Concept

Cluster Beowulf

Publications associées (66)

Multi-physics modeling of VVERs with high fidelity high-resolution codes

The calculations performed for the design and operation of a Nuclear Power Plant (NPP) are a key factor for their safety analyses. The standard for the computational analysis of NPPs is the so called conventional approach, which relies on coarse mesh diffu ...

EPFL2022

Subspace clustering in high-dimensions: Phase transitions & Statistical-to-Computational gap

Florent Gérard Krzakala, Lenka Zdeborová, Luca Pesce, Bruno Loureiro

A simple model to study subspace clustering is the high-dimensional k -Gaussian mixture model where the cluster means are sparse vectors. Here we provide an exact asymptotic characterization of the statistically optimal reconstruction error in this model i ...

2022

Simple automation of SEM-EDS spectral maps analysis with Python and the edxia framework

Karen Scrivener, Fabien Jacques Michel Georget, William Wilson

In a recent article, we described the edxia framework, a user-friendly framework to analyse the microstructure of cementitious materials using SEM-EDS hypermaps. The manual approach presented was shown to be efficient to answer the relevant scientific ques ...

WILEY2022

Cluster Catalysis with Lattice Oxygen: Tracing Oxygen Transport from a Magnetite (001) Support onto Small Pt Clusters

Wolfgang Harbich, Giulia Elisabetta Pacchioni, Ke Zhang

Oxidation catalysis on reducible oxide-supported small metal clusters often involves lattice oxygen. The present work aims at differentiating whether the reaction takes place at the cluster/support interface or on the cluster. To that purpose, we trace the ...

AMER CHEMICAL SOC2021

Consensus Control for Decentralized Deep Learning

Martin Jaggi, Sebastian Urban Stich, Anastasiia Koloskova, Tao Lin, Lingjing Kong

Decentralized training of deep learning models enables on-device learning over networks, as well as efficient scaling to large compute clusters. Experiments in earlier works reveal that, even in a data-center setup, decentralized training often suffers fro ...

JMLR-JOURNAL MACHINE LEARNING RESEARCH2021

An Architecture for Load Balance in Computer Cluster Applications

Laurent Bindschaedler

Amid a data revolution that is transforming industries around the globe, computing systems have undergone a paradigm shift where many applications are scaled out to run on multiple computers in a computing cluster. As the storage and processing capabilitie ...

EPFL2020

An Associativity-Agnostic in-Cache Computing Architecture Optimized for Multiplication

David Atienza Alonso, Marina Zapater Sancho, Alexandre Sébastien Julien Levisse, Marco Antonio Rios, William Andrew Simon

With the spread of cloud services and Internet of Things concept, there is a popularization of machine learning and artificial intelligence based analytics in our everyday life. However, an efficient deployment of these data-intensive services requires per ...

2019

Finding a Needle in the Haystack of Hardened Interconnect Patterns

Paolo Ienne, Grace Zgheib, Stefan Nikolic

Circuits naturally exhibit recurring patterns of local interconnect. Hardening those patterns when designing Field Programmable Gate Array (FPGA) clusters can both eliminate slow programmable connections from the critical path and remove the need for trans ...

IEEE2019

Hybrid, Job-Aware, and Preemptive Datacenter Scheduling

Pamela Isabel Delgado Borda

Scheduling in datacenters is an important, yet challenging problem. Datacenters are composed of a large number, typically tens of thousands, of commodity computers running a variety of data-parallel jobs. The role of the scheduler is to assign cluster reso ...

EPFL2018

Diffusion gradient boosting for networked learning

Ali H. Sayed, Bicheng Ying

Using duality arguments from optimization theory, this work develops an effective distributed gradient boosting strategy for inference and classification by networked clusters of learners. By sharing local dual variables with their immediate neighbors thro ...

2017

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