New method for parallel computation of Hessian matrix of conformational energy function in internal coordinates

Journal of Computational Chemistry
Shugo NakamuraKentaro Shimizu

Abstract

A new algorithm for parallel calculation of the second derivatives (Hessian) of the conformational energy function of biomolecules in internal coordinates is proposed. The basic scheme of this algorithm is the division of the entire calculation of the Hessian matrix (called "task") into subtasks and the optimization of the assignment of processors to each subtask by considering both the load balancing and reduction of the communication cost. A genetic algorithm is used for this optimization considering the dependencies between subtasks. We applied this method to a glutaminyl transfer RNA (Gln-tRNA) molecule for which the scalability of our previously developed parallel algorithm was significantly decreased when the large number of processors was used. The speedup for the calculation was 32.6 times with 60 processors, which is considerably better than the speedup for our previously reported parallel algorithm. The elapsed time for the calculation of subtasks, data sending, and data receiving was analyzed, and the effect of the optimization using the genetic algorithm is discussed.

References

Jun 1, 1983·Proceedings of the National Academy of Sciences of the United States of America·N GoT Nishikawa
Feb 11, 1994·Nucleic Acids Research·S Nakamura, J Doi
Dec 11, 1999·Nucleic Acids Research·H M BermanP E Bourne

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