Publications associées à Parallelization of the LEMan Code with MPI and OpenMP

Systematic Assessment of Hyperdimensional Computing for Epileptic Seizure Detection

David Atienza Alonso, Una Pale, Tomas Teijeiro Campo

Hyperdimensional computing is a promising novel paradigm for low-power embedded machine learning. It has been applied on different biomedical applications, and particularly on epileptic seizure detection. Unfortunately, due to differences in data preparati ...

2021

Computation Of A 30750-Bit Binary Field Discrete Logarithm

Arjen Lenstra, Thorsten Kleinjung, Benjamin Pierre Charles Wesolowski, Robert Granger

This paper reports on the computation of a discrete logarithm in the finite field F-230750, breaking by a large margin the previous record, which was set in January 2014 by a computation in F-29234. The present computation made essential use of the elimina ...

AMER MATHEMATICAL SOC2021

Path Replay Backpropagation: Differentiating Light Paths using Constant Memory and Linear Time

Sébastien Nicolas Speierer, Wenzel Alban Jakob, Delio Aleardo Vicini

Differentiable physically-based rendering has become an indispensable tool for solving inverse problems involving light. Most applications in this area jointly optimize a large set of scene parameters to minimize an objective function, in which case revers ...

ASSOC COMPUTING MACHINERY2021

Energy-based comparison between the Fourier-Galerkin method and the finite element method

Thomas Willem Jan de Geus

The Fourier-Galerkin method (in short FFTH) has gained popularity in numerical homogenisation because it can treat problems with a huge number of degrees of freedom. Because the method incorporates the fast Fourier transform (FFT) in the linear solver, it ...

ELSEVIER2020

Graph fragmentation problem: analysis and synthesis

Manuel Francesco Aprile, Pablo Romero Gómez

Vulnerability metrics play a key role in the understanding of cascading failures and target/random attacks to a network. The graph fragmentation problem (GFP) is the result of a worst-case analysis of a random attack. We can choose a fixed number of indivi ...

WILEY2019

Computational memory-based inference and training of deep neural networks

Irem Boybat Kara, Abu Sebastian, Evangelos Eleftheriou

In-memory computing is an emerging computing paradigm where certain computational tasks are performed in place in a computational memory unit by exploiting the physical attributes of the memory devices, Here, we present an overview of the application of in ...

IEEE2019

New Algorithmic Paradigms for Discrete Problems using Dynamical Systems and Polynomials

Damian Mateusz Straszak

Optimization is a fundamental tool in modern science. Numerous important tasks in biology, economy, physics and computer science can be cast as optimization problems. Consider the example of machine learning: recent advances have shown that even the most s ...

EPFL2018

PDE-Constrained Optimal Control Problems with Uncertain Parameters using SAGA

Fabio Nobile, Matthieu Claude Martin

We consider an optimal control problem (OCP) for a partial differential equation (PDE) with random coefficients. The optimal control function is a deterministic, distributed forcing term that minimizes an expected quadratic regularized loss functional. For ...

2021

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

Round Compression for Parallel Matching Algorithms

Slobodan Mitrovic, Aleksander Madry

For over a decade now we have been witnessing the success of massive parallel computation (MPC) frameworks, such as MapReduce, Hadoop, Dryad, or Spark. One of the reasons for their success is the fact that these frameworks are able to accurately capture th ...

ASSOC COMPUTING MACHINERY2018

Efficient Sample Delay Calculation for 2-D and 3-D Ultrasound Imaging

Jean-Philippe Thiran, Giovanni De Micheli, Federico Angiolini, Luca Benini, Aya Mohamed Naguib Ahmed Ibrahim, Marcel Arditi

Ultrasound imaging is a reference medical diagnostic technique, thanks to its blend of versatility, effectiveness, and moderate cost. The core computation of all ultrasound imaging methods is based on simple formulae, except for those required to calculate ...

Ieee-Inst Electrical Electronics Engineers Inc2017

On Coordinated Primal-Dual Interior-Point Methods for Multi-Agent Optimization

Colin Neil Jones, Altug Bitlislioglu

This paper presents a coordinated primal-dual interior point (PDIP) method for solving structured convex linear and quadratic programs (LP-QP) in a distributed man- ner. The considered class of problems represents a multi-agent setting, where the aggregate ...

2017

Ultra-Low Power Estimation of Heart Rate Under Physical Activity Using a Wearable Photoplethysmographic System

David Atienza Alonso, Srinivasan Murali, Francisco Javier Rincon Vallejos, Elisabetta De Giovanni

In the last years, the need for enhancing health and preventing problems with remote monitoring is increasing. A non-invasive low-cost technique for processing bio-signals and monitoring vital parameters, at rest and during physical activity, is the use of ...

IEEE Press2016

A Fast Hadamard Transform for Signals with Sub-linear Sparsity in the Transform Domain

Martin Vetterli, Robin Scheibler, Saeid Haghighatshoar

In this paper, we design a new iterative low-complexity algorithm for computing the Walsh-Hadamard transform (WHT) of an N dimensional signal with a K-sparse WHT. We suppose that N is a power of two and K = O(N^α), scales sub-linearly in N for some α ∈ (0, ...

Institute of Electrical and Electronics Engineers2015

Real-Time High-Resolution Multiple-Camera Depth Map Estimation Hardware and Its Applications

Abdulkadir Akin

Depth information is used in a variety of 3D based signal processing applications such as autonomous navigation of robots and driving systems, object detection and tracking, computer games, 3D television, and free view-point synthesis. These applications r ...

EPFL2015

An inexact proximal path-following algorithm for constrained convex minimization

Volkan Cevher, Anastasios Kyrillidis, Quoc Tran Dinh

Many scientific and engineering applications feature large-scale non-smooth convex minimization problems over convex sets. In this paper, we address an important instance of this broad class where we assume that the non-smooth objective is equipped with a ...

Siam Publications2014

LLR Compression for BICM Systems Using Large Constellations

Bixio Rimoldi, Stefano Rosati

Digital video broadcasting (DVB-C2) and other modern communication standards increase diversity by means of a symbol-level interleaver that spans over several codewords. Deinterleaving at the receiver requires a large memory, which has a significant impact ...

Institute of Electrical and Electronics Engineers2013

Blind Phase Calibration in Sparse Recovery

Rémi Gribonval, Gilles Puy

We consider a blind calibration problem in a compressed sensing measurement system in which each sensor introduces an unknown phase shift to be determined. We show that this problem can be approached similarly to the problem of phase retrieval from quadrat ...

2013

A Fast Hadamard Transform for Signals with Sub-linear Sparsity

Martin Vetterli, Robin Scheibler, Saeid Haghighatshoar

A new iterative low complexity algorithm has been presented for computing the Walsh-Hadamard transform (WHT) of an N dimensional signal with a K-sparse WHT, where N is a power of two and K = O(N^α), scales sub- linearly in N for some 0 < α < 1. Assuming a ...

2013

Silence-Based Communication

Christina Fragouli

Communication complexity---the minimum amount of communication required---of computing a function of data held by several parties is studied. A communication model where silence is used to convey information is introduced. For this model the worst-case and ...

2010