Efficient Associative Search in Brain-Inspired Hyperdimensional Computing

Mohsen Imani
Mohsen Imani
Justin Morris
Justin Morris
Helen Shu
Helen Shu
Shou Li
Shou Li

IEEE Design & Test, pp. 28-35, 2020.

Cited by: 0|Bibtex|Views59|DOI:https://doi.org/10.1109/MDAT.2019.2919954
EI WOS
Other Links: dblp.uni-trier.de|academic.microsoft.com

Abstract:

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.

Code:

Data:

Your rating :
0

 

Tags
Comments