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MAchinE Learning for Scalable meTeoROlogy and cliMate

Objective

To develop Europe’s computer architecture of the future, MAELSTROM will co-design bespoke compute system designs for optimal application performance and energy efficiency, a software framework to optimise usability and training efficiency for machine learning at scale, and large-scale machine learning applications for the domain of weather and climate science.

The MAELSTROM compute system designs will benchmark the applications across a range of computing systems regarding energy consumption, time-to-solution, numerical precision and solution accuracy. Customised compute systems will be designed that are optimised for application needs to strengthen Europe’s high-performance computing portfolio and to pull recent hardware developments, driven by general machine learning applications, toward needs of weather and climate applications.

The MAELSTROM software framework will enable scientists to apply and compare machine learning tools and libraries efficiently across a wide range of computer systems. A user interface will link application developers with compute system designers, and automated benchmarking and error detection of machine learning solutions will be performed during the development phase. Tools will be published as open source.

The MAELSTROM machine learning applications will cover all important components of the workflow of weather and climate predictions including the processing of observations, the assimilation of observations to generate initial and reference conditions, model simulations, as well as post-processing of model data and the development of forecast products. For each application, benchmark datasets with up to 10 terabytes of data will be published online for training and machine learning tool-developments at the scale of the fastest supercomputers in the world. MAELSTROM machine learning solutions will serve as blueprint for a wide range of machine learning applications on supercomputers in the future.

Call for proposal

H2020-JTI-EuroHPC-2019-1
See other projects for this call

Funding Scheme

EuroHPC-RIA - EuroHPC-RIA

Coordinator

EUROPEAN CENTRE FOR MEDIUM-RANGE WEATHER FORECASTS
Address
Shinfield Park
RG2 9AX Reading
United Kingdom
Activity type
Research Organisations
EU contribution
€ 380 625

Participants (6)

4CAST GMBH & CO KG
Germany
EU contribution
€ 435 625
Address
David-gilly-strasse 1
14469 Potsdam
Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)
E4 COMPUTER ENGINEERING SPA
Italy
EU contribution
€ 301 531,25
Address
Via Martiri Della Liberta 66
42019 Scandiano
Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)
EIDGENOESSISCHE TECHNISCHE HOCHSCHULE ZUERICH
Switzerland
EU contribution
€ 303 000
Address
Raemistrasse 101
8092 Zuerich
Activity type
Higher or Secondary Education Establishments
FORSCHUNGSZENTRUM JULICH GMBH
Germany
EU contribution
€ 395 675
Address
Wilhelm Johnen Strasse
52428 Julich
Activity type
Research Organisations
METEOROLOGISK INSTITUTT
Norway
EU contribution
€ 165 375
Address
Henrik Mohns Plass 1
0313 Oslo
Activity type
Research Organisations
UNIVERSITE DU LUXEMBOURG
Luxembourg
EU contribution
€ 174 375
Address
2 Avenue De L'universite
4365 Esch-sur-alzette
Activity type
Higher or Secondary Education Establishments