Research on Genetic and Simulated Annealing Algorithm for Multip Sequence Alignment Based on Hybrid Parallel Computation

DOI

10.2991/amee-17.2017.42How to use a DOI?

Keywords

MOC(MPI;OpenMP,CUDA); hybrid parallel; genetic annealing; sequence alignment

Abstract

For the computational efficiency issues of multiple sequence alignment (MSA) caused by large amount of calculation. Based on the Hybrid Parallel model for MPI, OpenMP, CUDA, research on genetic and simulated annealing algorithm for multiple sequence alignment, to maximize computing capabilities is proposed.Analyzes the GSA-MSA algorithm for Implementation principle and characteristics of the serial algorithm, and excavates potential multi-level parallelism. To design and implement comprehensive multi-level parallel for the algorithm in a variety of hybrid parallel model, respectively designed the hybrid parallel algorithms MPI+OpenMP+CUDA within multiple nodes. Experimental results show that the hybrid parallel GSA-MSA algorithm has good speedup with keeping the sensitivity for serial algorithm.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yu Liu
AU  - Longsheng Li
PY  - 2017/09
DA  - 2017/09
TI  - Research on Genetic and Simulated Annealing Algorithm for Multip Sequence Alignment Based on Hybrid Parallel Computation
BT  - Proceedings of the 2017 2nd International Conference on Automation, Mechanical and Electrical Engineering (AMEE 2017)
PB  - Atlantis Press
SP  - 205
EP  - 208
SN  - 2352-5401
UR  - https://doi.org/10.2991/amee-17.2017.42
DO  - 10.2991/amee-17.2017.42
ID  - Liu2017/09
ER  -