TY - GEN
T1 - A shared memory method for enhancing the HTNGH algorithm performance
T2 - 2017 International Conference on Future Networks and Distributed Systems, ICFNDS 2017
AU - Abu-Hashem, Muhannad A.
AU - Uliyan, Diaa M.
AU - Abuarqoub, Abdelrahman
N1 - Publisher Copyright:
© 2017 Association for Computing Machinery.
PY - 2017/7/19
Y1 - 2017/7/19
N2 - In bioinformatics, pair-wise alignment plays a significant role insequence comparison by rating the similarities and distances between protein, DeoxyriboNucleic Acid (DNA), and RiboNucleic Acid (RNA)sequences. Sequence comparison considered as a key stone in building distance matrices.Due to the rapid growth of molecular databases, the need for faster sequence comparison and alignment has become anecessity.High performance computing impacthas increased in the last decade through providing many high performance architectures and tools. In this paper we present a parallel shared memory design for a dynamic programming algorithm named Hash Table-N-Gram-Hirschberg (HT-NGH) an extension of Hashing-N-Gram-Hirschberg (HNGH) and N-Gram-Hirschberg (NGH) algorithm, to speed up the sequence alignment construction process.The focus of the proposed method ison the transformation phase of HT-NGH algorithm since it takes% of HT-NGH overall run time.The experimental evaluation of the proposed parallel designshows an enhancement in the execution time and speedup without sacrificing the accuracy. However,the decomposition method might slightly slowdown the proposed algorithm due to the differences in performance between the processing units.
AB - In bioinformatics, pair-wise alignment plays a significant role insequence comparison by rating the similarities and distances between protein, DeoxyriboNucleic Acid (DNA), and RiboNucleic Acid (RNA)sequences. Sequence comparison considered as a key stone in building distance matrices.Due to the rapid growth of molecular databases, the need for faster sequence comparison and alignment has become anecessity.High performance computing impacthas increased in the last decade through providing many high performance architectures and tools. In this paper we present a parallel shared memory design for a dynamic programming algorithm named Hash Table-N-Gram-Hirschberg (HT-NGH) an extension of Hashing-N-Gram-Hirschberg (HNGH) and N-Gram-Hirschberg (NGH) algorithm, to speed up the sequence alignment construction process.The focus of the proposed method ison the transformation phase of HT-NGH algorithm since it takes% of HT-NGH overall run time.The experimental evaluation of the proposed parallel designshows an enhancement in the execution time and speedup without sacrificing the accuracy. However,the decomposition method might slightly slowdown the proposed algorithm due to the differences in performance between the processing units.
KW - Distance
KW - High-performance computing
KW - Pair-wise alignment
KW - Parallel design
KW - Sequence alignment
KW - Shared-memory
UR - http://www.scopus.com/inward/record.url?scp=85030474763&partnerID=8YFLogxK
U2 - 10.1145/3102304.3102318
DO - 10.1145/3102304.3102318
M3 - Conference contribution
AN - SCOPUS:85030474763
T3 - ACM International Conference Proceeding Series
BT - Proceedings of the International Conference on Future Networks and Distributed Systems, ICFNDS 2017
PB - Association for Computing Machinery
Y2 - 19 July 2017 through 20 July 2017
ER -