Signal Processing to the Rescue of Moore's Law

该项目旨在为抑制当今2500亿美元全球半导体行业增长的电源可靠性问题提供有效且低成本的解决方案。这是一个制造集成电路（IC）或微芯片的行业，这些集成电路或微芯片是消费电子产品、通信和计算产品（如手机、笔记本电脑、个人数字助理、调制解调器、路由器等）的核心。 摩尔？自上世纪70年代以来，一个推动行业创新和增长的自我实现的预言，预测每单位面积的晶体管数量将每18个月翻一番。 摩尔？这一定律正受到两种趋势的威胁：纳米非理想化的出现使得设计可靠的芯片变得困难，以及新应用和标准所要求的增加的功能导致高功耗。这就是威胁摩尔的电源可靠性问题？s定律。在这个项目中，研究人员正在利用信号处理理论和技术的力量，通过将纳米IC视为噪声通信网络，解决上述宽带通信系统IC的电源可靠性问题。研究分为三大活动。首先，将开发数字信号处理（DSP）特定模块（如数据路径、计算、存储器和片上通信模块）的参数化统计行为模型。接下来，将研究信号处理启发的技术，通过采用行为模型和使用统计信号处理理论的概念，如自适应滤波，检测和估计，误差控制和分布式和鲁棒系统理论，来设计信号处理和通信系统的鲁棒和节能的实现。最后，将在项目的最后一年实施和测试一个原型测试芯片，展示一种或多种技术的潜力。

This project seeks to provide effective and low-cost solutions to the power-reliability problem inhibiting the growth of the $250B global semiconductor industry today. This is the industry that manufactures integrated circuits (ICs) or micro-chips that lie at the heart of consumer electronics, communications and computing products such as cell-phones, lap-tops, personal digital assistants, modems, routers, and many others. Moore?s Law, a self-fulfilling prophesy driving innovation and growth in the industry since the 70s, predicts that the number of transistors per unit area will double every 18 months. Moore?s Law is under threat from two trends: emergence of nanometer non-idealities that make it hard to design reliable chips, and increased functionality demanded by new applications and standards resulting in high power consumption. This is then the power-reliability problem which threatens Moore?s Law. In this project, the investigators are employing the power of signal processing theory and techniques to solve the power-reliability problem described above in the context of ICs for broadband communication systems by viewing nanometer ICs as noisy communication networks. The research is organized into three major activities. First, parameterized statistical behavioral models for digital signal processing (DSP)-specific blocks such as data-path, computation, memory, and on-chip communication blocks will be developed. Next, signal processing-inspired techniques will be investigated for designing robust and energy-efficient implementations of signal processing and communication systems by employing the behavioral models and using concepts from statistical signal processing theory such as adaptive filtering, detection and estimation, error-control and distributed and robust systems theory. Finally, a prototype test chip demonstrating the potential of one or more of the techniques will be implemented and tested in the final year of the project.