2026-08-17T00:09:34Z https://drops.dagstuhl.de/oai

oai:drops-oai.dagstuhl.de:23261 2025-10-27T10:36:24Z ddc:004 open_access

Elias-Fano Compression for Space-Efficient Rank and Select Structures Hough, Lannie Dalton Bhatele, Abhinav rank and select cache-aware succinct data structures bit vector Bit vectors are an important component in many data structures. Such data structures are used in a variety of applications and domains including databases, search engines, and computational biology. Many use cases depend on being able to perform rank and/or select queries on the bit vector. No existing rank and select structure enabling these queries is most efficient both for space and for time; there is a tradeoff between the two. In practice, the smallest rank and select data structures, cs-poppy and pasta-flat, impose a space overhead of 3.51%, or 3.125% if only rank needs to be supported. In this paper, we present a new data structure, orzo, which reduces the overhead of the rank component by a further 26.5%. We preserve desirable cache-centric design decisions made in prior work, which allows us to minimize the performance penalty of creating a smaller data structure. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Lannie Dalton Hough and Abhinav Bhatele 2025 Is Part Of LIPIcs, Volume 338, 23rd International Symposium on Experimental Algorithms (SEA 2025) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/LIPIcs.SEA.2025.23 urn:nbn:de:0030-drops-232617 https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2025.23 eng https://creativecommons.org/licenses/by/4.0/legalcode