Fault tolerant adaptive write schemes for improving endurance and reliability of memristor memories

Ravi, V.; Prabaharan, S. R. S.

doi:10.1016/j.aeue.2018.07.023

Cited by 13 publications

(9 citation statements)

References 52 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Application of a fixed write pulse can lead to degradation due to changes in the thickness/length of the break in the filament . To avoid this, the theoretical model [99] proposes a recording scheme that identifies the optimal amplitude and duration for the recording pulse. It has been found that the proposed scheme for various malfunctions of the memristor can effectively improve its endurance.…”

Section: Influence Of Switching the Pulse Parametersmentioning

confidence: 99%

To the Issue of the Memristor’s HRS and LRS States Degradation and Data Retention Time

Фадеев

Руденко

2021

Russ Microelectron

View full text Add to dashboard Cite

In this review of experimental studies, the retention time and endurance of memristor RRAM memory elements based on reversible resistive switching in oxide dielectrics are studied. The influence of external parameters—switching pulses and ambient temperature—as well as internal factors—evolution of the concentration of oxygen vacancies in the filament region, the material, structure; the thickness of the active dielectric layer, material of metal electrodes on the long-term stability of high resistance state (HRS) and the low resistance state (LRS) of the memristor is discussed.

show abstract

Section: Influence Of Switching the Pulse Parametersmentioning

confidence: 99%

To the Issue of the Memristor’s HRS and LRS States Degradation and Data Retention Time

Фадеев

Руденко

2021

Russ Microelectron

View full text Add to dashboard Cite

show abstract

“…This is sometimes known as durability. [ 65,66 ] The figure on the left side of Figure a shows that once the proportion of switches arrives at a particular level, the memristors are degraded and their memory properties are lost. From the comparison of the picture located on the left and right sides of Figure 4a, it can be observed that the durability of the memristor can be affected by the setting of the switching voltage.…”

Section: Characteristics and Structural Classification Of Memristorsmentioning

confidence: 99%

“…Reliability and randomness of memristors: a) Endurance behavior in memristive devices; Reproduced with permission. [ 66 ] Copyright 2018, Elsevier. b) Current fluctuations in resistive random access memory because of RTN p .…”

Section: Characteristics and Structural Classification Of Memristorsmentioning

confidence: 99%

Application of Memristors in Hardware Security: A Current State‐of‐the‐Art Technology

Liu

Geng

2020

Advanced Intelligent Systems

View full text Add to dashboard Cite

Memristors are widely used in hardware security applications. Research progress in memristor‐based physical unclonable functions (PUFs), random number generators (RNGs), and chaotic circuits is reviewed. To enhance device security, PUFs and RNGs apply randomness of memristors and incorporate 3D crossbars to amplify the number of challenge‐response pairs and provide proof of the destruction of the key, which enables the administrator to firmly control the device information. In addition, the image encryption technique based on the chaotic system is summarized. Furthermore, an assessment of the research advancement in PUFs, RNGs, and chaotic circuits is conducted. This Review examines the characteristics, applications, progress, and challenges of memristors in hardware security and compares the benefits and limitations of different schemes as accelerators for hardware information protection.

show abstract

“…There are various types of memristor defects that may affect network performance, and usually they occur due to process variation [45], [46]. Examples of device defects are ageing faults, endurance degradation faults, switching delay faults, and stuck-at faults [47], [48]. Here, we will emphasize the stuck-at fault as it is ubiquitous and has high impact on 16.…”

Section: Device Failure and Network Robustnessmentioning

confidence: 99%

Neuromorphic System for Spatial and Temporal Information Processing

Zyarah

Gómez

Kudithipudi

2020

IEEE Trans. Comput.

View full text Add to dashboard Cite

Neuromorphic systems that learn and predict from streaming inputs hold significant promise in pervasive edge computing and its applications. In this article, a neuromorphic system that processes spatio-temporal information on the edge is proposed. Algorithmically, the system is based on hierarchical temporal memory that inherently offers online learning, resiliency, and fault tolerance. Architecturally, it is a full custom mixed-signal design with an underlying digital communication scheme and analog computational modules. Therefore, the proposed system features reconfigurability, real-time processing, low power consumption, and low-latency processing. The proposed architecture is benchmarked to predict on real-world streaming data. The network's mean absolute percentage error on the mixed-signal system is 1.129 X lower compared to its baseline algorithm model. This reduction can be attributed to device non-idealities and probabilistic formation of synaptic connections. We demonstrate that the combined effect of Hebbian learning and network sparsity also plays a major role in extending the overall network lifespan. We also illustrate that the system offers 3.46 X reduction in latency and 77.02 X reduction in power consumption when compared to a custom CMOS digital design implemented at the same technology node. By employing specific low power techniques, such as clock gating, we observe 161.37 X reduction in power consumption.

show abstract

Fault tolerant adaptive write schemes for improving endurance and reliability of memristor memories

Cited by 13 publications

References 52 publications

To the Issue of the Memristor’s HRS and LRS States Degradation and Data Retention Time

To the Issue of the Memristor’s HRS and LRS States Degradation and Data Retention Time

Application of Memristors in Hardware Security: A Current State‐of‐the‐Art Technology

Neuromorphic System for Spatial and Temporal Information Processing

Contact Info

Product

Resources

About