This paper presents an overview of emerging memory technologies. It begins with the presentation of stand-alone and embedded memory technology evolution, since the appearance of Flash memory in the 1980s. Then, the progress of emerging memory technol...
Polymer dielectric materials have recently attracted attention for their versatile applications in emerging electronic devices such as memory, field-effect transistors (FETs), and triboelectric nanogenerators (TENGs). This review highlights the advan...
Data-intensive workloads and applications, such as machine learning (ML), are fundamentally limited by traditional computing systems based on the von-Neumann architecture. As data movement operations and energy consumption become key bottlenecks in t...
The rapid growth of Deep Neural Networks (DNNs) has led to the development of application-specific DNN accelerators. Conventional 2D von Neumann architectures suffer from memory bandwidth limitations between the memory and the processing core. 3D DNN...
Due to a rapid increase in the amount of data, there is a huge demand for the development of new memory technologies as well as emerging computing systems for high-density memory storage and efficient computing. As the conventional transistor-based s...
Perovskite quantum dots (PVK QDs) are gaining significant attention as potential materials for next-generation memory devices leveraged by their ion dynamics, quantum confinement, optoelectronic synergy, bandgap tunability, and solution-processable f...
Processing systems are in continuous evolution thanks to the constant technological advancement and architectural progress. Over the years, computing systems have become more and more powerful, providing support for applications, such as Machine Lear...
As data movement operations and power-budget become key bottlenecks in the design of computing systems, the interest in unconventional approaches such as processing-in-memory (PIM), machine learning (ML), and especially neural network (NN)-based acce...
To enable the design of large capacity memory structures, novel memory technologies such as non-volatile memory (NVM) and novel fabrication approaches, e.g., 3D stacking and multi-level cell (MLC) design have been explored. The existing modeling tool...
The non-ideality aspects of phase change memory (PCM) such as drift and resistance variability can pose significant obstacles in neuromorphic hardware implementations. A unique drift and variability compensation strategy is demonstrated and implement...
The capability of multiple valued logic (MVL) circuits to achieve higher storage density when compared to that of existing binary circuits is highly impressive. Recently, MVL circuits have attracted significant attention for the design of digital sys...
Due to the difficulties associated with scaling of silicon transistors, various technologies beyond binary logic processing are actively being investigated. Ternary logic circuit implementation with carbon nanotube field effect transistors (CNTFETs)...
Emerging nonvolatile memory (eNVM) devices are pushing the limits of emerging applications beyond the scope of silicon-based complementary metal oxide semiconductors (CMOS). Among several alternatives, phase change memory, spin-transfer torque random...
Most modern CPU architectures are based on the von Neumann principle, where memory and processing units are separate entities. Although processing unit performance has improved over the years, memory capacity has not followed the same trend, creating...
As immersive technologies reshape how people experience identity, emotion, and loss, virtual memorialization is emerging as an important application of virtual reality. This study examines the psychological mechanisms influencing user intentions to e...
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, provid...
Phase Change Memory (PCM) has emerged as a promising non-volatile memory technology with significant applications in both edge computing and analog in-memory computing. This paper synthesizes recent research contributions on the use of PCM for smart...
To mitigate the environmental footprint of the aviation sector, this study proposes an integrated cascading biorefinery scheme to produce Sustainable Aviation Fuel (SAF) precursor bloodstock via enzymatic transesterification of coconut oil. Utilizing...
As the CMOS technology approaches its physical and economic limits, further advancement of Moore’s Law for enhanced computing performance can no longer rely solely on smaller transistors and higher integration density. Instead, the computing la...
The traditional computer architectures severely suffer from the bottleneck between the processing elements and memory that is the biggest barrier in front of their scalability. Nevertheless, the amount of data that applications need to process is inc...
Facing the era of information explosion and the advent of artificial intelligence, there is a growing demand for information technologies with huge storage capacity and efficient computer processing. However, traditional silicon-based storage and com...
Technology scaling has led to an increase in density and capacity of on-chip caches. This has enabled higher throughput by enabling more low latency memory transfers. With the reduction in size of SRAMs and development of emerging technologies, e.g.,...
NAND Flash memories have gained tremendous attention owing to the increasing demand for storage capacity. This implies that NAND cells need to scale continuously to maintain the pace of technological evolution. Even though NAND Flash memory technolog...
This new Special Issue of Materials entitled “3D/4D Printing Application for Shape Memory Materials” aims to publish original and review papers dealing with basic and applied research on this emerging technology [...]
24 November 2021
Computational methods in memory array are being researched in many emerging memory technologies to conquer the ‘von Neumann bottleneck’. Resistive RAM (ReRAM) is a non-volatile memory, which supports Boolean logic operation, and adders ca...
Computer memory comprises temporarily or permanently stored data and instructions, which are utilized in electronic digital computers. The opposite of serial access memory is Random Access Memory (RAM), where the memory is accessed immediately for bo...
