Materials Map

Discover the materials research landscape. Find experts, partners, networks.

  • About
  • Privacy Policy
  • Legal Notice
  • Contact

The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

×

Materials Map under construction

The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

To Graph

1.080 Topics available

To Map

977 Locations available

693.932 PEOPLE
693.932 People People

693.932 People

Show results for 693.932 people that are selected by your search filters.

←

Page 1 of 27758

→
←

Page 1 of 0

→
PeopleLocationsStatistics
Naji, M.
  • 2
  • 13
  • 3
  • 2025
Motta, Antonella
  • 8
  • 52
  • 159
  • 2025
Aletan, Dirar
  • 1
  • 1
  • 0
  • 2025
Mohamed, Tarek
  • 1
  • 7
  • 2
  • 2025
Ertürk, Emre
  • 2
  • 3
  • 0
  • 2025
Taccardi, Nicola
  • 9
  • 81
  • 75
  • 2025
Kononenko, Denys
  • 1
  • 8
  • 2
  • 2025
Petrov, R. H.Madrid
  • 46
  • 125
  • 1k
  • 2025
Alshaaer, MazenBrussels
  • 17
  • 31
  • 172
  • 2025
Bih, L.
  • 15
  • 44
  • 145
  • 2025
Casati, R.
  • 31
  • 86
  • 661
  • 2025
Muller, Hermance
  • 1
  • 11
  • 0
  • 2025
Kočí, JanPrague
  • 28
  • 34
  • 209
  • 2025
Šuljagić, Marija
  • 10
  • 33
  • 43
  • 2025
Kalteremidou, Kalliopi-ArtemiBrussels
  • 14
  • 22
  • 158
  • 2025
Azam, Siraj
  • 1
  • 3
  • 2
  • 2025
Ospanova, Alyiya
  • 1
  • 6
  • 0
  • 2025
Blanpain, Bart
  • 568
  • 653
  • 13k
  • 2025
Ali, M. A.
  • 7
  • 75
  • 187
  • 2025
Popa, V.
  • 5
  • 12
  • 45
  • 2025
Rančić, M.
  • 2
  • 13
  • 0
  • 2025
Ollier, Nadège
  • 28
  • 75
  • 239
  • 2025
Azevedo, Nuno Monteiro
  • 4
  • 8
  • 25
  • 2025
Landes, Michael
  • 1
  • 9
  • 2
  • 2025
Rignanese, Gian-Marco
  • 15
  • 98
  • 805
  • 2025

Arzel, Matthieu

  • Google
  • 4
  • 7
  • 16

in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (4/4 displayed)

  • 2017A Scaling-Less Newton-Raphson Pipelined Implementation for a Fixed-Point Reciprocal Operator6citations
  • 2017Open-source flexible packet parser for high data rate agile network probe3citations
  • 2017A scaling-less Newton-Raphson pipelined implementation for a fixed-point inverse square root operator7citations
  • 2017Combining FPGAs and processors for high-throughput forensicscitations

Places of action

Chart of shared publication
Lahuec, Cyril
2 / 6 shared
Andriulli, Francesco
2 / 3 shared
Libessart, Erwan
2 / 2 shared
Cornevaux-Juignet, Franck
2 / 2 shared
Person, Christian
2 / 5 shared
Groleat, Tristan
2 / 2 shared
Horrein, Pierre-Henri
2 / 2 shared
Chart of publication period
2017

Co-Authors (by relevance)

  • Lahuec, Cyril
  • Andriulli, Francesco
  • Libessart, Erwan
  • Cornevaux-Juignet, Franck
  • Person, Christian
  • Groleat, Tristan
  • Horrein, Pierre-Henri
OrganizationsLocationPeople

document

Combining FPGAs and processors for high-throughput forensics

  • Arzel, Matthieu
  • Cornevaux-Juignet, Franck
  • Person, Christian
  • Groleat, Tristan
  • Horrein, Pierre-Henri
Abstract

Data centers availability is mandatory and is conditioned by a quick response to failures and attacks thanks to efficient live forensics. However, this task is lately impossible to complete with classic systems because of encountered data rates and service diversity. Moreover, Software-Defined Networking (SDN) devices agility requirements prevent the use of Application Specific Integrated Circuits (ASIC) solutions due to long development time. New solutions of smart Network Interface Cards (NIC) with embedded Field Programmable Gate Arrays (FPGA) are considered, as in Microsoft Azure solution. FPGAs ensure high throughput processings without packet loss to offload CPU processing, but their configurations support only sparse firmware upgrades and shut down processings. This paper proposes an hybrid architecture to realize agile high performance traffic forensics. This work combines hardware performance, high throughput, and software high flexibility to achieve data rates beyond 40 Gb/s while being configurable at runtime through parameters. A software API allows a user-friendly configuration without stopping processings. The implementation of a flexible packet parser, first block of the packet processing chain, demonstrates the viability of the concept.

Topics
  • impedance spectroscopy