Distributed and Parallel Systems

Prof. Radu Prodan @ Der Standard – Wie man Supercomputer programmiert

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Wer schafft mehr Rechenoperation pro Sekunde? Hochleistungsrechner sind ein wichtiges Werkzeug im Lösen wissenschaftlicher Probleme. HIER der aktuelle Standard Artikel – ein Interview mit Prof. Radu Prodan.

Prof. Radu Prodan

Prof. Radu Prodan visited the Indian Institute of Technology Kottayam

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Prof. Radu Prodan visited the Indian Institute of Technology Kottayam.

ARTICONF: kick-off meeting at Klagenfurt

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Prof. Radu Prodan coordinated EU H2020 Horizon project – ARTICONF (smART socIal media eCOsystem in a blockchaiN Federated environment) held its first kick-off meeting at Klagenfurt from January 8th – 10th 2019. The ARTICONF team comprising of international partners from Austria, Netherlands, UK, Macedonia, Portugal, Spain, and Norway pledged support to create a novel decentralized and trusted social media ecosystem.  The international team with diverse expertise ranging from blockchain to digital sociology discussed the road map of the project over three years stipulated period and outlined innovative ways of contribution to European Union’s grand vision of Next Generation Internet (NGI) goals.

Prof. Radu Prodan

Prof. Radu Prodan @ India

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From October 13-22, 2018 Prof. Radu Prodan visited Chandigarh University and Lovely Professional University in India for interaction with research scholars and discussions about the common research projects.

 

Prof. Radu Prodan (Principal Investigator, ARTICONF, European Union’s Horizon 2020 research and innovation H2020-ICT-2018-2) sharing insights about next generation social media

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Please find the full AAU news blog article here.

Prof. Radu Prodan and Dr. Dragi Kimovski participate at “The 1st ACM SIGOPS Summer School on Advanced Topics in Systems”

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Prof. Radu Prodan and Dr. Dragi Kimovski participate at “The 1st ACM SIGOPS Summer School on Advanced Topics in Systems” where with many proeminent speakers in the area of distributed systenms. They will also present a poster on their work on “A Nature-Inspired Adaptive Fog Architecture”.

Prof. Radu Prodan and Dr. Dragi Kimovski participate in the kickoff meeting of ASPIDE

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The H2020 FET-HPC project ASPIDE started with the Kickoff meeting at the University Carlos III in Madrid.

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Aspide group picture

Guest researcher from the Capital University of Science and Technology, Islamabad

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Dr. Muhammad Aleem  from the Capital University of Science and Technology, Islamabad, Pakistan, visits ITEC@AAU for a period of two months, invited by Prof. Radu Prodan. They will jointly investigate novel programming paradigms, APIs, runtime tools, and methodologies for expressing data-intensive tasks on Exascale systems.

Prof. Radu Prodan

Guest Editor: Special issue in Future Generation Computer Systems

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Prof. Radu Prodan together with Prof. Dr. Eng. Florin Pop and Dr. Gabriel Antoniu published an editorial on “RM-BDP: Resource management for Big Data platforms” in Future Generation Computer Systems (Volume 86, September 2018, Pages 961-963).

Abstract:
Nowadays, when we face with numerous data, when data cannot be classified into regular relational databases and new solutions are required, and when data are generated and processed rapidly, we need powerful platforms and infrastructure as support. Extracting valuable information from raw data is especially difficult considering the velocity of growing data from year to year and the fact that 80% of data is unstructured. In addition, data sources are heterogeneous (various sensors, users with different profiles, etc.) and are located in different situations or contexts. Cloud computing, which concerns large-scale interconnected systems with the main purpose of aggregation and efficient exploiting the power of widely distributed resources, represent one viable solution. Resource management and task scheduling play an essential role, in cases where one is concerned with optimized use of resources (Negru et al., 2017).
The goal of this special issue is to explore new directions and approaches for reasoning about advanced resource management and task scheduling methods and algorithms for Big Data platforms. The accepted papers present new results in the domain of resource management and task scheduling, Cloud platforms supporting Big Data processing, data handling and Big Data applications.