License: Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/DagRep.11.1.1
URN: urn:nbn:de:0030-drops-143481
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2021/14348/
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Brodal, Gerth Stølting ; Iacono, John ; Nebel, Markus E. ; Ramachandran, Vijaya
Weitere Beteiligte (Hrsg. etc.): Gerth Stølting Brodal and John Iacono and Markus E. Nebel and Vijaya Ramachandran

Scalable Data Structures (Dagstuhl Seminar 21071)

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dagrep_v011_i001_p001_21071.pdf (2 MB)

Abstract

This report documents the program and the outcomes of Dagstuhl Seminar 21071 "Scalable Data Structure". Even if the field of data structures is quite mature, new trends and limitations in computer hardware together with the ever-increasing amounts of data that need to be processed raise new questions with respect to efficiency and continuously challenge the existing models of computation. Thermal and electrical power constraints have caused technology to reach "the power wall" with stagnating single processor performance, meaning that all nontrivial applications need to address scalability with multiple processors, a memory hierarchy and other communication challenges. Scalable data structures are pivotal to this process since they form the backbone of the algorithms driving these applications. The extended abstracts included in this report contain both recent state of the art advances and lay the foundation for new directions within data structures research.

BibTeX - Entry

@Article{brodal_et_al:DagRep.11.1.1,
  author =	{Brodal, Gerth St{\o}lting and Iacono, John and Nebel, Markus E. and Ramachandran, Vijaya},
  title =	{{Scalable Data Structures (Dagstuhl Seminar 21071)}},
  pages =	{1--23},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2021},
  volume =	{11},
  number =	{1},
  editor =	{Brodal, Gerth St{\o}lting and Iacono, John and Nebel, Markus E. and Ramachandran, Vijaya},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2021/14348},
  URN =		{urn:nbn:de:0030-drops-143481},
  doi =		{10.4230/DagRep.11.1.1},
  annote =	{Keywords: algorithms, big data, data structures, GPU computing, large data sets, models of computation, parallel algorithms}
}

Keywords: algorithms, big data, data structures, GPU computing, large data sets, models of computation, parallel algorithms
Collection: DagRep, Volume 11, Issue 1
Issue Date: 2021
Date of publication: 14.07.2021

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