Shape-memory polymers are outstanding “smart” materials, which can perform important geometrical changes, when activated by several types of external stimuli, and which can be applied to several emerging engineering fields, from aerospace application...
24 September 2020
Due to the amount of data involved in emerging deep learning and big data applications, operations related to data movement have quickly become a bottleneck. Data-centric computing (DCC), as enabled by processing-in-memory (PIM) and near-memory proce...
From self-driving cars to detecting cancer, the applications of modern artificial intelligence (AI) rely primarily on deep neural networks (DNNs). Given raw sensory data, DNNs are able to extract high-level features after the network has been trained...
The increasing growth in knowledge about the functioning of the nervous system of mammals and humans, as well as the significant neuromorphic technology developments in recent decades, has led to the emergence of a large number of brain–compute...
A significant rise in the adoption of streaming applications has changed the decision-making processes in the last decade. This movement has led to the emergence of several Big Data technologies for in-memory processing, such as the systems Apache St...
The rapid expansion of data has made global access easier, but it also demands increasing amounts of energy for data storage and processing. In response, neuromorphic electronics, inspired by the functionality of biological neurons and synapses, have...
Fear memory is a critical adaptive process that enables organisms to avoid potential threats and survive in complex environments. Traditionally viewed as a neuronal phenomenon, emerging evidence has demonstrated that astrocytes play a fundamental rol...
Memristor devices for resistive-switching memory and artificial synapses have emerged as promising solutions for overcoming the technological challenges associated with the von Neumann bottleneck. Recently, due to their unique optoelectronic properti...
Digitization is changing our world, creating innovative finance channels and emerging technology such as cryptocurrencies, which are applications of blockchain technology. However, cryptocurrency price volatility is one of this technology’s mai...
Temporal (race) computing schemes rely on temporal memories, where information is represented with the timing of signal edges. Standard digital circuit techniques can be used to capture the relative timing characteristics of signal edges. However, th...
Modern computer applications have become highly data-intensive, giving rise to an increase in data traffic between the processor and memory units. Computing-in-Memory (CiM) has shown great promise as a solution to this aptly named von Neumann bottlen...
Recent progress in the development of artificial intelligence technologies, aided by deep learning algorithms, has led to an unprecedented revolution in neuromorphic circuits, bringing us ever closer to brain-like computers. However, the vast majorit...
Arc fault is the dominant cause of fire in photovoltaic (PV) systems, making its accurate identification crucial for PV fire prevention. This study investigates the influence of voltage (200, 300, and 400 V) and current (3, 5, 7, 9, and 11 A) on the...
The emerging resistive switching devices have attracted broad interest as promising candidates for future memory and computing applications. Particularly, it is believed that memristor-based neuromorphic engineering promises to enable efficient artif...
This paper presents a land area measuring instrument based on an STM32 microcontroller (STMicroelectronics, Paris, France) and a BeiDou positioning chip (Zhongke Microelectronics, Hangzhou, China). The system employs BeiDou navigation as the core pos...
Computing data-intensive applications on the von Neumann architecture lead to significant performance and energy overheads. The concept of computation in memory (CiM) addresses the bottleneck of von Neumann machines by reducing the data movement in t...
Shape Memory Alloys (SMAs) have emerged as a promising actuation technology for wearable rehabilitation robots due to their unique properties, including the shape memory effect, high actuation stress, pseudoelasticity, and three-dimensional actuation...
Immersive technologies such as augmented reality (AR) and virtual reality (VR) have emerged as powerful tools in cultural heritage education and preservation. Building on prior work that demonstrated the effectiveness of gamified XR applications in e...
24 September 2021
Several promising non-volatile memories (NVMs) such as magnetic RAM (MRAM), spin-transfer torque RAM (STTRAM), ferroelectric RAM (FeRAM), resistive RAM (RRAM), and phase-change memory (PCM) are being investigated to keep the static leakage within a t...
This comprehensive survey explores recent advancements in scheduling techniques for efficient deep learning computations on GPUs. The article highlights challenges related to parallel thread execution, resource utilization, and memory latency in GPUs...
The increasing demand for high-performance and low-power hardware in artificial intelligence (AI) applications—such as speech recognition, facial recognition, and object detection—has driven the exploration of advanced memory designs. Con...
The von Neumann architecture is no longer sufficient for handling large-scale data. In-memory computing has emerged as the potent method for breaking through the memory bottleneck. A new 10T SRAM bitcell with row and column control lines called RC-SR...
With advances in science and technology and changes in industry, research on promising future technologies has emerged as important. Furthermore, with the advent of a ubiquitous and smart environment, governments and enterprises are required to predi...
Cloudlet networks are an emerging distributed data processing paradigm, which contain multiple cloudlets deployed beside base stations to serve local user devices (UDs). Each cloudlet is a small data center with limited memory, in which multiple virt...
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