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Publications associées (30)

Distributed Fault Detection for Interconnected Large-Scale Systems: A Scalable Plug & Play Approach

Giancarlo Ferrari Trecate, Marcello Farina

In this paper, we propose a novel distributed fault detection method to monitor the state of a-possibly large scale-linear system, partitioned into interconnected subsystems. The approach hinges on the definition of a partition-based distributed Luenberger ...

2019

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

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

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

Data stream statistics over sliding windows: How to summarize 150 Million updates per second on a single node

Odysseas Papapetrou, Grigorios Chrysos, Dionysios Pnevmatikatos

Traditional data management systems map information using centralized and static data structures. Modern applications need to process in real time datasets much larger than system memory. To achieve this, they use dynamic entities that are updated with str ...

2019

Synergy of classical and quantum computational methods to investigate the properties of microporous materials

Daniele Ongari

The aim of this thesis is to explore the power and the limits of classical and quantum molecular modelling, for the investigation of the adsorption properties of microporous crystalline materials. The materials analyzed are metal organic frameworks (MOFs) ...

EPFL2019

Joint Learning of Semantic Alignment and Object Landmark Detection

Seungryong Kim

Convolutional neural networks (CNNs) based approaches for semantic alignment and object landmark detection have improved their performance significantly. Current efforts for the two tasks focus on addressing the lack of massive training data through weakly ...

IEEE2019

Low-Overhead Dynamic Instruction Mix Generation using Hybrid Basic Block Profiling

Willy Zwaenepoel, Andrzej Pawel Nowak

Dynamic instruction mixes form an important part of the toolkits of performance tuners, compiler writers, and CPU architects. Instruction mixes are traditionally generated using software instrumentation, an accurate yet slow method, that is normally limite ...

2018

Development and Characterisation of Silicon Photomultiplier Multichannel Arrays for the Readout of a Large Scale Scintillating Fibre Tracker

Axel Kuonen

The current LHCb detector will continue collecting data until the long shutdown 2 (2019/2020). It will be upgraded in order to operate at higher luminosity. To achieve this, two major changes are required. First the Level-0 hardware trigger limited to 1,M ...

EPFL2018

Easy and Accurate Hardware-based Program Performance Monitoring

Andrzej Pawel Nowak

The performance monitoring of computer systems is a complex affair, made even more challenging by the increasing gap between hardware and software. Methods that collect and feed data to performance analysis can usually be classified into one of two groups. ...

EPFL2017

ESTIMA: Extrapolating ScalabiliTy of In-Memory Applications

Rachid Guerraoui, Aleksandar Dragojevic, Georgios Chatzopoulos

This article presents ESTIMA, an easy-to-use tool for extrapolating the scalability of in-memory applications. ESTIMA is designed to perform a simple yet important task: Given the performance of an application on a small machine with a handful of cores, ES ...

2017

NAND-NOR: A Compact, Fast, and Delay Balanced FPGA Logic Element

Paolo Ienne, Grace Zgheib, Yu Lin, Wei Li

The And-Inverter Cone has been introduced as an alternative logic element to the look-up table in FPGAs, since it improves their performance and resource utilization. However, further analysis of the AIC design showed that it suffers from the delay discrep ...

ACM2017

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