XPS: EXPL: FP: Collaborative Research: Formal methods based algorithmic synthesis of more-than-Moore nano-crossbars for extreme-scale computing

XPS：EXPL：FP：协作研究：基于形式方法的超摩尔纳米交叉开关的算法合成，用于超大规模计算

• 批准号: 1438989
• 负责人: Sumit Jha
• 金额: $ 21.5万
• 依托单位: The University of Central Florida Board of Trustees
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-08-01 至 2017-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1438989&HistoricalAwards=false
• 关键词: XPS; EXPL; FP; Collaborative; Research

The transistor density of integrated circuits has been doubling approximately every two years for about four decades. This exponential rise in the computational power of the integrated circuit has driven the information technology revolution that has transformed every aspect of our society - from personal entertainment devices to high-assurance intelligent cyber-physical systems. However, the growth in transistor density is now slowing down, and new technological breakthroughs are urgently needed to sustain the ongoing information technology revolution. This project creates a new memristor-based nano-computing architecture that circumvents the fabrication density problems associated with traditional transistor-based integrated circuits. The project investigates the fundamental principles of memristor-based nano-computing and designs efficient memristor-based nano-crossbar circuits that can execute elementary bit-vector mathematical and logical computations. The project pursues a transformative agenda for next-generation extreme-scale computing involving two design principles: (1) the use of memristors as distributed asynchronous digital switches and continuous-valued non-volatile nano-stores of input data and intermediate results, and (2) the use of sneak-paths in nano-crossbars as fundamental computational primitives that pool together results of intermediate computations from distributed memristor nano-stores.The memristor-based nano-computing architecture developed in the project will enable the execution of legacy programs on low-energy ultra-dense memristive nano-crossbar circuits and will facilitate the design of domain-specific parallel execution engines that combine storage and computation on the same chip - thereby nullifying the traditional barrier between the memory and the microprocessor.

综合电路的晶体管密度在大约四十年的时间里大约每两年增加一次。综合电路的计算能力的指数级增长驱动了信息技术革命，这改变了我们社会的各个方面 - 从个人娱乐设备到高质量智能的网络物理系统。但是，晶体管密度的增长现在正在减慢，并且迫切需要新的技术突破来维持正在进行的信息技术革命。该项目创建了一个新的基于备忘录的纳米计算结构，该体系结构规避了与传统的基于晶体管的集成电路相关的制造密度问题。该项目调查了基于备忘录的纳米计算和设计有效的基于Memristor的纳米杂交电路的基本原理，这些纳米杂交电路可以执行基本的比特矢量数学和逻辑计算。 The project pursues a transformative agenda for next-generation extreme-scale computing involving two design principles: (1) the use of memristors as distributed asynchronous digital switches and continuous-valued non-volatile nano-stores of input data and intermediate results, and (2) the use of sneak-paths in nano-crossbars as fundamental computational primitives that pool together results of intermediate computations从分布式的回忆录纳米商店中。项目中开发的基于回忆录的纳米计算结构将使在低能超密度超密度的超密度的纳米杂交电路上执行遗留程序，并将促进范围内的储存和计算机上的固定式储藏和计算机的设计，从而将其组合在同一芯片上，并将其组合在相同的芯片上 - 将其组合在同一芯片上 - 微处理器。