Automated Synthesis Of Compact Crossbars For Sneak-Path Based In-Memory Computing

Abstract

The rise of data-intensive computational loads has exposed the processor-memory bottleneck in Von Neumann architectures and has reinforced the need for in-memory computing using devices such as memristors. Existing literature on computing Boolean formula using sneak-paths in nanoscale memristor crossbars has only focussed on short Boolean formula. There are two open questions: (i) Can one synthesize sneak-path based crossbars for computing large Boolean formula? (ii) What is the size of a memristor crossbar that can compute a given Boolean formula using sneak paths? In this paper, we make progress on both these problems. First, we show that the number of rows and columns required to compute a Boolean formula is at most linear in the size of the Reduced Ordered Binary Decision Diagram representing the Boolean function. Second, we demonstrate how Boolean Decision Diagrams can be used to synthesize nanoscale crossbars that can compute a given Boolean formula using naturally occurring sneak paths. In particular, we synthesize large logical circuits such as 128-bit adders for the first-time using sneak-path based crossbar computing.

Publication Date

5-11-2017

Publication Title

Proceedings of the 2017 Design, Automation and Test in Europe, DATE 2017

Number of Pages

770-775

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.23919/DATE.2017.7927093

Socpus ID

85020198633 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/85020198633

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