Handling biological sequence alignments on networked computing systems: A divide-and-conquer approach

Veeravalli, Bharadwaj; Wong, Han Min

doi:10.1016/j.jpdc.2009.04.014

Cited by 3 publications

(1 citation statement)

References 23 publications

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“…The backtracking is the reverse of the score calculation. It starts from the bottom right corner and proceeds towards the top left corner [15,17]. Table 2.…”

Section: Needleman-wunsch Algorithmmentioning

confidence: 99%

A Work Distribution Strategy for Global Sequence Alignment

Kalare¹,

Tembhurne²

2019

IJC

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The sequence alignment comprises to identify similarities and dissimilarities between two given sequences. In this paper, we propose a work distribution strategy for the implementation of DNA global sequence alignment. The main objective of this work is to minimize the execution time required for DNA global alignment of large biological sequences. The proposed approach dealt the issues with the memory optimizations and minimization of execution time. We considered the biological sequences of different size to fit into the global memory of the system. The proposed strategy is implemented in shared memory architecture using OpenMP programming for large biological sequences. Parallelization using OpenMP directive is relatively easy and execute the code fast. We experimented on the Dell Precision Tower 7910 with Intel Xeon processor with 32GB RAM and 28 CPU cores. The efficient use of global memory and cache memory optimization dominate the results of execution time. The results demonstrate the significantly high speed up using OpenMP as compared with other implementations.

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“…The backtracking is the reverse of the score calculation. It starts from the bottom right corner and proceeds towards the top left corner [15,17]. Table 2.…”

Section: Needleman-wunsch Algorithmmentioning

confidence: 99%