Efficient Memristive Stateful Logic Exploring Boolean Expressions in the Sum-of-Products Form

The semiconductor industry faces growing difficulties in addressing technical and technological challenges, such as the exhaustion of CMOS downscaling and the limitations imposed by the von Neumann bottleneck. At the same time, this sector needs to meet the requirements of increasingly demanding applications, such as Internet of Things (IoT) and Artificial Intelligence (AI). These circumstances have boosted the research development related to emerging technologies and new computing paradigms. In this context, the unique features of memristive devices make them promising objects of study in both areas. In light of this, we present a new concept for performing logic-in-memory (LiM) using memristive devices. Our method is based on expressions in the form of sum-of-products (SOP), and it establishes a pattern of voltage application on memristors, from which it is possible to compute any Boolean function through sequential steps. Our proposal exhibits an intuitive relationship with logic synthesis tools currently used in digital circuit design, and it can outperform other generalist schemes in the literature in sequence size and device count. Moreover, its implementation flexibility simplifies the handling of functions with varying fan-ins.

Authors

Institutions

Publication Details

Journal
IEEE Transactions on Circuits and Systems I Regular Papers
Published
2024-12-13
DOI
https://doi.org/10.1109/tcsi.2024.3515011
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Efficient Memristive Stateful Logic Exploring Boolean Expressions in the Sum-of-Products Form

Cesar de Souza Dias, Paulo F. Butzen, Raphael M. Brum, Helisa S. de Lima
IEEE Transactions on Circuits and Systems I Regular Papers
Advanced Memory and Neural Computing
article

Efficient Memristive Stateful Logic Exploring Boolean Expressions in the Sum-of-Products Form

Cesar de Souza Dias, Paulo F. Butzen, Raphael M. Brum, Helisa S. de Lima
article en

Abstract

The semiconductor industry faces growing difficulties in addressing technical and technological challenges, such as the exhaustion of CMOS downscaling and the limitations imposed by the von Neumann bottleneck. At the same time, this sector needs to meet the requirements of increasingly demanding applications, such as Internet of Things (IoT) and Artificial Intelligence (AI). These circumstances have boosted the research development related to emerging technologies and new computing paradigms. In this context, the unique features of memristive devices make them promising objects of study in both areas. In light of this, we present a new concept for performing logic-in-memory (LiM) using memristive devices. Our method is based on expressions in the form of sum-of-products (SOP), and it establishes a pattern of voltage application on memristors, from which it is possible to compute any Boolean function through sequential steps. Our proposal exhibits an intuitive relationship with logic synthesis tools currently used in digital circuit design, and it can outperform other generalist schemes in the literature in sequence size and device count. Moreover, its implementation flexibility simplifies the handling of functions with varying fan-ins.

IEEE Transactions on Circuits and Systems I Regular PapersVol. 72(9)
Universidade Federal do Rio Grande do Sul (BR)
Openalex Percentile: Top 80%
Advanced Memory and Neural Computing
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.