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Parallelization and scalability analysis of inverse factorization using the Chunks and Tasks programming model
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
2019 (English)In: Computing Research Repository, no 1901.07993Article in journal (Other academic) Submitted
Place, publisher, year, edition, pages
2019. no 1901.07993
National Category
Computational Mathematics Computer Sciences
Identifiers
URN: urn:nbn:se:uu:diva-381329OAI: oai:DiVA.org:uu-381329DiVA, id: diva2:1302984
Projects
eSSENCEAvailable from: 2019-01-24 Created: 2019-04-08 Last updated: 2019-04-09Bibliographically approved
In thesis
1. Inverse factorization in electronic structure theory: Analysis and parallelization
Open this publication in new window or tab >>Inverse factorization in electronic structure theory: Analysis and parallelization
2019 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

This licentiate thesis is a part of an effort to run large electronic structure calculations in modern computational environments with distributed memory. The ultimate goal is to model materials consisting of millions of atoms at the level of quantum mechanics. In particular, the thesis focuses on different aspects of a computational problem of inverse factorization of Hermitian positive definite matrices. The considered aspects are numerical properties of the algorithms and parallelization. Not only is an efficient and scalable computation of inverse factors necessary in order to be able to run large scale electronic computations based on the Hartree–Fock or Kohn–Sham approaches with the self-consistent field procedure, but it can be applied more generally for preconditioner construction.

Parallelization of algorithms with unknown load and data distributions requires a paradigm shift in programming. In this thesis we also discuss a few parallel programming models with focus on task-based models, and, more specifically, the Chunks and Tasks model.

Place, publisher, year, edition, pages
Uppsala University, 2019
Series
Information technology licentiate theses: Licentiate theses from the Department of Information Technology, ISSN 1404-5117 ; 2019-002
National Category
Computational Mathematics
Research subject
Scientific Computing
Identifiers
urn:nbn:se:uu:diva-381333 (URN)
Supervisors
Projects
eSSENCE
Available from: 2019-05-07 Created: 2019-04-08 Last updated: 2019-05-22Bibliographically approved

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https://arxiv.org/abs/1901.07993

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Rudberg, EliasRubensson, Emanuel H.

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