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Concept

Booting process of Linux

Publications associées (12)

End-to-end kernel learning via generative random Fourier features

Fanghui Liu

Random Fourier features (RFFs) provide a promising way for kernel learning in a spectral case. Current RFFs-based kernel learning methods usually work in a two-stage way. In the first-stage process, learn-ing an optimal feature map is often formulated as a ...

ELSEVIER SCI LTD2023

SecureCells: A Secure Compartmentalized Architecture

Babak Falsafi, Mathias Josef Payer, Siddharth Gupta, Atri Bhattacharyya, Yuanlong Li, Florian Hofhammer, Andrés Sánchez Marín

Modern programs are monolithic, combining code of varied provenance without isolation, all the while running on network-connected devices. A vulnerability in any component may compromise code and data of all other components. Compartmentalization separates ...

2023

USBFuzz: A Framework for Fuzzing USB Drivers by Device Emulation

Mathias Josef Payer

The Universal Serial Bus (USB) connects external devices to a host. This interface exposes the OS kernels and device drivers to attacks by malicious devices. Unfortunately, kernels and drivers were developed under a security model that implicitly trusts co ...

USENIX ASSOC2020

i-DPs CGRA: An Interleaved-Datapaths Reconfigurable Accelerator for Embedded Bio-signal Processing

David Atienza Alonso, Giovanni Ansaloni, Miguel Peon Quiros, Soumya Subhra Basu, Loris Gérard Duch

Smart edge sensors for bio-signal monitoring must support complex signal processing routines within an extremely small energy envelope. Coarse-Grained Reconfigurable Arrays (CGRAs) are good candidates for tackling these conflicting objectives because, than ...

2019

Kernel Modeling Super-Resolution on Real Low-Resolution Images

Sabine Süsstrunk, Ruofan Zhou

Deep convolutional neural networks (CNNs), trained on corresponding pairs of high- and low-resolution images, achieve state-of-the-art performance in single-image super- resolution and surpass previous signal-processing based approaches. However, their per ...

IEEE COMPUTER SOC2019

A Synchronization-Based Hybrid-Memory Multi-Core Architecture for Energy-Efficient Biomedical Signal Processing

David Atienza Alonso, Luca Benini, Giovanni Ansaloni, Ruben Braojos Lopez

In the last decade, improvements on technology scaling have enabled the design of a novel generation of wearable bio-sensing monitors. These smart Wireless Body Sensor Nodes (WBSNs) are able to acquire and process biological signals, such as electrocardiog ...

Institute of Electrical and Electronics Engineers2017

A Multi-Core Reconfigurable Architecture for Ultra-Low Power Bio-Signal Analysis

David Atienza Alonso, Giovanni Ansaloni, Ruben Braojos Lopez, Soumya Subhra Basu, Loris Gérard Duch

This paper introduces a novel computing architecture devoted to the ultra-low power analysis of multiple bio-signals. Its structure comprises several processors interfaced with a shared acceleration resource, implemented as a Coarse Grained Reconfigurable ...

2016

Hardware/Software Co-Design of Ultra-Low Power Biomedical Monitors

Ruben Braojos Lopez

Ongoing changes in world demographics and the prevalence of unhealthy lifestyles are imposing a paradigm shift in healthcare delivery. Nowadays, chronic ailments such as cardiovascular diseases, hypertension and diabetes, represent the most common causes o ...

EPFL2016

Guided Mesh Normal Filtering

Sofien Bouaziz, Bailin Deng

The joint bilateral filter is a variant of the standard bilateral filter, where the range kernel is evaluated using a guidance signal instead of the original signal. It has been successfully applied to various image processing problems, where it provides m ...

Wiley-Blackwell2015

The Movement Error Rate for Evaluation of Machine Learning Methods for sEMG-based Hand Movement Classification

Barbara Caputo

There has been increasing interest in applying learning algorithms to improve the dexterity of myoelectric prostheses. In this work, we present a large-scale benchmark evaluation on the second iteration of the publicly released NinaPro database, which cont ...

2014

Rebasing I/O for Scientific Computing: Leveraging Storage Class Memory in an IBM BlueGene/Q Supercomputer

Felix Schürmann, Pramod Shivaji Kumbhar, Fabien Jonathan Delalondre, Lars Schneidenbach, Alessandro Curioni, John Anthony Biddiscombe, Miguel Angel Gila Arrondo, Peter Morjan, Robert Germain, Blake Fitch

Storage class memory is receiving increasing attention for use in HPC systems for the acceleration of intensive IO operations. We report a particular instance using SLC FLASH memory integrated with an IBM BlueGene/Q supercomputer at scale (Blue Gene Active ...

Springer2014

Aseba Meets D-Bus: From the Depths of a Low-Level Event-

Francesco Mondada, Stéphane Magnenat

The robotics research community has clearly acknowledged the need of open and standard software stacks to promote reuse of code and developments. However, to date no particular project has prevailed. We suggest that one possible reason for this is that mos ...

2009