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Research output: Contribution to Journal/Magazine › Journal article

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In: arxiv.org, 26.06.2019.

Research output: Contribution to Journal/Magazine › Journal article

Djidjev, HN, Hahn, G, Mniszewski, SM, Negre, CFA, Niklasson, AMN & Sardeshmukh, VB 2019, 'Using Graph Partitioning for Scalable Distributed Quantum Molecular Dynamics', *arxiv.org*.

Djidjev, H. N., Hahn, G., Mniszewski, S. M., Negre, C. F. A., Niklasson, A. M. N., & Sardeshmukh, V. B. (2019). Using Graph Partitioning for Scalable Distributed Quantum Molecular Dynamics. *arxiv.org*.

Djidjev HN, Hahn G, Mniszewski SM, Negre CFA, Niklasson AMN, Sardeshmukh VB. Using Graph Partitioning for Scalable Distributed Quantum Molecular Dynamics. arxiv.org. 2019 Jun 26.

@article{912ae14f8251435bab6bcf8a8cad62e5,

title = "Using Graph Partitioning for Scalable Distributed Quantum Molecular Dynamics",

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 in order 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. ",

keywords = "physics.comp-ph, quant-ph",

author = "Djidjev, {Hristo N.} and Georg Hahn and Mniszewski, {Susan M.} and Negre, {Christian F. A.} and Niklasson, {Anders M. N.} and Sardeshmukh, {Vivek B.}",

year = "2019",

month = jun,

day = "26",

language = "Undefined/Unknown",

journal = "arxiv.org",

}

TY - JOUR

T1 - Using Graph Partitioning for Scalable Distributed Quantum Molecular Dynamics

AU - Djidjev, Hristo N.

AU - Hahn, Georg

AU - Mniszewski, Susan M.

AU - Negre, Christian F. A.

AU - Niklasson, Anders M. N.

AU - Sardeshmukh, Vivek B.

PY - 2019/6/26

Y1 - 2019/6/26

N2 - 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 in order 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.

AB - 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 in order 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.

KW - physics.comp-ph

KW - quant-ph

M3 - Journal article

JO - arxiv.org

JF - arxiv.org

ER -