MAELSTROM
MAchinE Learning for Scalable meTeoROlogy and cliMate
Duration
April 2021 to March 2024
Contact
Prof. Dr. Martin Schultz
Head of research group Earth System Data Exploration and co-lead of division Large Scale Data Science, University professor in Computational Earth System Science at the University of Cologne PI in Helmholtz Information Program 1, Topic 1 (Topic Board Member)
Building 14.14 / Room 4010
+49 2461/61-96870
E-Mail
Dr. Andreas Herten
Co-Lead of division Novel System Architecture design, head of ATML Accelerating Devices
Building 16.3 / Room 228
+49 2461/61-1825
E-MailMAELSTROM will develop Europe’s supercomputing architecture of the future and enable the Weather and Climate (W&C) community to make efficient use of new Machine Learning (ML) capabilities on exascale supercomputers. MAELSTROM will implement a co-design cycle that will bring together system designers, ML experts and W&C domain scientists to develop compute system designs, a software framework, and large-scale ML applications that are customised for W&C science.
MAELSTROM will connect the current developments of next-generation high-performance computer(HPC) architectures and high-performance data analysics (HPDA), and the needs of the W&C community for customised ML solutions that can make use of exascale supercomputers. This is realised via the joint development of artificial intelligence(AI) applications for W&C science and the design of HPC solutions that perform optimally for those applications. MAELSTROM will also develop the software environment that is required to efficiently train and apply ML solutions on exascale supercomputers using data sets of the size
of tens of terabytes and develop dedicated concepts for data processing.
