Publications associées à Control of Resistive Switching in Mott Memories Based on TiN/AM4Q8/TiN MIM Devices

2D Nanosystems: Applications of 2D Semiconductors for In-Memory Computing

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

Exploring ferroelectricity in HfO2-based thin films by tackling application-relevant challenges

Matteo Cavalieri

Ferroelectric materials offer a broad range of application-relevant properties, including spontaneous polarization switchable by electric field. Archetypical representatives of this class of materials are perovskites, currently used in applications ranging ...

EPFL2021

Accurate deep neural network inference using computational phase-change memory

Irem Boybat Kara, Abu Sebastian, Evangelos Eleftheriou

In-memory computing using resistive memory devices is a promising non-von Neumann approach for making energy-efficient deep learning inference hardware. However, due to device variability and noise, the network needs to be trained in a specific way so that ...

Nature Research2020

Accurate Emulation of Memristive Crossbar Arrays for In-Memory Computing

Irem Boybat Kara, Evangelos Eleftheriou

In-memory computing is an emerging non-von Neumann computing paradigm where certain computational tasks are performed in memory by exploiting the physical attributes of the memory devices. Memristive devices such as phase-change memory (PCM), where informa ...

IEEE2020

Distributed Computing with Modern Shared Memory

Mihail Igor Zablotchi

In this thesis, we revisit classic problems in shared-memory distributed computing through the lenses of (1) emerging hardware technologies and (2) changing requirements. Our contributions consist, on the one hand, in providing a better understanding of th ...

EPFL2020

Write Termination circuits for RRAM : A Holistic Approach From Technology to Application Considerations

David Atienza Alonso, Alexandre Sébastien Julien Levisse, Marco Antonio Rios

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

Generalized Synthesis to Produce Transparent Thin Films of Ternary Metal Oxide Photoelectrodes

Kevin Sivula, Nestor Guijarro Carratala, Liang Yao, Florent Alexandre Boudoire, Charles Roger Jean Lhermitte, Annalisa Polo

Developing facile approaches to prepare non-light-scattering ternary oxide thin film photoelectrodes is an important goal for solar water splitting tandem cells. Herein, a novel synthesis route is reported that employs ethylenediaminetetraacetic acid (EDTA ...

WILEY-V C H VERLAG GMBH2020

Multi-memristive synaptic architectures for training neural networks

Irem Boybat Kara

Highly data-centric AI workloads require that new computing paradigms be adopted because the performance of traditional CPU- and GPU-based systems are limited by data access and transfer. Training deep neural networks with millions of tunable parameters ta ...

EPFL2020

Exploration Methodology for BTI-Induced Failures on RRAM-Based Edge AI Systems

David Atienza Alonso, Miguel Peon Quiros, Alexandre Sébastien Julien Levisse, Marco Antonio Rios

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

Bridging the p-type transparent conductive materials gap: synthesis approaches for disperse valence band materials

Monica Morales Masis, Angela Nicole Fioretti

Transparent conductive materials (TCMs) with high p-type conductivity and broadband transparency have remained elusive for years. Despite decades of research, no p-type material has yet been found to match the performance of n-type TCMs. If developed, the ...

2020

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. ReRAMâ s excellent performance properties such as high sw ...

EPFL2019

Switching event detection and self-termination programming circuit for energy efficient ReRAM memory arrays

Etienne Nowak, Alexandre Sébastien Julien Levisse

Energy efficiency remains a challenge for the design of non-volatile resistive memories (ReRAMs) arrays. This memory technology suffers from intrinsic variability in switching speed, programming voltages and resistance levels. The programming conditions of ...

2019

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

Yusuf Leblebici, Jury Sandrini, Elmira Shahrabi, 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

ReRAM From Material Study to CMOS Co-integration

Elmira Shahrabi

The revolution of information-technology owes to silicon-based complementary-metal-oxide (CMOS) technology. However, CMOS technology approaches its physical limitation hardening the further progress of memory devices as well as computing paradigm requiring ...

EPFL2019

A Product Engine for Energy-Efficient Execution of Binary Neural Networks Using Resistive Memories

David Atienza Alonso, Xifan Tang, Pierre-Emmanuel Julien Marc Gaillardon, Edouard Giacomin, Marina Zapater Sancho, Yasir Mahmood Qureshi, João Miguel Morgado Pereira Vieira

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

Performance improvement of chip-level CMOS-integrated ReRAM cells through material optimization

Yusuf Leblebici, Thomas La Grange, Elmira Shahrabi, Tugba Demirci

The integration of the resistive random access memory (ReRAM) with CMOS logic circuitry provides a solution to scaling limitations, and offers promising candidates for use in next generation computing applications. It is challenging to realize a reliable, ...

ELSEVIER SCIENCE BV2019

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

Impact of the Oxygen Content on the Optoelectronic Properties of the Indium-Tin-Oxide Based Transparent Electrodes for Silicon Heterojunction Solar Cells

Christophe Ballif, Akshath Raghu Shetty, Mathieu Gérard Boccard, Jean Cattin, Jan Haschke, Brahim Aissa

Amorphous/crystalline silicon heterojunction (SHJ) solar cells technology is attracting tremendous attention in recent years due to its potential to achieve high power conversion efficiencies at low fabrication temperatures and using few process steps. How ...

AMER INST PHYSICS2019

Perspective on training fully connected networks with resistive memories: Device requirements for multiple conductances of varying significance

Massimo Giordano, Giorgio Cristiano

Novel Deep Neural Network (DNN) accelerators based on crossbar arrays of non-volatile memories (NVMs)-such as Phase-Change Memory or Resistive Memory-can implement multiply-accumulate operations in a highly parallelized fashion. In such systems, computatio ...

2018

Resistive Switching Memory Architecture Based on Polarity Controllable Selectors

Pierre-Emmanuel Julien Marc Gaillardon, Alexandre Sébastien Julien Levisse

With the continuous scaling of CMOS technology, integrating an embedded high-density non-volatile memory appears to be more and more costly and technologically challenging. Beyond floating-gate memory technologies, bipolar resistive random access memories ...

2018