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Cellular automata basedmulti-bit stuck-at fault diagnosis for resistive memory

Frontiers of Information Technology & Electronic Engineering 2022年第7期23卷 1110-1126页

作者： Sutapa SARKAR Biplab Kumar SIKDAR Mousumi SAHA Department of Electronics and Communication Engineering Seacom Engineering CollegeHowrahWest Bengal 711302India Department of Computer Science and Technology Indian Institute of Engineering Science and TechnologyHowrahWest Bengal 711103India Department of Computer Science and Engineering National Institute of TechnologyDurgapurWest Bengal 713209India

This paper presents a group-based dynamic stuck-at fault diagnosis scheme intended for resistive randomaccess memory(ReRAM).Traditional static random-access memory,dynamic random-access memory,NAND,and NOR flash memory are limited by their scalability,power,package density,and so forth.Next-generation memory types like ReRAMs are considered to have various advantages such as high package density,non-volatility,scalability,and low power consumption,but cell reliability has been a problem.Unreliable memory operation is caused by permanent stuck-at faults due to extensive use of write-or memory-intensive workloads.An increased number of stuck-at faults also prematurely limit chip lifetime.Therefore,a cellular automaton(CA)based dynamic stuck-at fault-tolerant design is proposed here to combat unreliable cell functioning and variable cell lifetime issues.A scalable,block-level fault diagnosis and recovery scheme is introduced to ensure readable data despite multi-bit stuck-at faults.The scheme is a novel approach because its goal is to remove all the restrictions on the number and nature of stuck-at faults in general fault conditions.The proposed scheme is based on Wolfram’s null boundary and periodic boundary CA theory.Various special classes of CAs are introduced for 100%fault tolerance:single-lengthcycle single-attractor cellular automata(SACAs),single-length-cycle two-attractor cellular automata(TACAs),and single-length-cycle multiple-attractor cellular automata(MACAs).The target micro-architectural unit is designed with optimal space overhead.

关键词： resistive memory Cell reliability Stuck-at fault diagnosis Single-length-cycle single-attractor cellular automata Single-length-cycle two-attractor cellular automata Single-length-cycle multiple-attractor cellular automata

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Recent advances in organic-based materials for resistive memory applications

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InfoMat 2020年第6期2卷 995-1033页

作者： Yang Li Qingyun Qian Xiaolin Zhu Yujia Li Mayue Zhang Jingni Li Chunlan Ma Hua Li Jianmei Lu Qichun Zhang College of Chemistry Chemical Engineering and Materials ScienceSoochow UniversitySuzhouJiangsuChina Jiangsu Key Laboratory of Micro and Nano Heat Fluid Flow Technology and Energy Application School of Mathematics and PhysicsSuzhou University of Science and TechnologySuzhouJiangsuChina School of Materials Science and Engineering Nanyang Technological UniversitySingaporeSingapore

With the rapid development of data-driven human interaction,advanced datastorage technologies with lower power consumption,larger storage capacity,faster switching speed,and higher integration density have become the goals of future memory electronics.Nevertheless,the physical limitations of conventional Si-based binary storage systems lag far behind the ultrahigh-density requirements of post-Moore information storage.In this regard,the pursuit of alternatives and/or supplements to the existing storage technology has come to the forefront.Recently,organic-based resistive memory materials have emerged as promising candidates for next-generation information storage applications,which provide new possibilities of realizing high-performance organic electronics.Herein,the memory device structure,switching types,mechanisms,and recent advances in organic resistive memory materials are reviewed.In particular,their potential of fulfilling multilevel storage is summarized.Besides,the present challenges and future prospects confronted by organic resistive memory materials and devices are discussed.

