An energy-efficient parallel multigrid methods for multi-core CPU platforms and HPC clusters
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BiBTeXSEEK ID: https://publications.h-its.org/publications/251
Research Groups: Data Mining and Uncertainty Quantification
Publication type: Journal
Journal: EMCL Preprint Series
Citation: EMCL Preprint Series, vol. 03
Date Published: 2017
Registered Mode: imported from a bibtex file
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Created: 7th Sep 2019 at 10:40
Last updated: 5th Mar 2024 at 21:23
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Research Groups: Data Mining and Uncertainty Quantification
Institutions: Heidelberg Institute for Theoretical Studies
Research Groups: Scientific Databases and Visualisation, Astroinformatics, Data Mining and Uncertainty Quantification, Groups and Geometry, Natural Language Processing, Computational Molecular Evolution, Computational Carbon Chemistry, Physics of Stellar Objects, Playground, Molecular and Cellular Modeling, Stellar Evolution Theory, SIMPLAIX
Institutions: Heidelberg Institute for Theoretical Studies
Public web page: Not specified
