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researcher

Peter Sanders

4 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • last author2

Across the 3 of 4 papers where every author was matched, so the position is known.

fields
  • cs.DC2
  • cs.DS2
ORCID 0000-0003-3330-9349
same name
  • Peter Sanders — 8 papers, h 5
  • Peter Sanders — 5 papers, h 2
  • Peter Sanders — 3 papers, h 1
  • Peter Sanders — 3 papers, h 3
  • Peter Sanders — 2 papers, h 4
  • Peter Sanders — 2 papers, h 1

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20162024
most citedThrill: High-Performance Algorithmic Distributed Batch Data Processing with C++

9 citations · 10 across the 4 of their papers we have counts for

collaborators

4 papers

cs.DS2024★ 1 cited

Brief Announcement: Parallel Construction of Bumped Ribbon Retrieval

Matthias Becht, Hans-Peter Lehmann, Peter Sanders

A retrieval data structure stores a static function f : S -> {0,1}^r . For all x in S, it returns the r-bit value f(x), while for other inputs it may return an arbitrary result. Th…

cs.DC2024

Brief Announcement: Distributed Unconstrained Local Search for Multilevel Graph Partitioning

Peter Sanders, Daniel Seemaier

Partitioning a graph into blocks of roughly equal weight while cutting only few edges is a fundamental problem in computer science with numerous practical applications. While share…

cs.DS2020

Engineering Faster Sorters for Small Sets of Items

Timo Bingmann, Jasper Marianczuk, Peter Sanders

Sorting a set of items is a task that can be useful by itself or as a building block for more complex operations. That is why a lot of effort has been put into finding sorting algo…

cs.DC2016★ 9 cited

Thrill: High-Performance Algorithmic Distributed Batch Data Processing with C++

Timo Bingmann, Michael Axtmann, Emanuel Jöbstl +7

We present the design and a first performance evaluation of Thrill -- a prototype of a general purpose big data processing framework with a convenient data-flow style programming i…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.