4 Search Results for "Dönges, Saska"

Document
DOI: 10.4230/OASIcs.Manzini.6
Optimizing the Performance of the FM-Index for Large-Scale Data

Authors: Eddie Ferro and Christina Boucher

Published in: OASIcs, Volume 131, The Expanding World of Compressed Data: A Festschrift for Giovanni Manzini's 60th Birthday (2025)

Abstract
The FM-index is a fundamental data structure used in bioinformatics to efficiently search for strings and index genomes. However, the FM-index can pose computational challenges, particularly in the context of large-scale genomic datasets, due to the complexity of its underlying components and data encodings. In this paper, we present a comprehensive review of efficient variants of the FM-index and the encoding strategies used to improve performance. We examine hardware-accelerated techniques, such as memory-efficient data layouts and cache-aware structures, as well as software-level innovations, including algorithmic refinements and compact representations. The reviewed work demonstrates substantial gains in both speed and scalability, making methods that use the FM-index more practical for high-throughput genomic applications. By analyzing the trade-offs and design choices of these variants, we highlight how combining hardware-aware and software-centric strategies enables more efficient FM-index construction and usage across a range of bioinformatics tasks.
Cite as

Eddie Ferro and Christina Boucher. Optimizing the Performance of the FM-Index for Large-Scale Data. In The Expanding World of Compressed Data: A Festschrift for Giovanni Manzini's 60th Birthday. Open Access Series in Informatics (OASIcs), Volume 131, pp. 6:1-6:21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{ferro_et_al:OASIcs.Manzini.6,
  author =	{Ferro, Eddie and Boucher, Christina},
  title =	{{Optimizing the Performance of the FM-Index for Large-Scale Data}},
  booktitle =	{The Expanding World of Compressed Data: A Festschrift for Giovanni Manzini's 60th Birthday},
  pages =	{6:1--6:21},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-390-4},
  ISSN =	{2190-6807},
  year =	{2025},
  volume =	{131},
  editor =	{Ferragina, Paolo and Gagie, Travis and Navarro, Gonzalo},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.Manzini.6},
  URN =		{urn:nbn:de:0030-drops-239140},
  doi =		{10.4230/OASIcs.Manzini.6},
  annote =	{Keywords: FM-Index Acceleration, Run-Length Encoding, Suffix Array Optimization, Burrows-Wheeler Transform, Efficient Backward Search}
}
Document
DOI: 10.4230/LIPIcs.SEA.2025.15
Succinct Rank Dictionaries Revisited

Authors: Saska Dönges and Simon J. Puglisi

Published in: LIPIcs, Volume 338, 23rd International Symposium on Experimental Algorithms (SEA 2025)

Abstract
We study data structures for representing sets of m elements drawn from the universe [0..n-1] that support access and rank queries. A classical approach to this problem, foundational to the fields of succinct and compact data structures, is to represent the set as a bitvector X of n bits, where X[i] = 1 iff i is a member of the set. Our particular focus in this paper is on structures taking log₂{n choose m} + o(n) bits, which stem from the so-called RRR bitvector scheme (Raman et al., ACM Trans. Alg., 2007). In RRR bitvectors, X is conceptually divided into n/b blocks of b bits each. A block containing c 1 bits is then encoded using log₂ b + log₂{b choose c} bits, where log b bits are used to encode c, and log₂{b choose c} bits are used to say which of the {b choose c} possible combinations the block represents. In all existing RRR implementations the code assigned to a block is its lexicographical rank amongst the {b choose c} combinations of its class. In this paper we explore alternative non-lexicographical assignments of codes to blocks. We show these approaches can lead to faster query times and offer relevant space-time trade-offs in practice compared to state-of-the-art implementations (Gog and Petri, Software, Prac. & Exp., 2014) from the Succinct Data Structures Library.
Cite as

