Publication Type
Journal Article
Version
publishedVersion
Publication Date
2-2011
Abstract
Increasing density based on bit size reduction is currently a main driving force for the development of data storage technologies. However, it is expected that all of the current available storage technologies might approach their physical limits in around 15 to 20 years due to miniaturization. To further advance the storage technologies, it is required to explore a new development trend that is different from density driven. One possible direction is to derive insights from biological counterparts. Unlike physical memories that have a single function of data storage, human memory is versatile. It contributes to functions of data storage, information processing, and most importantly, cognitive functions such as adaptation, learning, perception, knowledge generation, etc. In this paper, a brief review of current data storage technologies are presented, followed by discussions of future storage technology development trend. We expect that the driving force will evolve from density to functionality, and new memory modules associated with additional functions other than only data storage will appear. As an initial step toward building a future generation memory technology, we propose Artificial Cognitive Memory (ACM), a memory based intelligent system. We also present the characteristics of ACM, new technologies that can be used to develop ACM components such as bioinspired element cells (silicon, memristor, phase change, etc.), and possible methodologies to construct a biologically inspired hierarchical system.
Keywords
Artificial Cognitive Memory, Data storage, cognitive computing
Discipline
Databases and Information Systems
Research Areas
Data Science and Engineering
Publication
Applied Physics A
Volume
102
Issue
4
First Page
865
Last Page
875
ISSN
0947-8396
Identifier
10.1007/s00339-011-6297-0
Citation
SHI, Luping; YI, Kaijun; RAMANATHAN, Kiruthika; ZHAO, Rong; NING, Ning; DING, Ding; and CHONG, Tow Chong.
Artificial cognitive memory - Changing from density driven to functionality driven. (2011). Applied Physics A. 102, (4), 865-875.
Available at: https://ink.library.smu.edu.sg/sis_research/7360
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
http://doi.org/10.1007/s00339-011-6297-0