Results 41 to 50 of about 14,870,547 (146)
Electroforming‐free, self‐rectifying switching with polarity‐dependent threshold modulation is realized in selector‐only memory through Cu‐ion migration in a bilayer stacked dual functional materials. Ultrafast rupturing of Cu filament enables drift‐free operation with high stability.
Jae‐Kyeong Kim +7 more
wiley +1 more source
Resistive Random Access Memory (ReRAM) is an emerging class of non-volatile memory that stores data by altering the resistance of a material within a memory cell.
Adiba Adiba +2 more
doaj +1 more source
Low‐Power Control Of Resistance Switching Transitions in First‐Order Memristors
Joule losses are a serious concern in modern integrated circuit design. In this regard, minimizing the energy necessary for programming memristors should be handled with care. This manuscript presents an optimal control framework, allowing to derive energy‐efficient programming voltage protocols for resistance switching devices. Following this approach,
Valeriy A. Slipko +3 more
wiley +1 more source
Reliability and Performance Optimization of Resistive Random-Access Memory Devices for Advanced Computing and Memory Applications [PDF]
Current trends towards more efficient computing include alternatives to the standard von Neumann architecture and a trend towards in-memory computing with non-volatile memory (NVM) arrays.
Liehr, Maximilian
core
Characterization and Modeling of Multilevel Analog ReRAM Synapses in the Sky130 Process
Nonvolatile memory devices play a key role in enabling energy-efficient computing. Among them, analog nonvolatile memories such as resistive random access memory (ReRAM) offer high density and low power compared to conventional digital memories. However,
Irem Didin +3 more
doaj +1 more source
Emerging Memory and Device Technologies for Hardware‐Accelerated Model Training and Inference
This review investigates the suitability of various emerging memory technologies as compute‐in‐memory hardware for artificial intelligence (AI) applications. Distinct requirements for training‐ and inference‐centric computing are discussed, spanning device physics, materials, and system integration.
Yoonho Cho +6 more
wiley +1 more source
The dependence of reactive metal layer on resistive switching characteristics is investigated in a bi-layer structural Ta/HfOx filament type resistive random access memory (ReRAM).
Hwang, H +5 more
core +1 more source
Application of Resistive Random Access Memory (RRAM) For Non-Von Neumann Computing [PDF]
The movement of data between physically separated memory and processing units in conventional computing systems (the so-called von Neumann architecture) incurs significant costs in energy and latency. This is known as the von Neumann bottleneck. With the
Rafiq, Sarah
core
Multilevel Cell Storage and Resistance Variability in Resistive Random Access Memory
Multilevel per cell (MLC) storage in resistive random access memory (ReRAM) is attractive in achieving high-density and low-cost memory and will be required in future.
Prakash A., Hyunsang Hwang
core +1 more source
Resistive Random-Access Memory (ReRAM) is a promising technology for next-generation non-volatile memory and neuromorphic computing due to its scalability, low power consumption, and rapid switching.
Rajib Sutradhar +5 more
doaj +1 more source

