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Efficient Associative Search in Brain-Inspired Hyperdimensional Computing
IEEE Design & Test ( IF 2 ) Pub Date : 2019-05-30 , DOI: 10.1109/mdat.2019.2919954
Mohsen Imani , Justin Morris , Helen Shu , Shou Li , Tajana Rosing

This article describes a method for efficient hypervector operations using a grouping strategy for reduced computations. Quantization is used for reducing the number of multiplications, whereas caching of magnitude is used for eliminating redundant computations.

中文翻译:

脑启发式超维计算中的有效联想搜索

本文介绍了一种有效的超向量操作方法,该方法使用分组策略来减少计算量。量化用于减少乘法次数,而幅度缓存用于消除冗余计算。
更新日期:2020-04-21
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