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Scalable Data Structures (Dagstuhl Seminar 21071) Brodal, Gerth Stølting Iacono, John Nebel, Markus E. Ramachandran, Vijaya algorithms big data data structures GPU computing large data sets models of computation parallel algorithms 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. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Gerth Stølting Brodal and John Iacono and Markus E. Nebel and Vijaya Ramachandran 2021 Is Part Of Dagstuhl Reports, Volume 11, Issue 1 (2021) Article Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/DagRep.11.1.1 urn:nbn:de:0030-drops-143481 https://drops.dagstuhl.de/entities/document/10.4230/DagRep.11.1.1 eng https://creativecommons.org/licenses/by/4.0/legalcode