Publications associées à Multiplieur-accumulateur

Multiplier Architectures: Challenges and Opportunities with Plasmonic-based Logic

Giovanni De Micheli, Mathias Soeken, Eleonora Testa, Odysseas Zografos

Emerging technologies such as plasmonics and photonics are promising alternatives to CMOS for high throughput applications, thanks to their waveguide's low power consumption and high speed of computation. Besides these qualities, these novel technologies a ...

2020

Multiplier Architectures: Challenges and Opportunities with Plasmonic-based Logic

Giovanni De Micheli, Mathias Soeken, Eleonora Testa, Odysseas Zografos

Emerging technologies such as plasmonics and photonics are promising alternatives to CMOS for high throughput applications, thanks to their waveguide's low power consumption and high speed of computation. Besides these qualities, these novel technologies a ...

IEEE2020

Side-channel attacks on SIKE

Natacha Yolande Emmanuel Marie Linard de Guertechin

This thesis presents, firstly, an introduction to the current state of the art in isogeny-based cryptography, and secondly, a side-channel differential power analysis of SIKE—an isogeny-based key exchange algorithm—in semi-static mode. These attacks have b ...

2020

Blade: An in-Cache Computing Architecture for Edge Devices

David Atienza Alonso, Marina Zapater Sancho, Alexandre Sébastien Julien Levisse, Marco Antonio Rios, William Andrew Simon, Yasir Mahmood Qureshi

Area and power constrained edge devices are increasingly utilized to perform compute intensive workloads, necessitating increasingly area and power efficient accelerators. In this context, in-SRAM computing performs hundreds of parallel operations on spati ...

2020

Review and Benchmarking of Precision-Scalable Multiply-Accumulate Unit Architectures for Embedded Neural-Network Processing

Christian Enz, Vincent Frédéric Camus

The current trend for deep learning has come with an enormous computational need for billions of Multiply-Accumulate (MAC) operations per inference. Fortunately, reduced precision has demonstrated large benefits with low impact on accuracy, paving the way ...

2019

Survey of Precision-Scalable Multiply-Accumulate Units for Neural-Network Processing

Christian Enz, Vincent Frédéric Camus

The current trend for deep learning has come with an enormous computational need for billions of Multiply-Accumulate (MAC) operations per inference. Fortunately, reduced precision has demonstrated large benefits with low impact on accuracy, paving the way ...

IEEE2019

Design of approximate and precision-scalable circuits for embedded multimedia and neural-network processing

Vincent Frédéric Camus

Density, speed and energy efficiency of integrated circuits have been increasing exponentially for the last four decades following Moore's law. However, power and reliability pose several challenges to the future of technology scaling. Approximate computin ...

EPFL2019

Inner-Loop-Free ADMM for Cryo-EM

Michaël Unser, Laurène Donati, Emmanuel Emilien Louis Soubies

Thanks to recent advances in signal processing, the interest for fast ℓ1-regularized reconstruction algorithms in cryo-electron microscopy (cryo-EM) has intensified. The approaches based on the alternating-direction of multipliers method (ADMM) are particu ...

IEEE2019

An Associativity-Agnostic in-Cache Computing Architecture Optimized for Multiplication

David Atienza Alonso, Marina Zapater Sancho, Alexandre Sébastien Julien Levisse, Marco Antonio Rios, William Andrew Simon

With the spread of cloud services and Internet of Things concept, there is a popularization of machine learning and artificial intelligence based analytics in our everyday life. However, an efficient deployment of these data-intensive services requires per ...

2019

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

Giorgio Cristiano, Massimo Giordano

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

Multiplieur-accumulateur

Multiplier Architectures: Challenges and Opportunities with Plasmonic-based Logic

Multiplier Architectures: Challenges and Opportunities with Plasmonic-based Logic

Side-channel attacks on SIKE

Blade: An in-Cache Computing Architecture for Edge Devices

Review and Benchmarking of Precision-Scalable Multiply-Accumulate Unit Architectures for Embedded Neural-Network Processing

Survey of Precision-Scalable Multiply-Accumulate Units for Neural-Network Processing

Design of approximate and precision-scalable circuits for embedded multimedia and neural-network processing

Inner-Loop-Free ADMM for Cryo-EM

An Associativity-Agnostic in-Cache Computing Architecture Optimized for Multiplication

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

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Multiplier Architectures: Challenges and Opportunities with Plasmonic-based Logic

Design of approximate and precision-scalable circuits for embedded multimedia and neural-network processing

Blade: An in-Cache Computing Architecture for Edge Devices

Side-channel attacks on SIKE

Multiplier Architectures: Challenges and Opportunities with Plasmonic-based Logic

Inner-Loop-Free ADMM for Cryo-EM

Review and Benchmarking of Precision-Scalable Multiply-Accumulate Unit Architectures for Embedded Neural-Network Processing

An Associativity-Agnostic in-Cache Computing Architecture Optimized for Multiplication

Survey of Precision-Scalable Multiply-Accumulate Units for Neural-Network Processing

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