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pro vyhledávání: '"Christian Löbbert"'
Autor:
Christian Löbbert, Lars Grasedyck
Publikováno v:
Advances in Mechanics and Mathematics ISBN: 9783030024864
High-dimensional tensors of low rank can be represented in the hierarchical Tucker format (HT format) with a complexity which is linear in the dimension d of the tensor. We developed parallel algorithms which perform arithmetic operations on tensors
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::60f3c7f0e0029e98af3b65a2b5f0d581
https://doi.org/10.1007/978-3-030-02487-1_16
https://doi.org/10.1007/978-3-030-02487-1_16
Autor:
Ronald Kriemann, Lars Grasedyck, Konstantinos Xylouris, Gabriel Wittum, Christian Löbbert, Arne Nägel
Publikováno v:
Computing and Visualization in Science. 17:67-78
We consider the problem of uncertainty quantification for extreme scale parameter dependent problems where an underlying low rank property of the parameter dependency is assumed. For this type of dependency the hierarchical Tucker format offers a sui
Space and Time Parallel Multigrid for Optimization and Uncertainty Quantification in PDE Simulations
Autor:
Volker Schulz, Martin Siebenborn, Uwe Küster, Arne Nägel, Gabriel Wittum, Pietro Benedusi, Björn Dick, Christian Löbbert, Rolf Krause, Lars Grasedyck
Publikováno v:
Lecture Notes in Computational Science and Engineering ISBN: 9783319405261
Software for Exascale Computing
Software for Exascale Computing
In this article we present a complete parallelization approach for simulations of PDEs with applications in optimization and uncertainty quantification. The method of choice for linear or nonlinear elliptic or parabolic problems is the geometric mult
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4cf61eef451c226591eaab1dd9e60ed5
https://doi.org/10.1007/978-3-319-40528-5_23
https://doi.org/10.1007/978-3-319-40528-5_23
Autor:
Lars Grasedyck, Christian Löbbert
Publikováno v:
Numerical Linear Algebra with Applications. 25:e2174
We consider tensors in the Hierarchical Tucker format and suppose the tensor data to be distributed among several compute nodes. We assume the compute nodes to be in a one-to-one correspondence with the nodes of the Hierarchical Tucker format such th