A Process Variation Tolerant Self-Compensation Sense Amplifier Design

As we move under the aegis of the Moore\u27s law, we have to deal with its darker side with problems like leakage and short channel effects. Once we go beyond 45nm regime process variations also have emerged as a significant design concern.Embedded memories uses sense amplifier for fast sensing and typically, sense amplifiers uses pair of matched transistors in a positive feedback environment. A small difference in voltage level of applied input signals to these matched transistors is amplified and the resulting logic signals are latched. Intra die variation causes mismatch between the sense transistors that should ideally be identical structures. Yield loss due to device and process variations has never been so critical to cause failure in circuits. Due to growth in size of embedded SRAMs as well as usage of sense amplifier based signaling techniques, process variations in sense amplifiers leads to significant loss of yield for that we need to come up with process variation tolerant circuit styles and new devices. In this work impact of transistor mismatch due to process variations on sense amplifier is evaluated and this problem is stated. For the solution of the problem a novel self compensation scheme on sense amplifiers is presented on different technology nodes up to 32nm on conventional bulk MOSFET technology. Our results show that the self compensation technique in the conventional bulk MOSFET latch type sense amplifier not just gives improvement in the yield but also leads to improvement in performance for latch type sense amplifiers. Lithography related CD variations, fluctuations in dopant density, oxide thickness and parametric variations of devices are identified as a major challenge to the classical bulk type MOSFET. With the emerging nanoscale devices, SIA roadmap identifies FinFETs as a candidate for post-planar end-of-roadmap CMOS device. With current technology scaling issues and with conventional bulk type MOSFET on 32nm node our technique can easily be applied to Double Gate devices. In this work, we also develop the model of Double Gate MOSFET through 3D Device Simulator Damocles and TCAD simulator. We propose a FinFET based process variation tolerant sense amplifier design that exploits the back gate of FinFET devices for dynamic compensation against process variations. Results from statistical simulation show that the proposed dynamic compensation is highly effective in restoring yield at a level comparable to that of sense amplifiers without process variations. We created the 32nm double gate models generated from Damocles 3-D device simulations [25] and Taurus Device Simulator available commercially from Synopsys [47] and use them in the nominal latch type sense amplifier design and on the Independent Gate Self Compensation Sense Amplifier Design (IGSSA) to compare the yield and performance benefits of sense amplifier design on FinFET technology over the conventional bulk type CMOS based sense amplifier on 32nm technology node effective in restoring yield at a level comparable to that of sense amplifiers without process variations. We created the 32nm double gate models generated from Damocles 3-D device simulations [25] and Taurus Device Simulator available commercially from Synopsys [47] and use them in the nominal latch type sense amplifier design and on the Independent Gate Self Compensation Sense Amplifier Design (IGSSA) to compare the yield and performance benefits of sense amplifier design on FinFET technology over the conventional bulk type CMOS based sense amplifier on 32nm technology node

Impact of Doping concentration and gate voltages on Simulation of n-FinFET

Here we are using a double gate FinFET and with the help of this device we are able to overcome the drawback of the MOSFET. In MOSFET we have a higher drain induced barrier lowering (DIBL). And because of short channel effects (SCE) the gate of the device loses its control over the channel. It also had higher threshold voltage. In this paper, firstly, we are implementing a 32nm gate length FinFET. And the software we are using is visual TCAD. Here in this paper, we had reported the impact of doping on 32nm gate length FinFET with fin width 22nm. The Id current, i.e. drain current increases when the donor ion concentration of source/drain regions increases from 1x1016 cm-3 to 7x1020 cm-3. Whereas we observed that there is a decrease in drain current when the acceptor ion concentration in the channel increases to 7x1020 cm-3. Secondly, we observed the impact of gate voltage on the device. Finally, Id-Vd comparison graph of varying gate length from 32nm gate length to 20nm gate length at the same parameters (i.e. 32nm, 28nm, 22nm, 20nm) are reported

Comparative proteomics analysis of differentially expressed proteins in chickpea extracellular matrix during dehydration stress

Water deficit or dehydration is the most crucial environmental factor that limits crop productivity and influences geographical distribution of many crop plants. It is suggested that dehydration-responsive changes in expression of proteins may lead to cellular adaptation against water deficit conditions. Most of the earlier understanding of dehydration-responsive cellular adaptation has evolved from transcriptome analyses. By contrast, comparative analysis of dehydration-responsive proteins, particularly proteins in the subcellular fraction, is limiting. In plants, cell wall or extracellular matrix (ECM) serves as the repository for most of the components of the cell signaling process and acts as a frontline defense. Thus, we have initiated a proteomics approach to identify dehydration-responsive ECM proteins in a food legume, chickpea. Several commercial chickpea varieties were screened for the status of dehydration tolerance using different physiological and biochemical indexes. Dehydration-responsive temporal changes of ECM proteins in JG-62, a relatively tolerant variety, revealed 186 proteins with variance at a 95% significance level statistically. The comparative proteomics analysis led to the identification of 134 differentially expressed proteins that include predicted and novel dehydration-responsive proteins. This study, for the first time, demonstrates that over a hundred ECM proteins, presumably involved in a variety of cellular functions, viz. cell wall modification, signal transduction, metabolism, and cell defense and rescue, impinge on the molecular mechanism of dehydration tolerance in plants

RecD: Deduplication for End-to-End Deep Learning Recommendation Model Training Infrastructure

