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Branch Prediction Analysis of Morris-Pratt and Knuth-Morris-Pratt Algorithms

Authors Cyril Nicaud , Carine Pivoteau, Stéphane Vialette

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ACM Subject Classification
  • Theory of computation → Design and analysis of algorithms
Keywords
  • Pattern matching
  • branch prediction
  • transducers
  • average case complexity
  • Markov chains

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Abstract

We investigate the classical Morris-Pratt and Knuth-Morris-Pratt pattern matching algorithms from the perspective of computer architecture, focusing on the effects of incorporating a simple branch prediction mechanism into the computational model. Assuming a fixed pattern and a random text, we derive precise estimates for the number of branch mispredictions incurred by these algorithms when using local predictors. Our analysis relies on tools from automata theory and Markov chains, offering a theoretical framework that can be extended to other text processing algorithms and more sophisticated branch prediction strategies.

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Cyril Nicaud, Carine Pivoteau, and Stéphane Vialette. Branch Prediction Analysis of Morris-Pratt and Knuth-Morris-Pratt Algorithms. In 36th Annual Symposium on Combinatorial Pattern Matching (CPM 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 331, pp. 8:1-8:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025) https://doi.org/10.4230/LIPIcs.CPM.2025.8

Author Details

Cyril Nicaud
  • Univ Gustave Eiffel, CNRS, LIGM, F-77454 Marne-la-Vallée, France
Carine Pivoteau
  • Univ Gustave Eiffel, CNRS, LIGM, F-77454 Marne-la-Vallée, France
Stéphane Vialette
  • Univ Gustave Eiffel, CNRS, LIGM, F-77454 Marne-la-Vallée, France

References

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