Parallel Longest Common SubSequence Analysis In Chapel
Document Type
Conference Proceeding
Publication Date
1-1-2023
Abstract
One of the most critical problems in the field of string algorithms is the longest common subsequence problem (LCS). The problem is NP-hard for an arbitrary number of strings but can be solved in polynomial time for a fixed number of strings. In this paper, we select a typical parallel LCS algorithm and integrate it into our large-scale string analysis algorithm library to support different types of large string analysis. Specifically, we take advantage of the high-level parallel language, Chapel, to integrate Lu and Liu's parallel LCS algorithm into Arkouda, an open-source framework. Through Arkouda, data scientists can easily handle large string analytics on the back-end high-performance computing resources from the front-end Python interface. The Chapel-enabled parallel LCS algorithm can identify the longest common subsequences of two strings, and experimental results are given to show how the number of parallel resources and the length of input strings can affect the algorithm's performance.
Identifier
85182596522 (Scopus)
ISBN
[9798350308600]
Publication Title
2023 IEEE High Performance Extreme Computing Conference Hpec 2023
External Full Text Location
https://doi.org/10.1109/HPEC58863.2023.10363472
Grant
CCF-2109988
Fund Ref
National Science Foundation
Recommended Citation
Vahidi, Soroush; Schieber, Baruch; Du, Zhihui; and Bader, David A., "Parallel Longest Common SubSequence Analysis In Chapel" (2023). Faculty Publications. 2181.
https://digitalcommons.njit.edu/fac_pubs/2181