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RRAM Crossbar Arrays for Storage Class Memory Applications : Throughput and Density Considerations

Related publications (41)

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Machine learning and data processing algorithms have been thriving in finding ways of processing and classifying information by exploiting the hidden trends of large datasets. Although these emerging computational methods have become successful in today's ...

EPFL2023

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

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

Memory chip or memory array for wide-voltage range in-memory computing using bitline technology

David Atienza Alonso, Marina Zapater Sancho, Marco Antonio Rios, William Andrew Simon

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

NVCache: A Plug-and-Play NVMM-based I/O Booster for Legacy Systems

Rafael Pereira Pires, Pascal Felber

This paper introduces NVCache, an approach that uses a non-volatile main memory (NVMM) as a write cache to improve the write performance of legacy applications. We compare NVCache against file systems tailored for NVMM (Ext4-DAX and NOVA) and with I/O-heav ...

IEEE2021

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Resistive switching memory technologies (RRAM) are seen by most of the scientific community as an enabler for Edge-level applications such as embedded deep Learning, AI or signal processing of audio and video signals. However, going beyond a "simple'' repl ...

IEEE2020

Perovskite Flash Memory with a Single-Layer Nanofloating Gate

Mohammad Khaja Nazeeruddin, Peng Gao, Hobeom Kim

Here we use triple-cation metal-organic halide perovskite single crystals for the transistor channel of a flash memory device. Moreover, we design and demonstrate a 10 nm thick single-layer nanofloating gate. It consists of a ternary blend of two organic s ...

2020

Bridging the Latency Gap between NVM and DRAM for Latency-bound Operations

Anastasia Ailamaki, Georgios Psaropoulos

Non-Volatile Memory (NVM) technologies exhibit 4× the read access latency of conventional DRAM. When the working set does not fit in the processor cache, this latency gap between DRAM and NVM leads to more than 2× runtime increase for queries dominated by ...

ACM2019

Fine-Grain Checkpointing with In-Cache-Line Logging

James Richard Larus, David Teksen Aksun, Nachshon Cohen

Non-Volatile Memory offers the possibility of implementing high-performance, durable data structures. However, achieving performance comparable to well-designed data structures in non-persistent (transient) memory is difficult, primarily because of the cos ...

ACM2019

Data-Retention-Time Characterization of Gain-Cell eDRAMs across the Design and Variations Space

Andreas Peter Burg, Andrea Bonetti

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