This article reviews recent progress in the development of the computing framework vector symbolic architectures (VSA) (also known as hyperdimensional computing). This framework is well suited for implementation in stochastic, emerging hardware, and it naturally expresses the types of cognitive operations required for artificial intelligence (AI). We demonstrate in this article that the field-like algebraic structure of VSA offers simple but powerful operations on high-dimensional vectors that can support all data structures and manipulations relevant to modern computing. In addition, we illustrate the distinguishing feature of VSA, “computing in superposition,” which sets it apart from conventional computing. It also opens the door to efficient solutions to the difficult combinatorial search problems inherent in AI applications. We sketch ways of demonstrating that VSA are computationally universal. We see them acting as a framework for computing with distributed representations that can play a role of an abstraction layer for emerging computing hardware. This article serves as a reference for computer architects by illustrating the philosophy behind VSA, techniques of distributed computing with them, and their relevance to emerging computing hardware, such as neuromorphic computing.

中文翻译：

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矢量符号架构作为新兴硬件的计算框架


本文回顾了计算框架矢量符号架构 (VSA)（也称为超维计算）的开发最新进展。该框架非常适合在随机的新兴硬件中实现，并且它自然地表达了人工智能 (AI) 所需的认知操作类型。我们在本文中证明，VSA 的类场代数结构提供了对高维向量的简单但强大的运算，可以支持与现代计算相关的所有数据结构和操作。此外，我们还说明了 VSA 的显着特征，即“叠加计算”，这使其区别于传统计算。它还为人工智能应用中固有的困难组合搜索问题的有效解决方案打开了大门。我们概述了证明 VSA 在计算上通用的方法。我们将它们视为分布式表示计算的框架，可以充当新兴计算硬件的抽象层。本文通过阐述 VSA 背后的原理、分布式计算技术以及它们与神经形态计算等新兴计算硬件的相关性，为计算机架构师提供参考。