Concept

Quadruple-precision floating-point format

Publications associées (136)

Smooth Power Direction Transition of a Bidirectional LLC Resonant Converter for DC Transformer Applications

The bidirectional LLC resonant converter operated at fixed switching frequency is a preferable candidate for a true dc transformer that does not actively control the power flow. This is due to its naturally stiff voltage ratio regardless of the imposed loa ...

2020

High Precision Capacitive Moisture Sensor for Polymers: Modeling and Experiments

Marco Mattavelli, Jean-Michel Sallese, Catherine Dehollain, Diego Ruben Barrettino

In this work a high precision capacitive moisture sensor for polymers was designed and fabricated. The device is part of a compact, fast, and economic moisture analyzer capable of reaching a similar precision than commercial moisture analyzers based on the ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

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

Self-Binarizing Networks

Sabine Süsstrunk, Radhakrishna Achanta, Fayez Lahoud, Pablo Marquez Neila

We present a method to train self-binarizing neural networks, that is, networks that evolve their weights and activations during training to become binary. To obtain similar binary networks, existing methods rely on the sign activation function. This funct ...

arXiv2019

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

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

Christian Enz, Vincent Frédéric Camus

2019

Multi-ReRAM synapses for artificial neural network training

Elmira Shahrabi, Igor Krawczuk, Yusuf Leblebici, Irem Boybat Kara, Carlo Ricciardi, Cecilia Giovinazzo, Evangelos Eleftheriou, Abu Sebastian

Metal-oxide-based resistive memory devices (ReRAM) are being actively researched as synaptic elements of neuromorphic co-processors for training deep neural networks (DNNs). However, device-level non-idealities are posing significant challenges. In this wo ...

IEEE2019

Advanced Machine Learning Techniques for Self-Interference Cancellation in Full-Duplex Radios

Andreas Peter Burg, Andreas Toftegaard Kristensen

In-band full-duplex systems allow for more efficient use of temporal and spectral resources by transmitting and receiving information at the same time and on the same frequency. However, this creates a strong self-interference signal at the receiver, makin ...

IEEE2019

Evaluating Charge Equilibration Methods To Generate Electrostatic Fields in Nanoporous Materials

Berend Smit, Daniele Ongari, Peter George Boyd, Amber Kashan Mace, Özge Kadioglu

Charge equilibration (Qeq) methods can estimate the electrostatic potential of molecules and periodic frameworks by assigning point charges to each atom, using only a small fraction of the resources needed to compute density functional (DFT)-derived charge ...

2019

Interactive Generation of Calligraphic Trajectories from Gaussian Mixtures

Sylvain Calinon

The chapter presents an approach for the interactive definition of curves and motion paths based on Gaussian mixture model (GMM) and optimal control. The input of our method is a mixture of multivariate Gaussians defined by the user, whose centers define a ...

Springer2019

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