关键词： data storage memristors organic electronics organic-inorganic hybrids resistive memory semiconductors

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Design memristor-based computing-in-memory for AI accelerators considering the interplay between devices, circuits, and system

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Science China(Information Sciences) 2023年第8期66卷 243-253页

作者： Junjie AN Linfang WANG Wang YE Weizeng LI Hanghang GAO Zhi LI Zhidao ZHOU Jinghui TIAN Jianfeng GAO Chunmeng DOU Qi LIU School of Microelectronics University of Science and Technology of China State key Lab of Fabrication Technologies for Integrated Circuits Institute of MicroelectronicsChinese Academy of Sciences School of Microelectronics University of Chinese Academy of Sciences Frontier Institute of Chip and System State Key Laboratory of ASIC and System Fudan University

Recent advances in developing beyond von Neumann architectures have moved the memristive devices to the forefront as one of the key enablers to realizing memristive computing-in-memory(m CIM)structures, which shows a great promise to boost the energy-efficiency and the performance of artificial intelligence(AI) chips. In this study, by considering the interactions between devices, circuits, and systems in the m CIM design, we propose several cross-layer design techniques, including(1) the BL-SL interactive forming protection(BSIFP) circuit that can reduce the voltage drop on the selected transistor, suppress the current overshoot by 65.96%, and improve the bit-cell density by more than 10.19%,(2) the clamping transistor trimming scheme(CTTS) to prevent the multiply-and-accumulate(MAC) signal margin degradation from chip-to-chip resistance variations, and(3) dynamic input-parallelism and output-precision(DIPOP) that can reduce the energy cost by 22.92% in a typical inference task with negligible accuracy loss. The results demonstrate the significant role of the cross-layer-interactive approach and provide a preliminary guideline for highly-efficient m CIM design.

关键词： memristor resistive memory computing-in-memory artificial intelligence cross-layer co-design

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Lead-free perovskite MASnBr3-based memristor for quaternary information storage

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InfoMat 2020年第4期2卷 743-751页

作者： Wen-Hu Qian Xue-Feng Cheng Jin Zhou Jing-Hui He Hua Li Qing-Feng Xu Na-Jun Li Dong-Yun Chen Zhi-Gang Yao Jian-Mei Lu National United Engineering Laboratory of Functionalized Environmental Adsorption Materials College of ChemistryChemical Engineering and Materials ScienceCollaborative Innovation Center of Suzhou Nano Science and TechnologySoochow UniversitySuzhouChina Testing and Analysis Center Soochow UniversitySuzhouChina

Memristors are a new type of circuit element with a resistance that is tunable to discrete levels by a voltage/current and sustainable after removal of power,allowing for low-power computation and multilevel information storage.Many organic-inorganic lead perovskites are reported to demonstrate memristive behavior,but few have been considered for use as a multilevel memory;also,their potential application has been hindered by the toxicity of lead ions.In this article,lead-free perovskite MASnBr3 was utilized in memristors for quaternary information storage.Indium tin oxide(ITO)/MASnBr3/Au memristors were fabricated and showed reliable memristive switching with well-separated ON/OFF states of a maxima resistance ratio of 102 to 103.More importantly,four resistive states can be distinguished and repeatedly written/read/erased with a retention time of 104 seconds and an endurance of 104 pulses.By investigating the current-electrode area relationship,Br distribution in the ON/OFF states by in situ Raman and scanning electron microscopy,and temperaturedependent current decay,the memristive behavior was explicitly attributed to the forming/breaking of conductive filaments caused by the migration of Br−under an electric field.In addition,poly(ethylene terephthalate)-ITO/MASnBr3/Au devices were found to retain their multiresistance state behavior after being bent for 1000 times,thus demonstrating good device flexibility.Our results will inspire more lead-free perovskite work for multilevel information storage,as well as other memristor-based electronics.

关键词： MASnBr3 memristor perovskite resistive memory RRAM

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Phase change memory

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Science China(Information Sciences) 2011年第5期54卷 1061-1072页

作者： LAM Chung IBM Research T.J. Watson Research Center Yorktown Heights New York 10598 USA

Phase change memory (PCM) is a non-volatile solid-state memory technology based on the large resistivity contrast between the amorphous and crystalline states in phase change materials. We present the physics behind this large resistivity contrast and describe how it is being exploited to create high density PCM. We address the challenges facing this technology, including the design of PCM cells, fabrication, device variability, thermal cross-talk and write disturb. We discuss the scalability, assess the performance, and examine the reliability of PCM including data retention, multi-bit storage and endurance.

关键词： solid state memory non-volatile DRAM flash phase change resistive memory data retention write endurance solid-state drive computer memory

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