Abstract: Database sequencing applications including sequence comparison, searching, and analysis are considered among the most computation power and time consumers. Heuristic algorithms suffer from sensitivity while traditional sequencing methods, require searching the whole database to find the most matched sequences, which requires high computation power and time. This paper introduces a dynamic programming technique based-on a measure of similarity between two sequential objects in the database using two components, namely frequency and mean. Additionally, database sequences that have the lowest scores in the comparison process were excluded such that the similarity algorithm between a query sequence and other database sequences is applied to meaningful parts of the database. The proposed technique was implemented and validated using a heterogeneous HW/SW FPGA-based embedded system platform. The implementation was partitioned into (1) hardware part (running on logic gates of FPGA) and (2) software part (running on ARM processor of FPGA). The validation study showed a significant reduction in computation time by accelerating the database sequencing processes by 60% comparing to traditional known methods.

Talal Bonny, “Heterogeneous HW/SW FPGA-Based Embedded System for Database Sequencing Applications” International Journal of Advanced Computer Science and Applications(IJACSA), 9(10), 2018. http://dx.doi.org/10.14569/IJACSA.2018.091030

@article{Bonny2018,
title = {Heterogeneous HW/SW FPGA-Based Embedded System for Database Sequencing Applications},
journal = {International Journal of Advanced Computer Science and Applications}
doi = {10.14569/IJACSA.2018.091030},
url = {http://dx.doi.org/10.14569/IJACSA.2018.091030},
year = {2018},
publisher = {The Science and Information Organization},
volume = {9},
number = {10},
author = {Talal Bonny},
}