The project investigates the use of different hardware platforms (traditional multicore processors, ARM processors, graphics cards, etc.) for the efficient implementation of numerical linear algebra (NLA) algorithms. Funded by: ANII and MPI Magdeburg Funding period: 2018-2023 Contact: Peter Benner, Pablo Ezzatti (FING Uruguay)
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In the new initiative of the Max Planck Society and MaxNet on Big-Data-Driven Materials Science (abbreviated BiGmax), ten institutes of the Max Planck Society and Humboldt-Universität Berlin combine their know-how in data-driven material science. The aim is a better use of the possibilities associated with analyzing large amounts of data. Funded by: Max Planck Society Funding period: 2017-2022 Contact:Peter Benner, Matthias Scheffler (FHI Berlin) Project members: Pawan Goyal, Kirandeep Kour
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Partners: TU Chemnitz (Prof. Helmberg, Prof. Streif), TU Ilmenau (Prof. Worthmann) Funded by: BMBF Funding period: 2018-2021 Contact: Sara Grundel Researcher: Tobias Ritschel
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Partner: PD Dr. Averkov, Prof. Benner, Prof. Findeisen, Jun.-Prof. Kahle, Prof. Kaibel, Prof. Kirch, Prof. Nill, Prof. Pott, Prof. Sager, Prof. Schwabe Funded by: DFG Funding period: since 2017 Contact: Peter Benner, Sebastian Sager (OvGU) Associates: Sara Grundel, Jan Heiland, Shaima Monem Abdelhafez, Roman Weinhandl, Steffen Werner
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Partners: Fraunhofer SCAI, Fraunhofer ITWM, TU Berlin, TU Darmstadt, HU Berlin, Uni Trier, PSI AG, Venios GmbH Funded by: BMWi Funding period: 2016-2021 Contact: Peter Benner, Sara Grundel Researcher: Neeraj Sarna, Christian Himpe Mathematical Key Technologies for Evolving Energy Grids
Partners: TU Chemnitz, TU Dresden, RWTH Aachen, Fraunhofer (IWU, IPT) Funded by: DFG Funding period: 2011-2023 Contact: Peter Benner, Jens Saak Researcher: Norman Lang (2011-2019), Julia Vettermann
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