Tiling Dynamic Programming Computations to Maximize Parallelism

The Longest Common Subsequence (LCS) problem is fundamental in bioinformatics and file difference comparison algorithms, yet its conventional dynamic programming (DP) approach has a time complexity of \mathcal{O}(m n) , making it computationally expensive for large-scale inputs. Parallelization offe...

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Bibliographic Details

Published in:	2025 IEEE International Conference on High Performance Computing and Communications (HPCC) pp. 456 - 463
Main Authors:	Sun, YanTao, Wang, Miaomiao, Guan, Jian, Li, Lin, Wang, Li, Liu, Guanjun
Format:	Conference Proceeding
Language:	English
Published:	IEEE 13.08.2025
Subjects:	cache sensitivity Computational efficiency Costs Dynamic programming Heuristic algorithms High performance computing longest common subsequence Parallel processing parallelization Partitioning algorithms semaphore Sensitivity Synchronization Time complexity
Online Access:	Get full text
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