Automated synthesis of compact crossbars for sneak-path based in-memory computing

被引:0
作者
Chakraborty, Dwaipayan [1 ]
Jha, Sumit Kumar [1 ]
机构
[1] Univ Cent Florida, Comp Sci Dept, Orlando, FL 32816 USA
来源
PROCEEDINGS OF THE 2017 DESIGN, AUTOMATION & TEST IN EUROPE CONFERENCE & EXHIBITION (DATE) | 2017年
基金
美国国家科学基金会;
关键词
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:770 / 775
页数:6
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