how Little’s Law –a widely used result in queuing theory– can be adapted to support dynamic control in the context of such resource provisioning

Prescription and cost-analysis of antiemetic medication use in pediatric wards: a prospective observational study

Background: Use of anti-emetic drugs in pediatric population is often warranted, but choice of drug remains questionable within pediatricians. Objective of current study is: to study prescribing pattern and to calculate cost of antiemetic drug therapy in pediatric wards.Methods: A prospective, observational study was conducted in pediatric wards of a tertiary care hospital of over 14 month’s duration. Institutional ethics committee approval was obtained and written informed consent of parents/guardians was taken. Data of any pediatric patient receiving anti-emetic agent were included in the study.Results: A total of 218 prescriptions were collected. Mean age of patients was 4.39±3.16 (range 4 months to 12 years). Gastroenteritis was the most frequently diagnosed disease in 137(63%) patients. Domperidone was prescribed in 52.4% and ondansetron in 47.6% children. Oral liquid dosage formulation was prescribed in 109 (48.4%) followed by solid dosage form 47 (20.9%). Mean cost of domperidone therapy was 25.34±6.55 INR and for ondansetron it was 36.62±17.94 INR.Conclusions: Gastroenteritis was most frequent indication for use of anti-emetics. Domperidone pharmacotherapy was cheaper and most frequently prescribed than ondansetron