%0 Conference Paper
%A Krajsek, Kai
%A Comito, Claudia
%A Götz, Markus
%A Hagemeier, Björn
%A Knechtges, Philipp
%A Siggel, Martin
%T The Helmholtz Analytics Toolkit (HeAT) - A Scientific Big Data Library for HPC -
%V 40
%C Jülich
%I Forschungszentrum Jülich GmbH Zentralbibliothek
%M FZJ-2019-06336
%@ 978-3-95806-392-1
%B IAS Series
%P 57-60
%D 2019
%< Proceedings
%X We present HeAT, a scientific big data librarysupporting transparent computation on HPC systems. HeATbuilds on top of PyTorch, which already provides many requiredfeatures like automatic differentiation, CPU and GPU support,linear algebra operations and basic MPI functionality as well asan imperative programming paradigm allowing fast prototypingessential in scientific research. These features are generalized toa distributed tensor with a NumPy-like interface allowing to port existing NumPy algorithms to HPC systems nearly effortlessly.
%B Extreme Data Workshop 2018
%C 18 Sep 2018 - 19 Sep 2018, Jülich (Germany)
Y2 18 Sep 2018 - 19 Sep 2018
M2 Jülich, Germany
%F PUB:(DE-HGF)8 ; PUB:(DE-HGF)7
%9 Contribution to a conference proceedingsContribution to a book
%U https://juser.fz-juelich.de/record/867721