This article reviews recent progress in the development of the computing framework Vector Symbolic Architectures (also known as Hyperdimensional Computing). This framework is well suited for implementation in stochastic, nanoscale hardware and it naturally expresses the types of cognitive operations required for Artificial Intelligence (AI). We demonstrate in this article that the ring-like algebraic structure of Vector Symbolic Architectures offers simple but powerful operations on high-dimensional vectors that can support all data structures and manipulations relevant in modern computing. In addition, we illustrate the distinguishing feature of Vector Symbolic Architectures, "computing in superposition," which sets it apart from conventional computing. This latter property opens the door to efficient solutions to the difficult combinatorial search problems inherent in AI applications. Vector Symbolic Architectures are Turing complete, as we show, and we see them acting as a framework for computing with distributed representations in myriad AI settings. This paper serves as a reference for computer architects by illustrating techniques and philosophy of VSAs for distributed computing and relevance to emerging computing hardware, such as neuromorphic computing.

中文翻译：

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矢量符号体系结构作为纳米级硬件的计算框架

本文回顾了计算框架 Vector Symbolic Architectures（也称为超维计算）的最新进展。该框架非常适合在随机的纳米级硬件中实现，它自然地表达了人工智能 (AI) 所需的认知操作类型。我们在本文中展示了向量符号体系结构的环状代数结构对高维向量提供了简单但强大的运算，可以支持现代计算中相关的所有数据结构和操作。此外，我们还说明了向量符号体系结构的显着特征，即“叠加计算”，这将其与传统计算区分开来。后一种特性为解决人工智能应用程序固有的困难组合搜索问题的有效解决方案打开了大门。正如我们所展示的，矢量符号架构是图灵完备的，我们将它们视为在无数 AI 设置中使用分布式表示进行计算的框架。本文通过说明用于分布式计算的 VSA 的技术和理念以及与新兴计算硬件（如神经形态计算）的相关性，作为计算机架构师的参考。