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Tensor Computations: Applications and Optimization (Dagstuhl Seminar 22101)

Authors: Paolo Bientinesi, David Ham, Furong Huang, Paul H. J. Kelly, P. (Saday) Sadayappan, and Edward Stow

Published in: Dagstuhl Reports, Volume 12, Issue 3 (2022)


Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 22101 "Tensor Computations: Applications and Optimization". Tensors are higher dimensional analogs of matrices, and represent a key data abstraction for many applications in computational science and data science. Widely used shared infrastructure exists for linear algebra, while, in contrast, for tensor computations, there is no consensus on standard building blocks. This Dagstuhl Seminar aimed to bring together users, and performance optimization specialists, to build such foundations. We present the abstracts of the 5 tutorials and 14 talks given. The working groups and their outcomes so far are then presented.

Cite as

Paolo Bientinesi, David Ham, Furong Huang, Paul H. J. Kelly, P. (Saday) Sadayappan, and Edward Stow. Tensor Computations: Applications and Optimization (Dagstuhl Seminar 22101). In Dagstuhl Reports, Volume 12, Issue 3, pp. 1-14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)


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@Article{bientinesi_et_al:DagRep.12.3.1,
  author =	{Bientinesi, Paolo and Ham, David and Huang, Furong and Kelly, Paul H. J. and Sadayappan, P. (Saday) and Stow, Edward},
  title =	{{Tensor Computations: Applications and Optimization (Dagstuhl Seminar 22101)}},
  pages =	{1--14},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2022},
  volume =	{12},
  number =	{3},
  editor =	{Bientinesi, Paolo and Ham, David and Huang, Furong and Kelly, Paul H. J. and Sadayappan, P. (Saday) and Stow, Edward},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagRep.12.3.1},
  URN =		{urn:nbn:de:0030-drops-172674},
  doi =		{10.4230/DagRep.12.3.1},
  annote =	{Keywords: Tensor, Optimisation, Linear Algebra, Compilers, Benchmark, Domain Specific Language}
}
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