A Lightweight Peripheral Design for RRAM-based LUTs

Resistive random-access memory (RRAM) has garnered increasing interest due to its compact structure size, low energy requirements, and non-volatility. Recently, RRAM crossbars have shown potential for implementing lookup tables (LUTs) for reconfigurable logic. However, due to its analog properties, RRAM suffers from extensive peripherals, such as analog-to-digital converters (ADCs). In this paper, we tackle this problem by combining signal amplification, logic disjunction, and conversion to the digital domain in a single compact gate. As a result, the proposed RRAM-based LUT (R-LUT) design reduces the area per LUT by a factor of four and the peripheral overhead by more than six times. It is also almost three times smaller than an SRAM-based LUT implemented in the same technology. At the same time, it achieves a competitive access frequency of more than 3 GHz while consuming less than 240 fJ per inference, improving all major aspects of state-of-the-art R-LUT designs.

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Publication Details

Published
2025-05-25
DOI
https://doi.org/10.1109/iscas56072.2025.11043944
Primary Topic
Advanced Neural Network Applications
Type
article
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article

A Lightweight Peripheral Design for RRAM-based LUTs

Saleh Mulhem, Christoph Hübner, Mladen Bereković, Rainer Buchty et al.
Advanced Neural Network Applications
article

A Lightweight Peripheral Design for RRAM-based LUTs

Saleh Mulhem, Christoph Hübner, Mladen Bereković, Rainer Buchty, Philipp Grothe
article en

Abstract

Resistive random-access memory (RRAM) has garnered increasing interest due to its compact structure size, low energy requirements, and non-volatility. Recently, RRAM crossbars have shown potential for implementing lookup tables (LUTs) for reconfigurable logic. However, due to its analog properties, RRAM suffers from extensive peripherals, such as analog-to-digital converters (ADCs). In this paper, we tackle this problem by combining signal amplification, logic disjunction, and conversion to the digital domain in a single compact gate. As a result, the proposed RRAM-based LUT (R-LUT) design reduces the area per LUT by a factor of four and the peripheral overhead by more than six times. It is also almost three times smaller than an SRAM-based LUT implemented in the same technology. At the same time, it achieves a competitive access frequency of more than 3 GHz while consuming less than 240 fJ per inference, improving all major aspects of state-of-the-art R-LUT designs.

Openalex Percentile: Top 87%
Advanced Neural Network Applications
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