**Automated Synthesis of Compact Crossbars for Sneak-Path Based In-Memory Computing**

Dwaipayan Chakraborty^{a} and Sumit Kumar Jha^{b}

*Computer Science Department, University of Central Florida, Orlando, Florida. *

^{a}dchakra@eecs.ucf.edu

^{b}jha@eecs.ucf.edu

**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.