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

电子学使小规模设备具有相当大的计算能力;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中的大量信号，然后在相关距离上传递信息的能力仍然不成比例地小。然而，技术正在出现，为创建通信通道和大规模电子物理接口提供了变革的可能性。大面积电子技术是一种能够在柔性低成本片材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，这项技术可以导致系统的计算可以应用于比今天可能的更大规模的物理信号。由此产生的系统设计空间涵盖两个技术领域。为了创建高效和可扩展的系统，必须严格分析平台组件和硬件架构，并开发用于理解和优化设计权衡的方法。本研究的目的是分析模型的平台组件和架构的传感和通信，然后综合这些系统的设计方法。该平台架构包括用于数字和模拟信号的接口、用于感测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、架构和系统协议级别的分析。 一些引人注目的应用需要电子设备与物理系统的大规模接口，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。本研究透过发展系统设计的分析模式与方法，将科技发展与电脑系统领域的研究成果结合起来。本研究的结果将有助于协调和集中这些领域的研究和工程工作，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。扩大重点和新的形式因素可能计算系统将通过本科项目和专题课程，以及通过普林斯顿大学的推广计划，如科学和工程博览会的中学生，材料营的教师，和普林斯顿大学材料学院的代表性不足的高中学生向学生展示。

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.