We present RecD (Recommendation Deduplication), a suite of end-to-end infrastructure optimizations across the Deep Learning Recommendation Model (DLRM) training pipeline. RecD addresses immense storage, preprocessing, and training overheads caused by feature duplication inherent in industry-scale DLRM training datasets. Feature duplication arises because DLRM datasets are generated from interactions. While each user session can generate multiple training samples, many features' values do not change across these samples. We demonstrate how RecD exploits this property, end-to-end, across a deployed training pipeline. RecD optimizes data generation pipelines to decrease dataset storage and preprocessing resource demands and to maximize duplication within a training batch. RecD introduces a new tensor format, InverseKeyedJaggedTensors (IKJTs), to deduplicate feature values in each batch. We show how DLRM model architectures can leverage IKJTs to drastically increase training throughput. RecD improves the training and preprocessing throughput and storage efficiency by up to 2.48x, 1.79x, and 3.71x, respectively, in an industry-scale DLRM training system.Comment: Published in the Proceedings of the Sixth Conference on Machine Learning and Systems (MLSys 2023

A cross-sectional study of the levels of cytokines IL-6, TNF-α, and IFN-γ in blood and skin (lesional and uninvolved) of vitiligo patients and their possible role as biomarkers

Introduction: Vitiligo is a multifactorial disorder, most often explained by the autoimmune hypothesis. The objective of this study is to measure the levels of cytokines IL-6, TNF-α, and IFN-γ in the blood and skin (lesional and uninvolved) of vitiligo patients and to compare it with that of age-matched controls. Methods: IL-6, TNF-alpha, and IFN-gamma cytokines were measured with a BioRad 6110 ELISA reader. We compared the levels of these cytokines in generalized versus localized vitiligo and stable versus unstable vitiligo. We also correlated cytokine levels in blood/lesion/uninvolved skin with body surface area (BSA) involvement and Vitiligo Disease Activity (VIDA) scoring. Result: Forty-three participants, each with vitiligo and control, were analyzed. The values of TNF-α and IL 6 in sera were significantly higher in the vitiligo group compared with the controls (p < 0.001), whereas INF-γ was significantly lower in the vitiligo group than the control group. TNF-α, INF-γ levels when compared between blood, lesional skin, and normal skin in all vitiligo patients were found to be significant (p < 0.001). Conclusion: We conclude vitiligo is strongly associated with increased levels of TNF-α and IL 6

Evaluation of chemical composition of seed oil and oil cake of

The purpose of this investigation was to examine the antibacterial activity of oil derived from Ailanthus excelsa (Roxb) as well as the chemical composition of seed oil and the proximate analysis of oil cake. The oil content of the seeds is ∼ 17%. The seed oil was analyzed using GC-MS/FID, and the results showed that it contained a variety of fatty acids, such as linoleic acid, oleic acid, and palmitic acid. When employed with 100 µL, the oil did not demonstrate any antibacterial activity against the bacteria Staphylococcus aureus, Salmonella typhi, Escherichia coli, Pseudomonas aeruginosa, and Bacillus subtilis. The oil does not possess any antifungal action against Candida albicans and Aspergillus flavus. The oil cake is rich in protein and minerals. These findings imply that A. excelsa seed oil and oil cake have the potential to be used in the food and pharmaceutical industries after ascertaining its non-toxic nature and absence of antinutrients. The oil is not having antibacterial activity hence it can be used as a part of nutrient media for bacterial cultures

The nuclear proteome of chickpea (Cicer arietinum L.) reveals predicted and unexpected proteins

Nuclear proteins constitute a highly organized, complex network that plays diverse roles during cellular development and other physiological processes. The yeast nuclear proteome corresponds to about one-fourth of the total cellular proteins, suggesting the involvement of the nucleus in a number of diverse functions. In an attempt to understand the complexity of plant nuclear proteins, we have developed a proteome reference map of a legume, chickpea, using two-dimensional gel electrophoresis (2-DE). Approximately, 600 protein spots were detected, and LC-ESI-MS/MS analyses led to the identification of 150 proteins that have been implicated in a variety of cellular functions. The largest percentage of the identified proteins was involved in signaling and gene regulation (36%), while 17% were involved in DNA replication and transcription. The chickpea nuclear proteome indicates the presence of few new nuclear proteins of unknown functions vis-a-vis many known resident proteins. To the best of our knowledge, this is the first report of a nuclear proteome of an unsequenced genome

Extracellular matrix proteome of chickpea (Cicer arietinum L.) illustrates pathway abundance, novel protein functions and evolutionary perspect

The extracellular matrix (ECM) or cell wall is a dynamic system and serves as the first line mediator in cell signaling to perceive and transmit extra- and intercellular signals in many pathways. Although ECM is a conserved compartment ubiquitously present throughout evolution, a compositional variation does exist among different organisms. ECM proteins account for 10% of the ECM mass, however, comprise several hundreds of different molecules with diverse functions. To understand the function of ECM proteins, we have developed the cell wall proteome of a crop legume, chickpea (Cicer arietinum). This comprehensive overview of the proteome would provide a basis for future comparative proteomic efforts for this important crop. Proteomic analyses revealed new ECM proteins of unknown functions vis-a-vis the presence of many known cell wall proteins. In addition, we report here evidence for the presence of unexpected proteins with known biochemical activities, which have never been associated with ECM