MADAME

Manycore Application Development and Modeling Environment

 Coordinatore LUDWIG-MAXIMILIANS-UNIVERSITAET MUENCHEN 

 Organization address address: GESCHWISTER SCHOLL PLATZ 1
city: MUENCHEN
postcode: 80539

contact info
Titolo: Prof.
Nome: Dieter
Cognome: Kranzlmueller
Email: send email
Telefono: +49 89 2180 9146
Fax: +49 89 2180 9147

 Nazionalità Coordinatore Germany [DE]
 Totale costo 100˙000 €
 EC contributo 100˙000 €
 Programma FP7-PEOPLE
Specific programme "People" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013)
 Code Call FP7-PEOPLE-2010-RG
 Funding Scheme MC-IRG
 Anno di inizio 2011
 Periodo (anno-mese-giorno) 2011-01-03   -   2015-01-02

 Partecipanti

# participant  country  role  EC contrib. [€] 
1    LUDWIG-MAXIMILIANS-UNIVERSITAET MUENCHEN

 Organization address address: GESCHWISTER SCHOLL PLATZ 1
city: MUENCHEN
postcode: 80539

contact info
Titolo: Prof.
Nome: Dieter
Cognome: Kranzlmueller
Email: send email
Telefono: +49 89 2180 9146
Fax: +49 89 2180 9147

DE (MUENCHEN) coordinator 100˙000.00

Mappa


 Word cloud

Esplora la "nuvola delle parole (Word Cloud) per avere un'idea di massima del progetto.

yet    parallel    industry    tradeoffs    computing    efficient    manycore    designed    programmers   

 Obiettivo del progetto (Objective)

'The multicore revolution (parallel computing on a chip) is predicted by many to be a major disruptive change for the IT industry. The biggest challenges lie in the productive yet efficient usage of parallel computing resources for the large class of programmers who are not experts in parallel hard- and software architecture. Continuing industry trends leading to increased heterogeneity and asymmetry, together with execution environments that demand dynamic adaptability, will further exacerbate the programming challenges.

The MADAME proposal is designed to help programmers develop efficient parallel programs by providing two complementary components. The first component is an efficient monitoring toolset for manycore computing that extends previous work in the area of OpenMP profiling. The second component is a modeling approach that lets users understand performance vs. productivity tradeoffs when developing their code and allows the detection of scalability issues by estimating run-times on platforms that need not be available in real hardware yet. The models are also designed to be used at runtime by upcoming manycore operating systems as a means to communicate quality of service (QoS) requirements and tradeoffs.'

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