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Computing Patterns for High Performance Multiscale Computing

Objective

Multiscale phenomena are ubiquitous and they are the key to understanding the complexity of our world. Despite the significant progress achieved through computer simulations over the last decades, we are still limited in our capability to accurately and reliably simulate hierarchies of interacting multiscale physical processes that span a wide range of time and length scales, thus quickly reaching the limits of contemporary high performance computing at the tera- and petascale. Exascale supercomputers promise to lift this limitation, and in this project we will develop multiscale computing algorithms capable of producing high-fidelity scientific results and scalable to exascale computing systems. Our main objective is to develop generic and reusable High Performance Multiscale Computing algorithms that will address the exascale challenges posed by heterogeneous architectures and will enable us to run multiscale applications with extreme data requirements while achieving scalability, robustness, resiliency, and energy efficiency. Our approach is based on generic multiscale computing patterns that allow us to implement customized algorithms to optimise load balancing, data handling, fault tolerance and energy consumption under generic exascale application scenarios. We will realise an experimental execution environment on our pan-European facility, which will be used to measure performance characteristics and develop models that can provide reliable performance predictions for emerging and future exascale architectures. The viability of our approach will be demonstrated by implementing nine grand challenge applications which are exascale-ready and pave the road to unprecedented scientific discoveries. Our ambition is to establish new standards for multiscale computing at exascale, and provision a robust and reliable software technology stack that empowers multiscale modellers to transform computer simulations into predictive science.
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Coordinator

UNIVERSITEIT VAN AMSTERDAM

Address

Spui 21
1012wx Amsterdam

Netherlands

Activity type

Higher or Secondary Education Establishments

EU Contribution

€ 754 000

Participants (12)

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UNIVERSITY COLLEGE LONDON

United Kingdom

EU Contribution

€ 603 125

INSTYTUT CHEMII BIOORGANICZNEJ POLSKIEJ AKADEMII NAUK

Poland

EU Contribution

€ 435 375

BAYERISCHE AKADEMIE DER WISSENSCHAFTEN

Germany

EU Contribution

€ 423 375

MAX-PLANCK-GESELLSCHAFT ZUR FORDERUNG DER WISSENSCHAFTEN EV

Germany

EU Contribution

€ 413 625

UNIVERSITEIT LEIDEN

Netherlands

EU Contribution

€ 370 710

SCIENCE AND TECHNOLOGY FACILITIES COUNCIL

United Kingdom

UNITED KINGDOM RESEARCH AND INNOVATION

United Kingdom

EU Contribution

€ 346 750

ALLINEA SOFTWARE LIMITED

United Kingdom

EU Contribution

€ 110 156,91

CBK SCI CON LIMITED

United Kingdom

EU Contribution

€ 128 125

SAINT PETERSBURG NATIONAL RESEARCH UNIVERSITY OF INFORMATION TECHNOLOGIES, MECHANICS AND OPTICS

Russia

BRUNEL UNIVERSITY LONDON

United Kingdom

ARM LIMITED

United Kingdom

EU Contribution

€ 357 643,09

Project information

Grant agreement ID: 671564

  • Start date

    1 October 2015

  • End date

    30 September 2018

Funded under:

H2020-EU.1.2.2.

  • Overall budget:

    € 4 122 864,36

  • EU contribution

    € 3 942 885

Coordinated by:

UNIVERSITEIT VAN AMSTERDAM

Netherlands