Saska Dönges and Simon J. Puglisi. Succinct Rank Dictionaries Revisited. In 23rd International Symposium on Experimental Algorithms (SEA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 338, pp. 15:1-15:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{donges_et_al:LIPIcs.SEA.2025.15,
  author =	{D\"{o}nges, Saska and Puglisi, Simon J.},
  title =	{{Succinct Rank Dictionaries Revisited}},
  booktitle =	{23rd International Symposium on Experimental Algorithms (SEA 2025)},
  pages =	{15:1--15:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-375-1},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{338},
  editor =	{Mutzel, Petra and Prezza, Nicola},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2025.15},
  URN =		{urn:nbn:de:0030-drops-232530},
  doi =		{10.4230/LIPIcs.SEA.2025.15},
  annote =	{Keywords: data structures, data compression, succinct data structures, compressed data structures, weighted de Bruijn sequence, text indexing, string algorithms}
}
Artifact
Software
DOI: 10.4230/artifacts.23794
saskeli/h0_bv

Authors: Saska Dönges

Abstract
Cite as

Saska Dönges. saskeli/h0_bv (Software, Source code). Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@misc{dagstuhl-artifact-23794,
   title = {{saskeli/h0\underlinebv}}, 
   author = {D\"{o}nges, Saska},
   note = {Software, swhId: \href{https://archive.softwareheritage.org/swh:1:dir:383ab8d9247150886cfacd830469e5e5bdd72551;origin=https://github.com/saskeli/h0_bv;visit=swh:1:snp:878cf1da86d9c50ee61fcc5f30894bac7d1d99e1;anchor=swh:1:rev:0d5eee708614ee42bfbe5ba1b1fd38cbd3ab005b}{\texttt{swh:1:dir:383ab8d9247150886cfacd830469e5e5bdd72551}} (visited on 2025-07-15)},
   url = {https://github.com/saskeli/h0_bv},
   doi = {10.4230/artifacts.23794},
}
Document
DOI: 10.4230/LIPIcs.SEA.2023.7
Simple Runs-Bounded FM-Index Designs Are Fast

Authors: Diego Díaz-Domínguez, Saska Dönges, Simon J. Puglisi, and Leena Salmela

Published in: LIPIcs, Volume 265, 21st International Symposium on Experimental Algorithms (SEA 2023)

Abstract
Given a string X of length n on alphabet σ, the FM-index data structure allows counting all occurrences of a pattern P of length m in O(m) time via an algorithm called backward search. An important difficulty when searching with an FM-index is to support queries on L, the Burrows-Wheeler transform of X, while L is in compressed form. This problem has been the subject of intense research for 25 years now. Run-length encoding of L is an effective way to reduce index size, in particular when the data being indexed is highly-repetitive, which is the case in many types of modern data, including those arising from versioned document collections and in pangenomics. This paper takes a back-to-basics look at supporting backward search in FM-indexes, exploring and engineering two simple designs. The first divides the BWT string into blocks containing b symbols each and then run-length compresses each block separately, possibly introducing new runs (compared to applying run-length encoding once, to the whole string). Each block stores counts of each symbol that occurs before the block. This method supports the operation rank_c(L, i) (i.e., count the number of times c occurs in the prefix L[1..i]) by first determining the block i/b in which i falls and scanning the block to the appropriate position counting occurrences of c along the way. This partial answer to rank_c(L, i) is then added to the stored count of c symbols before the block to determine the final answer. Our second design has a similar structure, but instead divides the run-length-encoded version of L into blocks containing an equal number of runs. The trick then is to determine the block in which a query falls, which is achieved via a predecessor query over the block starting positions. We show via extensive experiments on a wide range of repetitive text collections that these FM-indexes are not only easy to implement, but also fast and space efficient in practice.
Cite as

Diego Díaz-Domínguez, Saska Dönges, Simon J. Puglisi, and Leena Salmela. Simple Runs-Bounded FM-Index Designs Are Fast. In 21st International Symposium on Experimental Algorithms (SEA 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 265, pp. 7:1-7:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{diazdominguez_et_al:LIPIcs.SEA.2023.7,
  author =	{D{\'\i}az-Dom{\'\i}nguez, Diego and D\"{o}nges, Saska and Puglisi, Simon J. and Salmela, Leena},
  title =	{{Simple Runs-Bounded FM-Index Designs Are Fast}},
  booktitle =	{21st International Symposium on Experimental Algorithms (SEA 2023)},
  pages =	{7:1--7:16},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-279-2},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{265},
  editor =	{Georgiadis, Loukas},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2023.7},
  URN =		{urn:nbn:de:0030-drops-183579},
  doi =		{10.4230/LIPIcs.SEA.2023.7},
  annote =	{Keywords: data structures, efficient algorithms}
}
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