NEB: Physics-Inspired Non-Boolean Computation based on Spatial- Temporal Wave Excitations

该项目是在Nanoelectronics for 2020及以后的竞争中获得的，得到了国家科学基金会多个部门和部门以及半导体研究公司Nanoelectronics Research Initiative的支持。这项工作的动机是未来的计算机芯片具有数百万个核心的愿景，其中每个核心都具有类似于早期微处理器的复杂性。此外，可以设想，这种系统中的计算可以以全新的方式完成，更类似于处理元件的类脑网络中的波传播。这项工作将确定波浪状的非布尔计算基元的基础上的时空特性，这样的处理器网络，灵感将从已知的波的物理行为和应用程序从这些派生。此外，纳米电子系统将探讨这种波型激发可能会找到一个自然的实现。 这项研究将确定，在物理层面上，基于纳米电子结构与时空波动动力学的计算构建块，并在计算机科学层面上，方法来执行计算与这种非布尔原语。 这项跨学科的研究，涵盖了从纳米结构到新的计算范式的整个范围，将需要一个拥有从物理学到计算机科学的专业知识的团队。 这一提议将为一种完全不同的信息处理方法奠定基础，这种方法是基于物理学启发的，在纳米电子处理元件的大规模阵列中具有类似大脑的波行为。 具体来说，我们的研究将确定未来计算系统的计算构建块，沿着固有的状态变量，其中每个计算任务直接映射到底层的物理结构。 该项目还将确定哪些信息处理任务将在这种架构中自然实现。这项拟议的研究计划与半导体研究公司（SRI）纳米电子研究计划（NRI）和SRC-NRI中西部纳米电子发现研究所（MIND）的活动协同。 特别是，这项研究将与英特尔的乔治Bourianoff博士合作，他领导了一个研究小组，对超低功耗应用特定的非布尔系统，这是密切相关的研究在这里提出。如果成功，这项工作将影响信息处理的方式在未来的信息处理系统。这项工作不仅会导致信息处理系统的逐步改进，而且会为计算机体系结构的全新方法打开大门。 计算将不再基于基本的布尔逻辑函数，而是基于物理学启发的和类似大脑的波活动。这将需要对计算是如何进行的进行彻底的重新思考。作为这项研究的一部分，研究生将接受这种新的思维方式的教育和培训，了解如何以更像大脑的方式进行计算。 在积极的REU和RET计划的基础上，本科生和教师将参与这项工作。 这是一个明确的目标，在一个最大限度地包容代表性不足的群体的环境中进行这项研究。

This project is awarded under the Nanoelectronics for 2020 and Beyond competition, with support by multiple Directorates and Divisions at the National Science Foundation as well as by the Nanoelectronics Research Initiative of the Semiconductor Research Corporation. This work is motivated by the vision of future computer chips with millions of cores, where each core has a complexity similar to early microprocessors. Furthermore, it is envisioned that computation in such systems might be done in an entirely new way, more akin to wave propagation in a brain-like network of processing elements. This work will identify wave-like non-Boolean computational primitives based on the spatial-temporal characteristics of such processor networks, and inspiration will be gained from known wave behavior in physics and applications derived from these. In addition, nanoelectronic systems will be explored where such wave-type excitations might find a natural implementation. This research will identify, on the physical level, computational building blocks based on nanoelectronic structures with spatial-temporal wave-like dynamics, and on the computer science level, ways to perform computation with such non-Boolean primitives. This interdisciplinary research, which spans the whole range from nanostructures to new paradigms for computing, will require a team with expertise that spans the whole range from physics to computer science. This proposal will lay the groundwork for a radically different approach to information processing, which is based on physics-inspired and brain-like wave behavior in large-scale arrays of nanoelectronic processing elements. Specifically, our research will identify computational building blocks of future computing systems, along with the inherent state variables, where each computational task directly maps onto the underlying physical structure. This project will also identify which information-processing tasks will find their natural implementation in such architectures. This proposed research is planned in synergy with the Semiconductor Research Corporation (SRI) Nanoelectronics Research Initiative (NRI) and activities at the SRC-NRI Midwest Institute for Nanoelectronics Discovery (MIND). In particular, this research will partner with Dr. George Bourianoff at Intel, who leads a study group on Ultra Low Power Application Specific Non-Boolean Systems, which is closely related to the research proposed here.If successful, this work would impact the way information processing is done in future information-processing systems. This work will not merely lead to incremental improvements in information processing systems, but open the door to an entirely new approach to computer architecture. Computation no longer will be based on elementary Boolean logic functions, but on physics-inspired and brain-like wave activity. This will necessitate a complete re-thinking of how computation is being done. As part of this research, graduate students will be educated and trained in this new way of thinking about how computation is done in a more brain-like fashion. Building upon active REU and RET programs, undergraduates and teachers will participate in this work. It is a stated goal to perform this research in an environment of maximum inclusivity of underrepresented groups.