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EAGER: Exploration of topological self-organizing non-linear dynamical systems with memory as efficient scalable computing fabric

EAGER：探索以内存作为高效可扩展计算结构的拓扑自组织非线性动力系统

基本信息

批准号：
2034558
负责人：
Massimiliano Di Ventra
金额：
$ 29.85万
依托单位：
University of California-San Diego
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2020
资助国家：
美国
起止时间：
2020-10-01 至 2022-09-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2034558&HistoricalAwards=false
关键词：
EAGER Exploration topological self organizing

项目摘要

Unconventional computing models that depart substantially from how our traditional computers work are emerging as an important research direction in both fundamental science and technology. Quantum computing is the most celebrated example, where a phenomenon known as entanglement and unique to quantum mechanical systems, is expected to help in the solution of some difficult problems, such as prime factorization. However, there is a wide range of physical phenomena one can exploit other than entanglement, and that do not require extreme technological conditions to operate. This means that there is a vast area of research yet to explore between our traditional computers and quantum computing. This project will investigate a radically novel computing fabric that falls within this uncharted territory, and is able to solve difficult problems efficiently by means of non-quantum dynamical systems. Such a computing fabric is called memcomputing because it exploits the innate time non-locality of any physical system, namely memory of their past dynamics. If successful, this project is expected to usher in a paradigm shift in computing that will reverberate across practically all aspects of technology. The proposed activities will contribute to the professional development of highly skilled personnel with expertise that cuts across different disciplines involved in this project. To prove the fundamental value of such a non-von-Neumann computing fabric, this award will support the development of a simulator for digital memcomputing machines based on the numerical integration of the differential equations of appropriate non-quantum, non-linear dynamical systems with memory. To facilitate an independent verification, the simulator will then be employed to tackle challenging combinatorial problems, such as prime factorization, whose solution can be easily checked. This award will thus serve as the stepping stone towards the ultimate goal of realizing such digital memcomputing machines in hardware. This project will also advance our knowledge of the physical requirements to compute efficiently by investigating the deep relation between computing, topology, and collective behavior of physical systems.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

与传统计算机工作方式有很大不同的非传统计算模型正在成为基础科学和技术领域的一个重要研究方向。量子计算是最著名的例子，其中一种被称为纠缠和量子力学系统所特有的现象，预计将有助于解决一些困难的问题，如素数分解。然而，除了纠缠之外，还有很多物理现象可以利用，并且不需要极端的技术条件来操作。这意味着在我们的传统计算机和量子计算之间还有广阔的研究领域有待探索。该项目将研究一种全新的计算结构，该结构福尔斯属于这一未知领域，并且能够通过非量子动力学系统有效地解决困难问题。这种计算结构被称为memcomputing，因为它利用了任何物理系统固有的时间非局部性，即它们过去动态的记忆。如果成功的话，这个项目预计将迎来计算的范式转变，这将在技术的各个方面产生反响。拟议的活动将有助于高技能人员的专业发展，这些人员具有跨本项目所涉不同学科的专门知识。为了证明这种非冯·诺依曼计算结构的基本价值，该奖项将支持基于适当的非量子非线性动态系统与内存的微分方程的数值积分的数字存储器计算机模拟器的开发。为了便于独立验证，模拟器将被用来解决具有挑战性的组合问题，如素数分解，其解决方案可以很容易地检查。因此，该奖项将作为实现这种数字记忆计算机器硬件的最终目标的垫脚石。该项目还将通过调查计算、拓扑结构和物理系统的集体行为之间的深层关系，提高我们对有效计算的物理要求的认识。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。