3,373 research outputs found

    Undergraduate Catalog of Studies, 2023-2024

    Get PDF

    Graduate Catalog of Studies, 2023-2024

    Get PDF

    A Review on Non-Volatile and Volatile Emerging Memory Technologies

    Get PDF
    As technology scaling is approaching a stand-still with architectural advancements on modern day processors struggling to improve performance, coupled with the rise in machine learning topologies demanding better performing processors, there is a pressing need to address the reasons behind today’s performance bottleneck. These reasons include long access latency of memory technologies, scalability of memory designs, energy inefficiency incurred by increased performance, and additional area overhead. To explore these issues, a holistic understanding of existing memory technologies is essential. In this chapter, a review of different memory designs starting from volatile memory technologies such as Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), NAND/NOR flash to emerging non-volatile memory technologies such as Resistive Random Access Memory (RRAM), Magneto-resistive random access memory (MRAM), Ferroelectric Field effect transistor (FeFET) is presented, with specific consideration of tradeoffs involving area, performance, energy

    Graduate Catalog of Studies, 2023-2024

    Get PDF

    Reliable Sensor Intelligence in Resource Constrained and Unreliable Environment

    Get PDF
    The objective of this research is to design a sensor intelligence that is reliable in a resource constrained, unreliable environment. There are various sources of variations and uncertainty involved in intelligent sensor system, so it is critical to build reliable sensor intelligence. Many prior works seek to design reliable sensor intelligence by developing robust and reliable task. This thesis suggests that along with improving task itself, task reliability quantification based early warning can further improve sensor intelligence. DNN based early warning generator quantifies task reliability based on spatiotemporal characteristics of input, and the early warning controls sensor parameters and avoids system failure. This thesis presents an early warning generator that predicts task failure due to sensor hardware induced input corruption and controls the sensor operation. Moreover, lightweight uncertainty estimator is presented to take account of DNN model uncertainty in task reliability quantification without prohibitive computation from stochastic DNN. Cross-layer uncertainty estimation is also discussed to consider the effect of PIM variations.Ph.D

    Undergraduate Catalog of Studies, 2022-2023

    Get PDF

    A survey on run-time power monitors at the edge

    Get PDF
    Effectively managing energy and power consumption is crucial to the success of the design of any computing system, helping mitigate the efficiency obstacles given by the downsizing of the systems while also being a valuable step towards achieving green and sustainable computing. The quality of energy and power management is strongly affected by the prompt availability of reliable and accurate information regarding the power consumption for the different parts composing the target monitored system. At the same time, effective energy and power management are even more critical within the field of devices at the edge, which exponentially proliferated within the past decade with the digital revolution brought by the Internet of things. This manuscript aims to provide a comprehensive conceptual framework to classify the different approaches to implementing run-time power monitors for edge devices that appeared in literature, leading the reader toward the solutions that best fit their application needs and the requirements and constraints of their target computing platforms. Run-time power monitors at the edge are analyzed according to both the power modeling and monitoring implementation aspects, identifying specific quality metrics for both in order to create a consistent and detailed taxonomy that encompasses the vast existing literature and provides a sound reference to the interested reader

    Analog Photonics Computing for Information Processing, Inference and Optimisation

    Full text link
    This review presents an overview of the current state-of-the-art in photonics computing, which leverages photons, photons coupled with matter, and optics-related technologies for effective and efficient computational purposes. It covers the history and development of photonics computing and modern analogue computing platforms and architectures, focusing on optimization tasks and neural network implementations. The authors examine special-purpose optimizers, mathematical descriptions of photonics optimizers, and their various interconnections. Disparate applications are discussed, including direct encoding, logistics, finance, phase retrieval, machine learning, neural networks, probabilistic graphical models, and image processing, among many others. The main directions of technological advancement and associated challenges in photonics computing are explored, along with an assessment of its efficiency. Finally, the paper discusses prospects and the field of optical quantum computing, providing insights into the potential applications of this technology.Comment: Invited submission by Journal of Advanced Quantum Technologies; accepted version 5/06/202

    Evaluación eléctrica y física de métodos de generación de redes lógicas para compuertas estáticas CMOS complementarias (SCCG)

    Get PDF
    Recientemente la evolución de la industria de la microelectrónica ha permitido el desarrollo de herramientas de diseño electrónico automático (EDA), las cuales tienen por objetivo optimizar el proceso de diseño de circuitos integrados (IC). Tradicionalmente en la creación de un IC se suele utilizar el enfoque de diseño de celdas estándar; no obstante, este tipo de flujo de diseño se encuentra limitado por la cantidad de compuertas lógicas que estén definidas en la librería utilizada. Es por ello que diversos estudios han realizado investigaciones respecto a la optimización de circuitos por Compuertas CMOS Estáticas Complementarias (SCCG). En la literatura podemos encontrar diversas estrategias de diseño de compuertas SCCG; sin embargo, la métrica que se usa para definir el mejor arreglo es la cantidad de transistores, la cual carece de otros análisis concernientes a los parámetros eléctricos y físicos. Es por ello que en este trabajo de tesis se plantea evaluarlas redes de transistores SCCG generadas por el framework SwitchCraft mediante un análisis eléctrico realizado con el software CADENCE y un análisis físico de los layouts generados por medio de la herramienta ASTRAN

    Spatially Resolved Chiroptical Spectroscopies Emphasizing Recent Applications to Thin Films of Chiral Organic Dyes

    Get PDF
    Instrumental techniques able to identify and structurally characterize the aggregation states in thin films of chiral organic π-conjugated materials, from the first-order supramolecular arrangement up to the microscopic and meso-scopic scale, are very helpful for clarifying structure-property relationships. Chiroptical imaging is currently gaining a central role, for its ability of mapping local supramolecular structures in thin films. The present review gives an overview of electronic circular dichroism imaging (ECDi), circularly polarized luminescence imaging (CPLi), and vibrational circular dichroism imaging (VCDi), with a focus on their applications on thin films of chiral organic dyes as case studies
    • …
    corecore