Using graph partitioning for scalable distributed quantum molecular dynamics

Djidjev, H.N. and Hahn, G. and Mniszewski, S.M. and Negre, C.F.A. and Niklasson, A.M.N. (2019) Using graph partitioning for scalable distributed quantum molecular dynamics. Numerical Algorithms, 12 (9). ISSN 1017-1398

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Abstract

The simulation of the physical movement of multi-body systems at an atomistic level, with forces calculated from a quantum mechanical description of the electrons, motivates a graph partitioning problem studied in this article. Several advanced algorithms relying on evaluations of matrix polynomials have been published in the literature for such simulations. We aim to use a special type of graph partitioning to efficiently parallelize these computations. For this, we create a graph representing the zero–nonzero structure of a thresholded density matrix, and partition that graph into several components. Each separate submatrix (corresponding to each subgraph) is then substituted into the matrix polynomial, and the result for the full matrix polynomial is reassembled at the end from the individual polynomials. This paper starts by introducing a rigorous definition as well as a mathematical justification of this partitioning problem. We assess the performance of several methods to compute graph partitions with respect to both the quality of the partitioning and their runtime.

Item Type:
Journal Article
Journal or Publication Title:
Numerical Algorithms
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/2600/2604
Subjects:
ID Code:
137723
Deposited By:
Deposited On:
10 Oct 2019 09:10
Refereed?:
Yes
Published?:
Published
Last Modified:
01 Jul 2020 06:18