Significance of randomness in P-RnaPredict - a parallel evolutionary algorithm for RNA folding

Author

Wiese, Kay C. ; Hendriks, Andrew ; Deschenes, Alain ; Youssef, B.B.

Author_Institution

Sch. of Comput. Sci., Simon Fraser Univ., Surrey, BC

Volume

1

fYear

2005

fDate

5-5 Sept. 2005

Firstpage

467

Abstract

This paper presents an extension to P-RnaPredict, a parallel evolutionary algorithm (EA) for RNA folding. The impact of three pseudorandom number generators (PRNGs) on the EA´s performance is evaluated. The generators tested included the C standard library PRNG RAND, a parallelized multiplicative congruential generator (MCG), and a parallelized Mersenne Twister (MT). P-RnaPredict was implemented using the message passing interface (MPI) and tested on a 128 node Beowulf cluster. The PRNG comparison testing was performed with four known structures that are 118, 122, 543, and 556 nucleotides in length. PRNGs effects were investigated and predicted structures compared to known structures

Keywords

biology computing; evolutionary computation; macromolecules; message passing; parallel algorithms; random number generation; software libraries; Beowulf cluster; C standard library; P-RnaPredict development; RNA; message passing interface; multiplicative congruential generator; parallel evolutionary algorithm; parallelized Mersenne Twister; pseudorandom number generator; Concurrent computing; Convergence; Evolutionary computation; Libraries; Molecular biophysics; Nuclear magnetic resonance; Predictive models; RNA; Testing; Thermodynamics;

fLanguage

English

Publisher

ieee

Conference_Titel

Evolutionary Computation, 2005. The 2005 IEEE Congress on

Conference_Location

Edinburgh, Scotland

Print_ISBN

0-7803-9363-5

Type

conf

DOI

10.1109/CEC.2005.1554720

Filename

1554720