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SHF: Small: Analytical Modeling and Design Methodology for Large-scale Computational Systems Employing Flexible Electronics for Extensive Physical Interfacing

SHF: Small: Analytical Modeling and Design Methodology for Large-scale Computational Systems Employing Flexible Electronics for Extensive Physical Interfacing
SHF:小型:采用柔性电子设备进行广泛物理接口的大型计算系统的分析建模和设计方法
批准号:
1218206
负责人:
Naveen Verma
金额:
$45.0万
依托单位:
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2012
资助国家:
美国
项目状态:
已结题
起止时间:
2012-07-01 至 2016-06-30

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中文摘要
翻译
电子学使小型设备具有大量的计算能力;这意味着来自物理系统的信号可以呈现给这些设备,以获得高价值的输出。挑战在于,尽管可以在嵌入式设备中实现巨大的计算能力,但获取分布在物理系统上的大量信号,然后在相关距离上通信信息的能力仍然小得不成比例。然而,正在出现的技术使创造通信渠道和大规模的电子物理接口成为可能。大面积电子学是一种能够在柔性、低成本的薄片上制造互连以及各种传感器的扩展阵列的技术。当与高性能硅集成电路(ic)相结合时,该技术可以使系统的计算可以应用于比今天更大规模的物理信号。系统的最终设计空间涵盖两个技术领域。为了创建高效且可伸缩的系统,必须严格分析平台组件和硬件架构,并且必须开发用于理解和优化设计权衡的方法。本研究的目的是对传感和通信的平台组件和架构进行分析建模,然后将它们综合到系统设计方法中。该平台架构包括用于数字和模拟信号的接口、用于传感的控制电路以及可扩展到许多节点的通信网络。这些方法涵盖了设备、体系结构和系统协议级别的分析。需要将电子设备与物理系统大规模接口的一些引人注目的应用包括通过厘米分辨率应变传感检测桥梁和建筑物的早期结构退化,通过高分辨率显示器和输入传感器进行视觉丰富计算的交互式表面等。大面积电子器件和高性能集成电路协同使用,具有实现此类应用的潜力。通过开发系统设计的分析模型和方法,本研究旨在将技术开发和计算机系统领域的努力结合起来。这项研究的结果将有助于协调和集中这些领域的研究和工程努力,以创建最佳系统。这项研究还将吸引新一代的工程师,特别是来自代表性不足的群体,通过独特的机会来开发与物理系统广泛交互的计算系统设计的系统原则。通过本科项目和专题课程,以及普林斯顿大学的外展项目,如面向中学生的科学与工程博览会、面向教师的材料夏令营和面向代表性不足的高中生的普林斯顿大学材料学院,将向学生展示计算系统的扩展焦点和新形式因素。
英文摘要
Electronics has enabled substantial computational capabilities in small-scale devices; this means that signals from physical systems can be presented to these devices to derive high-value outputs. The challenge is that although immense computational capacity can be realized in embedded devices, the ability to acquire a large number of signals that are distributed across a physical system, and to then communicate information over the associated distances, remains disproportionately small. Technologies are emerging, however, that enable transformational possibilities for creating communication channels and large-scale physical interfaces to electronics. Large-area electronics is a technology that enables the fabrication of interconnects as well as expansive arrays of diverse sensors on flexible, low-cost sheets. When combined with high-performance silicon integrated circuits (ICs), this technology can lead to systems where computation can be applied to physical signals on a much larger scale than that possible today. The resulting design space for the systems covers two technology domains. To create efficient and scalable systems, the platform components and hardware architectures must be analyzed rigorously, and methodologies for understanding and optimizing design trade-offs must be developed. The objective of this research is to analytically model the platform components and architectures for sensing and communication, and then to synthesize these into system design methodologies. The platform architectures include interfaces for digital and analog signaling, control circuits for sensing, and communication networks scalable to many nodes. The methodologies span analysis at the device, architecture, and system-protocol levels. Some of the compelling applications that require large-scale interfacing of electronics with physical systems include detection of early-stage structural degradation in bridges and buildings through centimeter-resolution strain sensing, interactive surfaces for visually-rich computing via high-resolution displays and input sensors, etc. Large-area electronics and high-performance ICs, used synergistically, have the potential to enable such applications. By developing analytical models and methodologies for system design, this research aims to unite the efforts from both the technology-development and computer-systems domains. The outcomes of this study will help coordinate and focus research and engineering efforts in these areas towards the creation of optimal systems. This research will also engage a new generation of engineers, particularly from underrepresented groups, through the unique opportunity to develop systematic principles for the design of computing systems that interact extensively with physical systems. The broadened focus and new form-factors possible for computing systems will be illustrated to students through undergraduate projects and special-topic courses, as well as through Princeton outreach programs such as the Science and Engineering Expo for middle-school students, the Materials Camp for teachers, and the Princeton University Materials Academy for under-represented high-school students.
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CAREER: Hardware and Algorithmic Architectures for Analyzing Physically-complex Systems: embedding inference capabilities in ultra-low-power sensors
  • 批准号:
    1253670
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $44.57万
  • 财政年份:
    2013
  • 负责人:
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Combining Large-area Electronics with High-performance Computation for Scalable Ambient Intelligence
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  • 负责人:
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Small RNAs调控解淀粉芽胞杆菌FZB42生防功能的机制研究
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  • 项目类别:
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