Hardware-Software Codesign Based Accelerated and Reconfigurable Methodology for String Matching in Computational Bioinformatics Applications.

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  • May 4, 2025
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Hardware-Software Codesign Based Accelerated and Reconfigurable Methodology for String Matching in Computational Bioinformatics Applications.

Autor: Gudur, Venkateshwarlu Y.; Acharyya, Amit

Publication year: 2020

IEEE/ACM transactions on computational biology and bioinformatics

issn:1557-9964 1545-5963

doi: 10.1109/TCBB.2018.2885296


Abstract:

Research for new technologies and methods in computational bioinformatics has resulted in many folds biological data generation. To cope with the ever increasing growth of biological data, there is a need for accelerated solutions in various domains of computational bioinformatics. In these domains, string matching is a most versatile operation performed at various stages of the computational pipeline. For search patterns that are updated with time, there is a need for accelerated and reconfigurable string matching to perform faster searching in the ever-growing biological databases. In this paper, we have proposed an accelerated and real-time reconfigurable methodology for string matching using hardware-software codesign. Using state of the art field programmable gate arrays, we have proposed a complete system-on-chip solution for applications that require accelerated as well as real-time reconfigurable string matching. The proposed methodology is the first of its kind novel approach for high-speed string matching that also supports quick reconfiguration by patterns changing with time. It is verified at the string matching stage of protein identification. Experimental results show that the architectures designed using our proposed methodology are 4X faster than state-of-the-art software implementation running on a workstation and 1.5X-4X faster than hardware accelerators available in the literature.

Language: eng

Rights:

Pmid: 30530335

Tags: *Algorithms; Computers; *Software; Computational Biology/*methods; Databases, Genetic; Proteins/chemistry/genetics

Link: https://pubmed.ncbi.nlm.nih.gov/30530335/

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