Publications associées à Network address translation

Intermediate Address Space: virtual memory optimization of heterogeneous architectures for cache-resident workloads

David Atienza Alonso, Marina Zapater Sancho, Luis Maria Costero Valero, Darong Huang, Qunyou Liu

The increasing demand for computing power and the emergence of heterogeneous computing architectures have driven the exploration of innovative techniques to address current limitations in both the compute and memory subsystems. One such solution is the use ...

2024

Influence of micro-patterned support properties and interfacial polymerization conditions on performance of patterned thin-film composite membranes

Kumar Varoon Agrawal, Cédric Karel J Van Goethem

Patterned membranes prepared via spray-modified non -solvent induced phase separation (s-NIPS) have successfully shown enhanced fluxes and better fouling control, thanks to the increased surface area and high fluid shear at the membrane/feed interface. The ...

Elsevier2024

Entrepreneurial Opportunities and Threats in the Era of Grand Societal Challenges

Enrico Bergamini

We live in an era defined by attempts to grapple with an ever-expanding array of grand societal challenges (GCs). These challenges comprise transformational social and environmental issues, such as environmental degradation and global pandemics, and the cr ...

EPFL2023

Rebooting Virtual Memory with Midgard

Siddharth Gupta

Virtual Memory (VM) is a critical programming abstraction that is widely used in various modern computing platforms. With the rise of datacenter computing and birth of planet-scale online services, the semantic and capacity requirements from memory have ev ...

EPFL2023

uKharon: A Membership Service for Microsecond Applications

Rachid Guerraoui, Antoine Murat, Javier Picorel Obando, Athanasios Xygkis

Modern data center fabrics open the possibility of microsecond distributed applications, such as data stores and message queues. A challenging aspect of their development is to ensure that, besides being fast in the common case, these applications react fa ...

USENIX Association2023

Critical node selection method for efficient Max-Pressure traffic signal control in large-scale congested networks

Nikolaos Geroliminis, Dimitrios Tsitsokas, Anastasios Kouvelas

Decentralized signal control of congested traffic networks based on the Max-Pressure (MP) controller is theoretically proven to maximize throughput, stabilize the system and balance queues for single intersections under specific conditions. However, its pe ...

2022

Expanding biochemical knowledge and illuminating metabolic dark matter with ATLASx

Vassily Hatzimanikatis, Jasmin Maria Hafner, Anastasia Sveshnikova, Victor Luc Etienne Viterbo

Metabolic "dark matter" describes currently unknown metabolic processes, which form a blind spot in our general understanding of metabolism and slow down the development of biosynthetic cell factories and naturally derived pharmaceuticals. Mapping the dark ...

Nature Portfolio2022

Byzantine Machine Learning Made Easy By Resilient Averaging of Momentums

Rachid Guerraoui, John Stephan, Sadegh Farhadkhani, Nirupam Gupta, Rafaël Benjamin Pinot

Byzantine resilience emerged as a prominent topic within the distributed machine learning community. Essentially, the goal is to enhance distributed optimization algorithms, such as distributed SGD, in a way that guarantees convergence despite the presence ...

PMLR2022

A Canvas for the Ethical Design of Learning Experiences with Digital Tools

Denis Gillet, Patrick Jermann, Roland John Tormey, Cécile Hardebolle, Adrian Christian Holzer, Jessica Elke Dehler Zufferey, Pascal Felber

The use of digital tools has drastically increased in engineering education, accelerated by the COVID-19 pandemic. These tools generate important ethical issues, in particular in terms of privacy and fairness. However, very few teacher training programmes ...

2022

Triple Crossed Flexure Pivot Based on a Zero Parasitic Center Shift Kinematic Design

Simon Nessim Henein, Etienne Frédéric Gabriel Thalmann

Thanks to their absence of play, absence of contact friction and possible monolithic fabrication, flexure pivots offer advantages over traditional bearings in small-scale, high accuracy applications and environments where lubrication and wear debris are pr ...

