• Lars Arge and Mikkel Thorup get best paper award at ISACC 2013

  • MADALGO researchers publish in Nature Communications

  • Pankaj Agarwal appointed honorary doctor at Aarhus University

  • MADALGO Summer School 2013: Feature

  • Lars Arge in Danish TV News broadcast

  • MADALGO awarded grant from The Danish National Advanced Technology foundation

  • Danish Minister for Science, Innovation and Higher Education visits MADALGO

  • MADALGO selected as success story in a new DNRF publication

  • Lars Arge named 2012 ACM Fellow

  • Kasper receives Best Paper and Best Student Paper Award at STOC’12

Visitors to MADALGO


MADALGO in the media


Streaming algorithms are algorithms designed in a model where only one (or a small constant number of) sequential pass(es) over the data is (are) allowed. The goal is to solve a given problem using significantly less space than the input data size, while processing each data element as fast as possible. The model is motivated by the fact that when processing truly massive datasets, solutions requiring more than one sequential pass over the data are often infeasible (e.g. since random accesses to disk blocks are much slower than sequential accesses). Moreover, in some applications data simply has to be processed sequentially as it is generated.

In recent years, the streaming algorithms area has flourished as the discovery of several novel algorithmic techniques has enabled the enlargement of the class of problems with efficient streaming algorithms. Nevertheless, fundamental gaps remains in the understanding of what problems can be solved in the streaming model.The center considers a number of streaming problems and e.g. investigates the general applicability of already developed streaming algorithms techniques; several fundamental geometric and of graph problems is also considered in variants of the streaming model. Please refer to the centers annual reports for a discussion of obtained result.

MADALGO - Center for Massive Data Algorithmics, a Center of the Danish National Research Foundation / Department of Computer Science / Aarhus University