Design Of Compact Memristive In-Memory Computing Systems Using Model Counting
Abstract
Crossbars of nanoscale memristors are being fabricated to serve as high-density non-volatile memory devices. The flow of current through memristor crossbars has been recently used to perform in-memory computations. However, existing approaches based on decision procedures only scale to the simplest circuits such as one-bit adders and other approaches employing decision diagrams produce large crossbar designs. In this paper, we present a new method for synthesizing compact combinational circuits using nanoscale crossbars. Our synthesis procedure exploits a symbolic representation of Boolean functions and employs model counting to guide a simulated annealing based search procedure. The proposed method creates crossbars that are up to about 6.3 times more compact than crossbars synthesized using decision diagrams. Our approach can scale to problems at least 4 times larger than the approach based on quantified decision procedures.
Publication Date
9-25-2017
Publication Title
Proceedings - IEEE International Symposium on Circuits and Systems
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1109/ISCAS.2017.8050965
Copyright Status
Unknown
Socpus ID
85032658884 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/85032658884
STARS Citation
Chakraborty, Dwaipayan and Jha, Sumit Kumar, "Design Of Compact Memristive In-Memory Computing Systems Using Model Counting" (2017). Scopus Export 2015-2019. 6636.
https://stars.library.ucf.edu/scopus2015/6636