[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-83627-en":3,"doc-seo-83627-105":29,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":13,"seo_description":14,"update_tm":27,"read_time":28},83627,1649267921044,"Ava Thompson","https://us-avatar.wpscdn.com/avatar/1800007509477c92dfb?_k=1782875107921204101",8,"Research & Report","Faster Cache Efficient Pattern Matching for Deterministic Wheeler Pangenome Graphs","Pattern matching on strings underpins many computer science tasks and is central to Burrows-Wheeler transform (BWT) methods, where backward search enables near-optimal RAM performance and operates on compressed data. Backward search extends to Wheeler deterministic finite automata (DFAs) used in bioinformatics by indexing Wheeler pangenome graphs. However, BWT-style approaches incur many I/O operations with a worst-case cost proportional to pattern length. This work introduces a cache-friendly Wheeler DFA indexing algorithm that interleaves binary search with sequential scans, achieving up to 500× speedups.","arXiv :2607 .02 1 13v 1 [ cs .DS] 2 Jul 2026  \nFaster Cache-Efficient Pattern Matching for Deterministic Wheeler Pangenome Graphs  \nRiccardo Maso, Nicola Prezza, and Carlo Tosoni  \nDAIS, Ca’ Foscari University of Venice, Italy  \n{ riccardo.maso, nicola.prezza, [carlo.tosoni](carlo.tosoni}unive.it)[}](carlo.tosoni}unive.it)[unive.it](carlo.tosoni}unive.it)  \nAbstract  \nPattern matching on strings is regarded as one of the core operations in computer science.  \nAlthough researchers proposed several solutions to this problem, some of the most elegant and widely used approaches are based on the renowned Burrows-Wheeler transform (BWT) . The success of the BWT lies in its pattern matching algorithm known as backward search, which is not only near-optimal in the RAM model, but also runs directly on a compressed representation of the input string. More recently, the backward search has been generalized to Wheeler deterministic finite automata (DFAs), a subclass of standard DFAs, without losing its near-optimal time efficiency.  \nSimilarly to the case of strings, this pattern matching algorithm for Wheeler DFAs has found applications in bioinformatics, where researchers have shown that specific pangenome graphs of human chromosomes can be transformed into Wheeler DFAs and consequently indexed using this strategy. However, this BWT-based index on Wheeler DFAs inherited a significant drawback from the original backward search, namely the high number ofI/O operations triggered during the algorithm execution, which are in the worst-case lower-bounded by the length of the pattern. In this paper, we address this limitation by proposing the first cache-friendly algorithm specifically designed for Wheeler DFAs. Our new data structure reduces the number of I/O operations by employing a strategy analogous to the suffix array: it interleaves a binary search with fast sequential scans ofthe automaton. We empirically validate this new indexing strategy by running our algorithm on real-world Wheeler pangenome graphs. We show that while our data structure can use up to 15 times the space required by the backward search, it can also be 500 times faster and able to process a single character of the pattern in less than 3 ns.  \nAcknowledgements  \nWe would like to thank Daniel Puttini for providing us the pangenome graphs employed in the experimental section of the paper, and Davide Cenzato for fruitful discussions on the implementation details. All authors are funded by the European Union (ERC, REGINDEX, 101039208) . Views and opinions expressed are however those of the authors only and do not necessarily reflect those of the European Union or the European Research Council Executive Agency. Neither the European Union nor the granting authority can be held responsible for them.  \n1 Introduction  \nPattern matching, the process of identifying a pattern 􀀥 within a text 􀀩 , is a fundamental operation in computer science. This task finds applications in several domains, with bioinformatics being a notable example, where locating the occurrences of a pattern can be used to perform sequence alignment or  \nmap short sequencing reads to a large reference genome [ 18, 19] . Due to these reasons, this problem has been deeply studied in the literature where various solutions have been proposed. Some of these solutions pre-process the pattern 􀀥 to achieve search times proportional to the length of the text􀀩 [ 17], others reverse this paradigm by preprocessing the text 􀀩 and their query times depend on the length of the pattern 􀀥 [26, 21, 20] . This latter group includes the pattern matching algorithms based on the Burrows-Wheeler transform (BWT) [4], including the renowned FM-index [ 11] . The importance of the FM-index lies in its dual capability to provide efficient query time, while compressing the text into its empirical entropy. This pattern matching problem naturally generalizes to a (potentially infinite) collection of strings, where the objective is to ident","cbCaimBIXgj1oa7B","https://ap.wps.com/l/cbCaimBIXgj1oa7B","pdf",616891,1,17,"English","en",105,"# Abstract\n# Introduction","[{\"question\":\"What problem does the paper address in Wheeler DFA pattern matching?\",\"answer\":\"It addresses the high number of I/O operations (cache misses) inherited from BWT-style backward search, which in the worst case is lower-bounded by the pattern length.\"},{\"question\":\"How does the proposed algorithm improve cache efficiency?\",\"answer\":\"It reduces I/O by using a strategy analogous to the suffix array: interleaving binary search with fast sequential scans of the automaton.\"},{\"question\":\"What performance results are reported for real-world Wheeler pangenome graphs?\",\"answer\":\"The method can use up to 15× the space of backward search while achieving up to 500× faster runtimes, including processing a single pattern character in less than 3 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problem does the paper address in Wheeler DFA pattern matching?","Question",{"text":75,"@type":76},"It addresses the high number of I/O operations (cache misses) inherited from BWT-style backward search, which in the worst case is lower-bounded by the pattern length.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How does the proposed algorithm improve cache efficiency?",{"text":80,"@type":76},"It reduces I/O by using a strategy analogous to the suffix array: interleaving binary search with fast sequential scans of the automaton.",{"name":82,"@type":73,"acceptedAnswer":83},"What performance results are reported for real-world Wheeler pangenome graphs?",{"text":84,"@type":76},"The method can use up to 15× the space of backward search while achieving up to 500× faster runtimes, including processing a single pattern character in less than 3 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