title: Local Møller-Plesset Perturbation Theory:  A Massively Parallel Algorithm.
abstract: A massively parallel algorithm is presented for computation of energies with local second-order Møller-Plesset (LMP2) perturbation theory. Both the storage requirement and the computational time scale linearly with the molecular size. The parallel algorithm is designed to be scalable, employing a distributed data scheme for the two-electron integrals, avoiding communication bottlenecks, and distributing tasks in all computationally significant steps. A sparse data representation and a set of generalized contraction routines have been developed to allow efficient massively parallel implementation using distributed sparse multidimensional arrays. High parallel efficiency of the algorithm is demonstrated for applications employing up to 100 processors.
authors.affiliation: Sandia National Laboratories, P.O. Box 969, Livermore, California 94551.
authors.forename: Ida M B
authors.initials: IM
authors.lastname: Nielsen
authors.affiliation: Sandia National Laboratories, P.O. Box 969, Livermore, California 94551.
authors.forename: Curtis L
authors.initials: CL
authors.lastname: Janssen