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

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