scholarly journals Parallel Computing of Graph-based Functions in ReRAM

2022 ◽  
Vol 18 (2) ◽  
pp. 1-24
Author(s):  
Saman Froehlich ◽  
Saeideh Shirinzadeh ◽  
Rolf Drechsler
Keyword(s):  
Parallel Computing ◽  
Boolean Functions ◽  
State Of The Art ◽  
Random Access ◽  
Resistive Random Access Memory ◽  
Computer Architectures ◽  
Non Volatile Memory ◽  
Promising Solution ◽  
High Scalability ◽  
Memory Bottleneck

Resistive Random Access Memory (ReRAM) is an emerging non-volatile memory technology. Besides its low power consumption and its high scalability, its inherent computation capabilities make ReRAM especially interesting for future computer architectures. Merging computations into the memory is a promising solution for overcoming the memory bottleneck. To perform computations in ReRAM, efficient synthesis strategies for Boolean functions have to be developed. In this article, we give a thorough presentation of how to employ parallel computing capabilities of ReRAM for the synthesis of functions given state-of-the-art graph-based representations AIGs or BDDs. Additionally, we introduce a new graph-based representation called m-And-Inverter Graph (m-AIGs), which allows us to fully exploit the computing capabilities of ReRAM. In the simulations, we show that our proposed approaches outperform state-of-the art synthesis strategies, and we show the superiority of m-AIGs over the standard AIG representation for ReRAM-based synthesis.

scholarly journals Overview of radiation effects on emerging non-volatile memory technologies

2017 ◽  
Vol 32 (4) ◽  
pp. 381-392
Author(s):  
Irfan Fetahovic ◽  
Edin Dolicanin ◽  
Djordje Lazarevic ◽  
Boris Loncar
Keyword(s):  
Radiation Effects ◽  
Random Access ◽  
Random Access Memory ◽  
Resistive Random Access Memory ◽  
Access Memory ◽  
High Radiation ◽  
Different Types ◽  
Non Volatile Memory ◽  
Volatile Memory ◽  
Change Memory

In this paper we give an overview of radiation effects in emergent, non-volatile memory technologies. Investigations into radiation hardness of resistive random access memory, ferroelectric random access memory, magneto-resistive random access memory, and phase change memory are presented in cases where these memory devices were subjected to different types of radiation. The obtained results proved high radiation tolerance of studied devices making them good candidates for application in radiation-intensive environments.

scholarly journals Effect of Annealing Environment on the Performance of Sol–Gel-Processed ZrO2 RRAM

Electronics ◽  
2019 ◽  
Vol 8 (9) ◽  
pp. 947 ◽  
Author(s):  
Seunghyun Ha ◽  
Hyunjae Lee ◽  
Won-Yong Lee ◽  
Bongho Jang ◽  
Hyuk-Jun Kwon ◽  
...  
Keyword(s):  
Sol Gel ◽  
Random Access ◽  
High Resistance State ◽  
Resistive Random Access Memory ◽  
Access Memory ◽  
Environment Effect ◽  
Bipolar Switching ◽  
Non Volatile Memory ◽  
Retention Characteristics ◽  
Resistance State

We investigate the annealing environment effect on ZrO2-based resistive random-access memory (RRAM) devices. Fabricated devices exhibited conventional bipolar-switching memory properties. In particular, the vacuum-annealed ZrO2 films exhibited larger crystallinity and grain size, denser film, and a relatively small quantity of oxygen vacancies compared with the films annealed in air and N2. These led to a decrease in the leakage current and an increase in the resistance ratio of the high-resistance state (HRS)/low-resistance state (LRS) and successfully improved non-volatile memory properties, such as endurance and retention characteristics. The HRS and LRS values were found to last for 104 s without any significant degradation.

Influence of near-surface and volume real structure on the electronic properties of SrTiO3 MIM structures

2011 ◽  
Vol 1368 ◽  
Author(s):  
J. Seibt ◽  
F. Hanzig ◽  
R. Strohmeyer ◽  
H. Stoecker ◽  
C. Himcinschi ◽  
...  
Keyword(s):  
Transition Metal Oxides ◽  
High Vacuum ◽  
Random Access ◽  
Resistive Random Access Memory ◽  
Real Structure ◽  
Near Surface ◽  
Metal Insulator Metal ◽  
Non Volatile Memory ◽  
Perovskite Type

ABSTRACTPerovskite-type transition metal oxides have great potential as storage material in resistive random-access memory (RRAM) devices. Typical non-volatile memory cells are realized in metal-insulator-metal (MIM) stacks with insulator thicknesses of few nanometers. We report on the investigation of single-crystal SrTiO3 to understand the role of volume and interface real structure for the electrical conductivity in such materials. Conductivity in SrTiO3 single crystals was established by a reducing high vacuum (HV) annealing introducing charged oxygen vacancies acting as donor centers. Titanium electrodes are evaporated on both crystal faces to obtain an MIM element.

