2 resultados para Coxian phase-type distributions fitting parameter estimation optimization health care data

em DRUM (Digital Repository at the University of Maryland)


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Due to increasing integration density and operating frequency of today's high performance processors, the temperature of a typical chip can easily exceed 100 degrees Celsius. However, the runtime thermal state of a chip is very hard to predict and manage due to the random nature in computing workloads, as well as the process, voltage and ambient temperature variability (together called PVT variability). The uneven nature (both in time and space) of the heat dissipation of the chip could lead to severe reliability issues and error-prone chip behavior (e.g. timing errors). Many dynamic power/thermal management techniques have been proposed to address this issue such as dynamic voltage and frequency scaling (DVFS), clock gating and etc. However, most of such techniques require accurate knowledge of the runtime thermal state of the chip to make efficient and effective control decisions. In this work we address the problem of tracking and managing the temperature of microprocessors which include the following sub-problems: (1) how to design an efficient sensor-based thermal tracking system on a given design that could provide accurate real-time temperature feedback; (2) what statistical techniques could be used to estimate the full-chip thermal profile based on very limited (and possibly noise-corrupted) sensor observations; (3) how do we adapt to changes in the underlying system's behavior, since such changes could impact the accuracy of our thermal estimation. The thermal tracking methodology proposed in this work is enabled by on-chip sensors which are already implemented in many modern processors. We first investigate the underlying relationship between heat distribution and power consumption, then we introduce an accurate thermal model for the chip system. Based on this model, we characterize the temperature correlation that exists among different chip modules and explore statistical approaches (such as those based on Kalman filter) that could utilize such correlation to estimate the accurate chip-level thermal profiles in real time. Such estimation is performed based on limited sensor information because sensors are usually resource constrained and noise-corrupted. We also took a further step to extend the standard Kalman filter approach to account for (1) nonlinear effects such as leakage-temperature interdependency and (2) varying statistical characteristics in the underlying system model. The proposed thermal tracking infrastructure and estimation algorithms could consistently generate accurate thermal estimates even when the system is switching among workloads that have very distinct characteristics. Through experiments, our approaches have demonstrated promising results with much higher accuracy compared to existing approaches. Such results can be used to ensure thermal reliability and improve the effectiveness of dynamic thermal management techniques.

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A solid state lithium metal battery based on a lithium garnet material was developed, constructed and tested. Specifically, a porous-dense-porous trilayer structure was fabricated by tape casting, a roll-to-roll technique conducive to high volume manufacturing. The high density and thin center layer (< 20 μm) effectively blocks dendrites even over hundreds of cycles. The microstructured porous layers, serving as electrode supports, are demonstrated to increase the interfacial surface area available to the electrodes and increase cathode loading. Reproducibility of flat, well sintered ceramics was achieved with consistent powderbed lattice parameter and ball milling of powderbed. Together, the resistance of the LLCZN trilayer was measured at an average of 7.6 ohm-cm2 in a symmetric lithium cell, significantly lower than any other reported literature results. Building on these results, a full cell with a lithium metal anode, LLCZN trilayer electrolyte, and LiCoO2 cathode was cycled 100 cycles without decay and an average ASR of 117 ohm-cm2. After cycling, the cell was held at open circuit for 24 hours without any voltage fade, demonstrating the absence of a dendrite or short-circuit of any type. Cost calculations guided the optimization of a trilayer structure predicted that resulting cells will be highly competitive in the marketplace as intrinsically safe lithium batteries with energy densities greater than 300 Wh/kg and 1000 Wh/L for under $100/kWh. Also in the pursuit of solid state batteries, an improved Na+ superionic conductor (NASICON) composition, Na3Zr2Si2PO12, was developed with a conductivity of 1.9x10-3 S/cm. New super-lithiated lithium garnet compositions, Li7.06La3Zr1.94Y0.06O12 and Li7.16La3Zr1.84Y0.16O12, were developed and studied revealing insights about the mechanisms of conductivity in lithium garnets.