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Design and Architectural Assessment of 3-D Resistive Memory Technologies in FPGAs

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Impact of Interface Traps in Floating-Gate Memory Based on Monolayer MoS2

Andras Kis, Guilherme Migliato Marega

Two-dimensional materials (2DMs) have found potential applications in many areas of electronics, such as sensing, memory systems, optoelectronics, and power. Despite an intense experimental work, the literature is lacking of accurate modeling of nonvolatil ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

Miss-Optimized Memory Systems: Turning Thousands of Outstanding Misses into Reuse Opportunities

Mikhail Asiatici

Even if Dennard scaling came to an end fifteen years ago, Moore's law kept fueling an exponential growth in compute performance through increased parallelization. However, the performance of memory and, in particular, Dynamic Random Access Memory (DRAM), ...

EPFL2021

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A random access memory having a memory array having a plurality of local memory groups, each local memory group including a plurality of bitcells arranged in a bitcell column, a pair of local bitlines operatively connected to the plurality of bitcells, a p ...

2021

Magnetic Skyrmions: From Fundamental Physics to Topological Electronics

Henrik Moodysson Rønnow, Dirk Grundler, Jonathan White

In Switzerland the National Science Foundation recently funded a network on Nano-Skyrmionics [https://skyrmions.epfl.ch] joining scientists from various institutions. Here, we provide a status report on selected forefront aspects of the research field. Thi ...

2020

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While Resistive Random Access Memories (RRAM) are perceived nowadays as a promising solution for the future of computing, these technologies suffer from intrinsic variability regarding programming voltage, switching speed and achieved resistance values. Wr ...

IEEE2020

The rise of data-intensive applications has increased the demand for high-density and low-power embedded memories. Among them, the gain-cell embedded DRAM (GC-eDRAM) is a suitable alternative to the static random access memory (SRAM) due to its high memory ...

IEEE2019

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The need for running complex Machine Learning (ML) algorithms, such as Convolutional Neural Networks (CNNs), in edge devices, which are highly constrained in terms of computing power and energy, makes it important to execute such applications efficiently. ...

2019

Material and Electrical study of HfO2-Based Resistive Random Access Memories (ReRAMs)

Behnoush Attarimashalkoubeh

Resistive Random Access Memories (ReRAMs) have been researched intensively in the last past decades as a promising alternatives technology for the next-generation non-volatile memory (NVM) devices. ReRAMâs excellent performance properties such as high sw ...

EPFL2019

Analog Control of Retainable Resistance Multistates in HfO2 Resistive-Switching Random Access Memories (ReRAMs)

Elmira Shahrabi, Yusuf Leblebici, Jury Sandrini, Carlo Ricciardi, Cecilia Giovinazzo, Oguz Tolga Celik

Resistive-switching random access memory (ReRAM) technologies are nowadays a good candidate to overcome the bottleneck of Von Neumann architectures, taking advantage of their logic-in-memory capability and the ability to mimic biological synapse behavior. ...

AMER CHEMICAL SOC2019

Post-P&R Performance and Power Analysis for RRAM-based FPGAs

Giovanni De Micheli, Pierre-Emmanuel Julien Marc Gaillardon, Xifan Tang, Edouard Giacomin

Resistive Random Access Memory (RRAM)-based FPGAs are predicted to outperform conventional FPGAs architectures in area, delay and power over a wide range of voltage operations, allowing novel energy-quality trade-offs for reconfigurable computing. The oppo ...

2018