Organic small molecule-based RRAM for data storage and neuromorphic computing

2020 ◽  
Vol 8 (37) ◽  
pp. 12714-12738 ◽  
Author(s):  
Boyuan Mu ◽  
Hsiao-Hsuan Hsu ◽  
Chi-Ching Kuo ◽  
Su-Ting Han ◽  
Ye Zhou
Keyword(s):  
Small Molecules ◽  
Data Storage ◽  
Small Molecule ◽  
State Of The Art ◽  
Random Access ◽  
Random Access Memory ◽  
Resistive Random Access Memory ◽  
Memory Devices ◽  
Access Memory ◽  
Neuromorphic Computing

Recent state-of-the-art developments related to organic small molecules for resistive random-access memory devices has been emphasized.

scholarly journals Energy-Efficient Non-Von Neumann Computing Architecture Supporting Multiple Computing Paradigms for Logic and Binarized Neural Networks

2021 ◽  
Vol 11 (3) ◽  
pp. 29
Author(s):  
Tommaso Zanotti ◽  
Francesco Maria Puglisi ◽  
Paolo Pavan
Keyword(s):  
Neural Networks ◽  
High Performance ◽  
Random Access ◽  
Resistive Random Access Memory ◽  
Hardware Accelerators ◽  
Memory Architecture ◽  
Ultra Low Power ◽  
Von Neumann ◽  
Non Volatile Memory ◽  
Volatile Memory

Different in-memory computing paradigms enabled by emerging non-volatile memory technologies are promising solutions for the development of ultra-low-power hardware for edge computing. Among these, SIMPLY, a smart logic-in-memory architecture, provides high reconfigurability and enables the in-memory computation of both logic operations and binarized neural networks (BNNs) inference. However, operation-specific hardware accelerators can result in better performance for a particular task, such as the analog computation of the multiply and accumulate operation for BNN inference, but lack reconfigurability. Nonetheless, a solution providing the flexibility of SIMPLY while also achieving the high performance of BNN-specific analog hardware accelerators is missing. In this work, we propose a novel in-memory architecture based on 1T1R crossbar arrays, which enables the coexistence on the same crossbar array of both SIMPLY computing paradigm and the analog acceleration of the multiply and accumulate operation for BNN inference. We also highlight the main design tradeoffs and opportunities enabled by different emerging non-volatile memory technologies. Finally, by using a physics-based Resistive Random Access Memory (RRAM) compact model calibrated on data from the literature, we show that the proposed architecture improves the energy delay product by >103 times when performing a BNN inference task with respect to a SIMPLY implementation.

scholarly journals Memristive Non-Volatile Memory Based on Graphene Materials

Micromachines ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 341 ◽  
Author(s):  
Zongjie Shen ◽  
Chun Zhao ◽  
Yanfei Qi ◽  
Ivona Z. Mitrovic ◽  
Li Yang ◽  
...  
Keyword(s):  
Resistive Switching ◽  
Large Scale ◽  
Surface Effect ◽  
Random Access ◽  
Resistive Random Access Memory ◽  
Atomic Diffusion ◽  
Promising Alternative ◽  
Operation Speed ◽  
Non Volatile Memory ◽  
Volatile Memory

Resistive random access memory (RRAM), which is considered as one of the most promising next-generation non-volatile memory (NVM) devices and a representative of memristor technologies, demonstrated great potential in acting as an artificial synapse in the industry of neuromorphic systems and artificial intelligence (AI), due its advantages such as fast operation speed, low power consumption, and high device density. Graphene and related materials (GRMs), especially graphene oxide (GO), acting as active materials for RRAM devices, are considered as a promising alternative to other materials including metal oxides and perovskite materials. Herein, an overview of GRM-based RRAM devices is provided, with discussion about the properties of GRMs, main operation mechanisms for resistive switching (RS) behavior, figure of merit (FoM) summary, and prospect extension of GRM-based RRAM devices. With excellent physical and chemical advantages like intrinsic Young’s modulus (1.0 TPa), good tensile strength (130 GPa), excellent carrier mobility (2.0 × 105 cm2∙V−1∙s−1), and high thermal (5000 Wm−1∙K−1) and superior electrical conductivity (1.0 × 106 S∙m−1), GRMs can act as electrodes and resistive switching media in RRAM devices. In addition, the GRM-based interface between electrode and dielectric can have an effect on atomic diffusion limitation in dielectric and surface effect suppression. Immense amounts of concrete research indicate that GRMs might play a significant role in promoting the large-scale commercialization possibility of RRAM devices.

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