Related publications (66)

EAST discharge prediction without integrating simulation results (vol 62, 126060, 2022)

Alessandro Pau, Xiaojuan Liu, Chenguang Wan

In the published paper titled 'EAST discharge prediction without integrating simulation results' (2022 Nucl. Fusion 62 126060), figure 5 used the wrong plot, and is not matched with table 3. We used the plot discussed with referees, the case when we do not ...
Bristol2023

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

Privatized graph federated learning

Ali H. Sayed, Stefan Vlaski, Elsa Rizk

Federated learning is a semi-distributed algorithm, where a server communicates with multiple dispersed clients to learn a global model. The federated architecture is not robust and is sensitive to communication and computational overloads due to its one-m ...
SPRINGER2023

Eco-morphodynamic carbon pumping by the largest rivers in the Neotropics

Paolo Perona

The eco-morphodynamic activity of large tropical rivers in South and Central America is analyzed to quantify the carbon flux from riparian vegetation to inland waters. We carried out a multi-temporal analysis of satellite data for all the largest rivers in ...
2023

Genuinely distributed Byzantine machine learning

Rachid Guerraoui, El Mahdi El Mhamdi, Le Nguyen Hoang, Sébastien Louis Alexandre Rouault, Arsany Hany Abdelmessih Guirguis

Machine learning (ML) solutions are nowadays distributed, according to the so-called server/worker architecture. One server holds the model parameters while several workers train the model. Clearly, such architecture is prone to various types of component ...
2022

Genuinely Distributed Byzantine Machine Learning

Rachid Guerraoui, El Mahdi El Mhamdi, Le Nguyen Hoang, Sébastien Louis Alexandre Rouault, Arsany Hany Abdelmessih Guirguis

Machine Learning (ML) solutions are nowadays distributed, according to the so-called server/worker architecture. One server holds the model parameters while several workers train the model. Clearly, such architecture is prone to various types of component ...
Association for Computing Machinery2020

The SUBGLACIOR drilling probe: Hydraulic considerations

Jérôme Chappellaz

Trends of carbon monoxide (CO) for the past 100 years are reported as derived from Antarctic firn drilling expeditions. Only one of 3 campaigns provided high quality results. The trend was reconstructed using a firn air model in the forward mode to constra ...
Copernicus GmbH2020

MAGNETIC: Multi-Agent Machine Learning-Based Approach for Energy Efficient Dynamic Consolidation in Data Centers

David Atienza Alonso, Marina Zapater Sancho, Ali Pahlevan, Kosar Haghshenas

Improving the energy efficiency of data centers while guaranteeing Quality of Service (QoS), together with detecting performance variability of servers caused by either hardware or software failures, are two of the major challenges for efficient resource m ...
2019

Drowsy-DC: Data center power management system

Willy Zwaenepoel, Baptiste Joseph Eustache Lepers, Mathieu Paul Fernand Bacou

In a modern data center (DC), a large majority of costs arise from energy consumption. The most popular technique used to mitigate this issue is virtualization and more precisely virtual machine (VM) consolidation. Although consolidation may increase serve ...
IEEE2019

Mitigating Load Imbalance in Distributed Data Serving with Rack-Scale Memory Pooling

Babak Falsafi, Edouard Bugnion, Boris Robert Grot, Alexandros Daglis, Stanko Novakovic, Dmitrii Ustiugov

To provide low-latency and high-throughput guarantees, most large key-value stores keep the data in the memory of many servers. Despite the natural parallelism across lookups, the load imbalance, introduced by heavy skew in the popularity distribution of k ...
2019

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