Publications associées à A Low-power Carry Cut-Back Approximate Adder with Fixed-point Implementation and Floating-point Precision

Publications associées (30)

Towards General-Purpose Decentralized Computing with Permissionless Extensibility

Smart contracts have emerged as the most promising foundations for applications of the blockchain technology. Even though smart contracts are expected to serve as the backbone of the next-generation web, they have several limitations that hinder their wide ...

EPFL2024

Functional-Basis Analysis of Non-Stationary Signals in Modern Power Grids: Theory and Implementation in Embedded Systems

Alexandra Cameron Karpilow

Situational awareness strategies are essential for the reliable and secure operation of the electric power grid which represents critical infrastructure in modern society. With the rise of converter-interfaced renewable generation and the consequent shift ...

EPFL2024

A 16-bit Floating-Point Near-SRAM Architecture for Low-power Sparse Matrix-Vector Multiplication

David Atienza Alonso, Giovanni Ansaloni, Marco Antonio Rios, Grégoire Axel Eggermann

State-of-the-art Artificial Intelligence (AI) algorithms, such as graph neural networks and recommendation systems, require floating-point computation of very large matrix multiplications over sparse data. Their execution in resource-constrained scenarios, ...

New York2023

Overflow-free compute memories for edge AI acceleration

David Atienza Alonso, Giovanni Ansaloni, Alexandre Sébastien Julien Levisse, Flavio Ponzina, Marco Antonio Rios

Compute memories are memory arrays augmented with dedicated logic to support arithmetic. They support the efficient execution of data-centric computing patterns, such as those characterizing Artificial Intelligence (AI) algorithms. These architectures can ...

2023

Efficient Lung Nodule Detection via 3D Deep Learning with Shifted Convolutions

Jiancheng Yang

The high computational costs of deep convolutional neural networks hinder their deployment in real-world applications, including pulmonary nodule detection from CT scans where large 3D image sizes amplify the issue. This paper presents a novel 3D method to ...

IEEE2023

Non-contact robotic manipulation of floating objects: exploiting emergent limit cycles

Josephine Anna Eleanor Hughes, Nana Obayashi

The study of non-contact manipulation in water, and the ability to robotically control floating objects has gained recent attention due to wide-ranging potential applications, including the analysis of plastic pollution in the oceans and the optimization o ...

Frontiers Media Sa2023

Performance investigation of cameras using HDR sensors for daylight glare evaluations

Jan Wienold, Geraldine Cai Ting Quek, Dong Hyun Kim

This study presents a novel framework for evaluating the luminance measurement capabilities of High Dynamic Range (HDR) sensor cameras in indoor glare conditions. Results indicate that the practical usage range of the CSEM VIP camera is significantly lower ...

International Commission on Illumination2023

DIET Controller: Dynamic Indoor Environment using Deep Reinforcement Learning

Arnab Chatterjee

Heating, Ventilation, and Air Conditioning (HVAC) Systems utilize much energy, accounting for 40% of total building energy use. The temperatures in buildings are commonly held within narrow limits, leading to higher energy use. Measurements from office bui ...

EPFL2023

Intelligent RF System for Ultra Low Power Spectrum Sensing with Machine Learning

Naci Pekçokgüler

The crowdedness of the RF spectrum constitutes problems in communication, however it also accommodates large amount of useful information. This information can be used to determine existing signals and operating contexts. However, spectrum condition varies ...

EPFL2024

Efficacy of temporal and spatial abstraction for training accurate machine learning models: A case study in smart thermostats

Rachid Guerraoui, Alexandre David Olivier Maurer

Smart thermostats are increasingly popular in homes and buildings as they improve occupant comfort, lower energy use in heating and cooling systems, and reduce utility bills by automatically adjusting room temperature according to measurements of their bui ...

ELSEVIER SCIENCE SA2023

A modelling framework for modern heritage buildings energy simulation

Franz Graf, Giulia Marino, Giuseppe Galbiati

The latest European polices highlight the urgent need to rehabilitate the existing building stock, responsible for 40 % of the EU's total energy consumption. In this process, a key role is played by thermal simulations, assessing the effective energy perfo ...

Elsevier2023

Endogenous Energy Efficiency Improvement in Housing and Cement Sectors in Switzerland

Sergey Arzoyan

The reduction of energy consumption in the residential building stock and cement industry is a substantial component of the Swiss Energy Strategy 2050. Therefore, it is vital to identify the potential for EEI in these two sectors. In this study, a new meth ...

EPFL2023

Low-Power Artificial Neural Network Perceptron Based on Monolayer MoS2

Aleksandra Radenovic, Andras Kis, Zhenyu Wang, Mukesh Kumar Tripathi, Guilherme Migliato Marega

Machine learning and signal processing on the edge are poised to influence our everyday lives with devices that will learn and infer from data generated by smart sensors and other devices for the Internet of Things. The next leap toward ubiquitous electron ...

2022

TimeEvolver: A program for time evolution with improved error bound

Sebastian Zell

We present TimeEvolver, a program for computing time evolution in a generic quantum system. It relies on well-known Krylov subspace techniques to tackle the problem of multiplying the exponential of a large sparse matrix iH, where His the Hamiltonian, with ...

ELSEVIER2022

Adaptive R-Peak Detection on Wearable ECG Sensors for High-Intensity Exercise

David Atienza Alonso, Grégoire Millet, Tomas Teijeiro Campo, Elisabetta De Giovanni

Objective: Continuous monitoring of biosignals via wearable sensors has quickly expanded in the medical and wellness fields. At rest, automatic detection of vital parameters is generally accurate. However, in conditions such as high-intensity exercise, sud ...

2022

Robust Binary Models by Pruning Randomly-initialized Networks

Sabine Süsstrunk, Mathieu Salzmann, Chen Liu

Robustness to adversarial attacks was shown to require a larger model capacity, and thus a larger memory footprint. In this paper, we introduce an approach to obtain robust yet compact models by pruning randomly-initialized binary networks. Unlike adversar ...

2022

The Rebound Effects from Industrial Energy Efficiency Improvements

Michel Zimmermann

In energy policy, energy efficiency constitutes a central element in reducing domestic and, specifically, industrial en-ergy use. Unfortunately, the effectiveness of energy efficiency improvements in achieving its targets is known to be limited by rebound ...

EPFL2022

Iterative refinement of Schur decompositions

Daniel Kressner, Zvonimir Bujanovic

The Schur decomposition of a square matrix A is an important intermediate step of state-of-the-art numerical algorithms for addressing eigenvalue problems, matrix functions, and matrix equations. This work is concerned with the following task: Compute a (m ...

SPRINGER2023

Low-noise high-dynamic-range single-photon avalanche diodes with integrated PQAR circuit in a standard 55 nm BCD

Edoardo Charbon, Claudio Bruschini, Francesco Gramuglia, Myung Jae Lee, Ekin Kizilkan, Pouyan Keshavarzian

Single-photon avalanche diode (SPAD) based sensors and systems enable a variety of applications in biomedical, automotive, consumer, and security domains. While several established standard technologies, which can facilitate the design of SPAD-based system ...

SPIE-INT SOC OPTICAL ENGINEERING2022

Highly Sensitive Detection of the Antidepressant Fluoxetine With an Extended Gate Field Effect Transistor

Mihai Adrian Ionescu, Shokoofeh Sheibani

Fluoxetine (FL) is one of the selective serotonin reuptake inhibitors, which is used as an anti-depressant, as well as anti-panic drug. In this work, a sensor for label-free recognition of trace amounts of FL is introduced, which is based on an extended ga ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022