EPEEC SIGNED
European joint Effort toward a Highly Productive Programming Environment for Heterogeneous Exascale Computing (EPEEC)
Total Cost €
0EC-Contrib. €
0Partnership
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0EPEEC project word cloud
Explore the words cloud of the EPEEC project. It provides you a very rough idea of what is the project "EPEEC" about.
Project "EPEEC" data sheet
The following table provides information about the project.
| Coordinator |
BARCELONA SUPERCOMPUTING CENTER - CENTRO NACIONAL DE SUPERCOMPUTACION
Organization address contact info |
| Coordinator Country | Spain [ES] |
| Total cost | 3˙990˙708 € |
| EC max contribution | 3˙990˙708 € (100%) |
| Programme |
1. H2020-EU.1.2.2. (FET Proactive) |
| Code Call | H2020-FETHPC-2017 |
| Funding Scheme | RIA |
| Starting year | 2018 |
| Duration (year-month-day) | from 2018-10-01 to 2021-09-30 |
Partnership
Take a look of project's partnership.
| # | ||||
|---|---|---|---|---|
| 1 | BARCELONA SUPERCOMPUTING CENTER - CENTRO NACIONAL DE SUPERCOMPUTACION | ES (BARCELONA) | coordinator | 972˙678.00 |
| 2 | FRAUNHOFER GESELLSCHAFT ZUR FOERDERUNG DER ANGEWANDTEN FORSCHUNG E.V. | DE (MUNCHEN) | participant | 496˙500.00 |
| 3 | INSTITUT NATIONAL DE RECHERCHE ENINFORMATIQUE ET AUTOMATIQUE | FR (LE CHESNAY CEDEX) | participant | 424˙597.00 |
| 4 | CENTRE EUROPEEN DE RECHERCHE ET DE FORMATION AVANCEE EN CALCUL SCIENTIFIQUE | FR (TOULOUSE) | participant | 385˙000.00 |
| 5 | INTERUNIVERSITAIR MICRO-ELECTRONICA CENTRUM | BE (LEUVEN) | participant | 355˙415.00 |
| 6 | INESC ID - INSTITUTO DE ENGENHARIADE SISTEMAS E COMPUTADORES, INVESTIGACAO E DESENVOLVIMENTO EM LISBOA | PT (LISBOA) | participant | 313˙750.00 |
| 7 | UPPSALA UNIVERSITET | SE (UPPSALA) | participant | 290˙625.00 |
| 8 | ETA SCALE AB | SE (UPPSALA) | participant | 269˙375.00 |
| 9 | APPENTRA SOLUTIONS SL | ES (A CORUNA) | participant | 257˙767.00 |
| 10 | CINECA CONSORZIO INTERUNIVERSITARIO | IT (CASALECCHIO DI RENO BO) | participant | 225˙000.00 |
Map
Project objective
EPEEC’s main goal is to develop and deploy a production-ready parallel programming environment that turns upcoming overwhelmingly-heterogeneous exascale supercomputers into manageable platforms for domain application developers. The consortium will significantly advance and integrate existing state-of-the-art components based on European technology (programming models, runtime systems, and tools) with key features enabling 3 overarching objectives: high coding productivity, high performance, and energy awareness. An automatic generator of compiler directives will provide outstanding coding productivity from the very beginning of the application developing/porting process. Developers will be able to leverage either shared memory or distributed-shared memory programming flavours, and code in their preferred language: C, Fortran, or C\. EPEEC will ensure the composability and interoperability of its programming models and runtimes, which will incorporate specific features to handle data-intensive and extreme-data applications. Enhanced leading-edge performance tools will offer integral profiling, performance prediction, and visualisation of traces. Five applications representative of different relevant scientific domains will serve as part of a strong inter-disciplinary co-design approach and as technology demonstrators. EPEEC exploits results from past FET projects that led to the cutting-edge software components it builds upon, and pursues influencing the most relevant parallel programming standardisation bodies. The consortium is composed of European institutions and individuals with the highest expertise in their field, including not only leading research centres and universities but also SME/start-up companies, all of them recognised as high-tech innovators worldwide. Adhering to the Work Programme’s guidelines, EPEEC features the participation of young and high-potential researchers, and includes careful dissemination, exploitation, and public engagement plans.
Publications
| year | authors and title | journal | last update |
|---|---|---|---|
| 2019 |
Tom Vander Aa, Imen Chakroun, Tom Ashby, Jaak Simm, Adam Arany, Yves Moreau, Thanh Le Van, José Felipe Golib Dzib, Jörg Wegner, Vladimir Chupakhin, Hugo Ceulemans, Roel Wuyts, Wilfried Verachtert SMURFF: a High-Performance Framework for Matrix Factorization Methods (extended abstract) published pages: , ISSN: , DOI: |
Proceedings of the 31st Benelux Conference on Artificial Intelligence (BNAIC 2019) and the 28th Belgian Dutch Conference on Machine Learning (Benelearn 2019) 2019 | 2020-04-15 |
| 2020 |
David Gureya, João Neto, Reza Karimi, João Barreto, Pramod Bhatotia, Vivien Quema, Rodrigo Rodrigues, Paolo Romano, Vladimir Vlassov Bandwidth-Aware Page Placement in NUMA published pages: , ISSN: , DOI: |
Proceedings of the 34th IEEE International Parallel & Distributed Processing Symposium (IPDPS), 2020 2020 | 2020-04-15 |
| 2019 |
Imen Chakroun, Tom Vander Aa, Tomas J. Ashby Guidelines for enhancing data locality in selected machine learning algorithms published pages: 1003-1020, ISSN: 1088-467X, DOI: 10.3233/ida-184287 |
Intelligent Data Analysis 23/5 | 2020-04-15 |
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