Title :
Parallel A-Star Multiple Sequence Alignment with Locality-Sensitive Hash Functions
Author :
Sundfeld, Daniel ; Teodoro, George ; Magalhaes Alves de Melo, Alba Cristina
Author_Institution :
Dept. of Comput. Sci., Univ. of Brasilia, Brasilia, Brazil
Abstract :
In this paper, we propose and evaluate a parallel solution for the exact Multiple Sequence Alignment problem based on the A-Star algorithm. In our parallel solution, we use a multi-index data structure, templates and a locality-sensitive hash function. The results were collected in two machines (4 cores and 32 cores), with real and synthetic sequence sets ranging from 3 to 14 sequences. We show that our parallel solution executes 2.89× and 4.77× faster than a state-of-the-art parallel MSA tool, with a proportional increase in memory usage, when comparing 2 hard instances of the benchmark Bali base reference set 1.
Keywords :
data structures; parallel processing; locality-sensitive hash functions; multiindex data structure; parallel A-Star multiple sequence alignment; Data structures; Dictionaries; Heuristic algorithms; Instruction sets; Memory management; Nickel; Random access memory; A-Star; Multicore parallel programming; Multiple Sequence Alignment;
Conference_Titel :
Complex, Intelligent, and Software Intensive Systems (CISIS), 2015 Ninth International Conference on
Conference_Location :
Blumenau
Print_ISBN :
978-1-4799-8869-3
DOI :
10.1109/CISIS.2015.50