SHF:Small: Collaborative Research: CONTINUOUS-TIME DIGITAL COMPUTATION AND SIGNAL PROCESSING

SHF:Small：协作研究：连续时间数字计算和信号处理

• 批准号: 1734577
• 负责人: Rajit Manohar
• 金额: $ 7.28万
• 依托单位: Yale University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-01-01 至 2017-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1734577&HistoricalAwards=false
• 关键词: SHF; Small; Collaborative; Research; CONTINUOUS

The goal of this research is to develop high-performance and power-efficient digital signal processors, using a novel event-driven approach involving special techniques that carefully keep track of the timing of events. Unlike standard "asynchronous" logic this approach inherently uses physical time as part of its representation of information. The systems and techniques to be developed in course of this research can benefit a number of important applications, including sensor networks and biomedical instrumentation in health care. The body of knowledge to be created would potentially find applications in other areas as well, including control systems and robotics. The work has a significant educational component, in that it involves synergistic development, combining different domains of knowledge and thus training the graduate and undergraduate students involved in interdisciplinary work, leading to new, creative solutions. Appealing technical properties of this approach include the absence of aliasing, better spectral properties of error, and faster response to changing inputs, compared to classical techniques. The approach is suitable for certain applications that demand very low power dissipation, notably those involving portability or difficult-to-access locations. While prior work concentrated on demonstrating the feasibility of continuous-time digital signal processors, this new effort concentrates on developing next-generation systems and achieving very high performance, necessitating new principles and techniques. The work seeks to advance the performance of continuous-time digital signal processors by reducing the effective sampling rate and improving output reconstruction, by using special coding techniques for relaxing granularity requirements in the signal processing units, by processing directly non-uniformly quantized signals, and by employing algorithmic techniques; it also expands continuous-time digital techniques to general scientific computation. The proposed effort brings together two groups with complementary expertise. The Columbia University group specializes in mixed-signal circuits and has demonstrated the first continuous-time digital signal processors; the Cornell University group works in asynchronous digital electronics, including event-driven processors and asynchronous dataflow FPGAs.

这项研究的目标是开发高性能和高能效的数字信号处理器，使用一种新颖的事件驱动方法，涉及仔细跟踪事件时序的特殊技术。与标准“异步”逻辑不同，这种方法本质上使用物理时间作为其信息表示的一部分。本研究过程中开发的系统和技术可以使许多重要应用受益，包括传感器网络和医疗保健中的生物医学仪器。要创建的知识体系也可能在其他领域找到应用，包括控制系统和机器人技术。这项工作具有重要的教育意义，因为它涉及协同发展，结合不同的知识领域，从而培训参与跨学科工作的研究生和本科生，从而产生新的、创造性的解决方案。与传统技术相比，这种方法具有吸引力的技术特性包括不存在混叠、更好的误差频谱特性以及对不断变化的输入的更快响应。该方法适用于需要极低功耗的某些应用，特别是那些涉及便携性或难以访问的位置的应用。虽然之前的工作集中在证明连续时间数字信号处理器的可行性，但这项新工作的重点是开发下一代系统并实现非常高的性能，因此需要新的原理和技术。这项工作旨在通过降低有效采样率和改进输出重构、使用特殊编码技术来放宽信号处理单元中的粒度要求、直接处理非均匀量化信号，以及提高连续时间数字信号处理器的性能。通过采用算法技术；它还将连续时间数字技术扩展到一般科学计算。拟议的工作将两个具有互补专业知识的小组聚集在一起。哥伦比亚大学小组专注于混合信号电路，并展示了第一个连续时间数字信号处理器；康奈尔大学小组致力于异步数字电子技术，包括事件驱动处理器和异步数据流 FPGA。