2022

Rebooting Virtual Memory with Midgard

Babak Falsafi, Mathias Josef Payer, Siddharth Gupta, Atri Bhattacharyya, Yunho Oh, Abhishek Bhattacharjee

Computer systems designers are building cache hierarchies with higher capacity to capture the ever-increasing working sets of modern workloads. Cache hierarchies with higher capacity improve system performance but shift the performance bottleneck to addres ...

2021

Fidelity Estimation Improves Noisy-Image Classification with Pretrained Networks

Sabine Süsstrunk, Majed El Helou, Deblina Bhattacharjee, Xiaoyu Lin

Image classification has significantly improved using deep learning. This is mainly due to convolutional neural networks (CNNs) that are capable of learning rich feature extractors from large datasets. However, most deep learning classification methods are ...

IEEE Institute of Electrical and Electronics Engineers2021

Reply to the Comment on "Phase transitions, screening and dielectric response of CsPbBr3" by S. Svirskas, S. Balciunas, M. Simenas, G. Usevicius, M. Kinka, M. Velicka, D. Kubicki, M. E. Castillo, A. Karabanov, V. V. Shvartsman, M. R. Soares, V. Sablinskas, A. N. Salak, D. C. Lupascu and J. Banys, J. Mater. Chem. A, 2020, 8, 14015

Dominik Józef Kubicki

In this reply, we address the concerns that were raised about our paper on CsPbBr3 single crystals. M. Szafranski criticized the dielectric and DSC data in our original paper claiming that they were affected by the experimental artefacts or poor quality of ...

Royal Society of Chemistry2021

Pretraining boosts out-of-domain robustness for pose estimation

Alexander Mathis, Mackenzie Mathis, Steffen Schneider, Matthias Bethge, Thomas Ray Biasi, Mert Yüksekgönül

Neural networks are highly effective tools for pose estimation. However, as in other computer vision tasks, robustness to out-of-domain data remains a challenge, especially for small training sets that are common for real-world applications. Here, we probe ...

IEEE COMPUTER SOC2021

mu RAI: Securing Embedded Systems with Return Address Integrity

Mathias Josef Payer

Embedded systems are deployed in security critical environments and have become a prominent target for remote attacks. Microcontroller-based systems (MCUS) are particularly vulnerable due to a combination of limited resources and low level programming whic ...

INTERNET SOC2020

Verification of Software Network Functions with No Verification Expertise

Arseniy Zaostrovnykh

Software network functions (NFs), such as a network address translator, load balancer, or proxy, promise to bring flexibility and rapid innovation to computer networks and to reduce operational costs. However, continuous updates and flexibility typically c ...

EPFL2020

Instability of Thin Concrete Walls with a Single Layer of Reinforcement under Cyclic Loading: Numerical Simulation and Improved Equivalent Boundary Element Model for Assessment

Katrin Beyer, João Saraiva Esteves Pacheco de Almeida, Angelica Rosso, Lisandro Arturo Jimenez Roa

Thin reinforced concrete walls may fail due to out-of-plane instability when subjected to seismic loading. While previous numerical studies on wall instability have focused on the behaviour of members with two layers of vertical reinforcement, this work ad ...

TAYLOR & FRANCIS LTD2022

Transport and Water Age Dynamics in Soils: A Comparative Study of Spatially Integrated and Spatially Explicit Models

Andrea Rinaldo, Paolo Benettin, Mitra Asadollahi

We address transport by transit times (i.e., the age of water parcels leaving a storage as discharge, deep loss, or evapotranspiration) in subvertical soil systems, key to our understanding of water quality in catchments and streams. While the use of field ...

2020

Private and Secure Distributed Learning

Georgios Damaskinos

The ever-growing number of edge devices (e.g., smartphones) and the exploding volume of sensitive data they produce, call for distributed machine learning techniques that are privacy-preserving. Given the increasing computing capabilities of modern edge de ...

EPFL2020

In response to ‘Six critical questions about smart spezialisation’

Dominique Foray

This paper has been written as a response to « Six critical questions about smart specialization » by R. Hassink and H. Gong. The paper starts with a reminder of what has not changed in terms of the basic principles and raison d’être of smart specializatio ...

2019