A Survey of Spintronic Architectures for Processing-in-Memory and Neural Networks

Umesh, Sumanth and Mittal, Sparsh (2018) A Survey of Spintronic Architectures for Processing-in-Memory and Neural Networks. Journal of Systems Architecture. ISSN 1383-7621 (In Press)

Full text not available from this repository. (Request a copy)


The rising overheads of data-movement and limitations of general-purpose processing architectures have led to a huge surge in the interest in “processing-in-memory” (PIM) approach and “neural networks” (NN) architectures. Spintronic memories facilitate efficient implementation of PIM approach and NN accelerators, and offer several advantages over conventional memories. In this paper, we present a survey of spintronic-architectures for PIM and NNs. We organize the works based on main attributes to underscore their similarities and differences. This paper will be useful for researchers in the area of artificial intelligence, hardware architecture, chip design and memory system.

[error in script]
IITH Creators:
IITH CreatorsORCiD
Mittal, Sparshhttp://orcid.org/0000-0002-2908-993X
Item Type: Article
Uncontrolled Keywords: Review, Spin transfer torque RAM, Spin orbit torque, Domain wall memory, Processing-in-memory, Machine learning, neural networks.
Subjects: Computer science
Divisions: Department of Computer Science & Engineering
Depositing User: Team Library
Date Deposited: 28 Nov 2018 09:01
Last Modified: 28 Nov 2018 09:01
URI: http://raiith.iith.ac.in/id/eprint/4568
Publisher URL: http://doi.org/10.1016/j.sysarc.2018.11.005
OA policy: http://www.sherpa.ac.uk/romeo/issn/1383-7621/
Related URLs:

Actions (login required)

View Item View Item
Statistics for RAIITH ePrint 4568 Statistics for this ePrint Item