Collaborative Research: Synthesis, Verification and Testing for Nano-CMOS and Beyond using Threshold Logic

合作研究：使用阈值逻辑对 Nano-CMOS 及其他技术进行综合、验证和测试

• 批准号: 0702628
• 负责人: Spyros Tragoudas
• 金额: $ 10万
• 依托单位: Southern Illinois University at Carbondale
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-10-01 至 2011-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0702628&HistoricalAwards=false
• 关键词: Collaborative; Research; Synthesis; Verification; Testing

Project Id: 0702831 and 0702628 PI(s): Sarma Vrudhula and Spyros TragoudasTitle: Synthesis, Verification and Testing for Nano-CMOS and Beyond using Threshold LogicInstitutions: Arizona State University & ABSTRACTBy 2020, when thickness of Silicon will be less than a stack of a few atoms, the Semiconductor Industry Association roadmap predicts that further scaling CMOS circuits will not be sustainable, and expects a transition from CMOS to one or more of the presently nascent nano technologies such as resonant tunneling diodes (RTD), carbon nanotube FETs (CNFET) and carbon nanowires. Further in the future are devices such as single electron transistors (SET), and quantum cellular automata (QCA). An important and distinctive characteristic of these post-CMOS nano technologies is that they make it possible to efficiently and naturally implement threshold logic (TL). While TL concepts have been known since the 1960s, there has been no comprehensive work on synthesis and optimization of large TL networks similar to what we have witnessed over the past 30 years for traditional CMOS logic gate networks. This is a proposal to develop a comprehensive design methodology encompassing synthesis, optimization, verification, and testing of TL networks. We propose to investigate synthesis algorithms that start with a technology independent, functional description of the circuit. Optimization of TL networks poses unique problems. Regardless of the underlying technology, TL gates are realized by comparing the weighted sum of the inputs with a given threshold. This can be a comparison of voltages or currents. Since process variations can change the outcome of such a comparison, they not only effect the performance and power but can also change the function realized by the gate. We refer to this as the functional yield (FY). We will develop new algorithms that jointly maximize the FY, power consumption, and performance of a TL network over the space of process variables, e.g. device lengths, widths, threshold voltages, oxide thicknesses, etc. Methods for testing the manufactured circuit for functional correctness and delay using new parametric fault models will also be developed. Verifying the equivalence of a TL network to a given a functional specification has not yet been addressed. This is essential for verifying the result of the synthesis procedure as well as in determining the functional yield when the design parameters are represented as statistical quantities as models of process variations. Expected outcomes of this effort include: new CMOS and post-CMOS circuit architectures for TL gates; algorithms and tools to automatically synthesize, perform functional verification and generate test patterns for TL circuits; methods to compute the parametric yield of TL networks, modeling TL network parameters as correlated random variables; methods to perform joint optimization of functional yield, power consumption and performance of TL networks over the space of process variables.

项目编号：0702831和0702628 PI(s): Sarma Vrudhula和Spyros TragoudasTitle：纳米cmos及其超越阈值逻辑的合成，验证和测试到2020年，当硅的厚度将小于几个原子的堆叠时，半导体工业协会的路线图预测，进一步缩放CMOS电路将不可持续，并期望从CMOS过渡到一种或多种当前新兴的纳米技术，如谐振隧道二极管（RTD），碳纳米管场效应管（CNFET）和碳纳米线。未来还会出现单电子晶体管（SET）和量子细胞自动机（QCA）等设备。这些后cmos纳米技术的一个重要和独特的特点是，它们可以有效和自然地实现阈值逻辑（TL）。虽然自20世纪60年代以来就已经知道了TL概念，但在过去30年里，我们在传统CMOS逻辑门网络中所看到的大型TL网络的综合和优化方面还没有全面的工作。这是一项建议，旨在开发一种全面的设计方法，包括TL网络的合成、优化、验证和测试。我们建议研究从技术独立的电路功能描述开始的合成算法。TL网络的优化提出了一些独特的问题。无论底层技术如何，TL门都是通过将输入的加权和与给定阈值进行比较来实现的。这可以是电压或电流的比较。由于工艺变化可以改变这种比较的结果，它们不仅影响性能和功率，而且还可以改变门实现的功能。我们称之为功能产率（FY）。我们将开发新的算法，在过程变量的空间上共同最大化TL网络的FY，功耗和性能，例如器件长度，宽度，阈值电压，氧化物厚度等。还将开发使用新的参数化故障模型测试制造电路功能正确性和延迟的方法。验证TL网络与给定功能规范的等价性尚未得到解决。这对于验证合成过程的结果以及确定当设计参数作为工艺变化模型的统计量表示时的功能收率是必不可少的。这项工作的预期成果包括：用于TL门的新型CMOS和后CMOS电路架构；自动合成、功能验证和生成TL电路测试模式的算法和工具；计算TL网络参数产量的方法，将TL网络参数建模为相关随机变量；在过程变量空间上对TL网络的功能良率、功耗和性能进行联合优化的方法。