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A Unified and Memory Efficient Framework for Simulating Mechanical Behavior of Carbon Nanotubes

Burger, Michael and Bischof, Christian and Schröppel, Christian and Wackerfuß, Jens (2015):
A Unified and Memory Efficient Framework for Simulating Mechanical Behavior of Carbon Nanotubes.
In: Proceedings of the International Conference on Computational Science, Reykjavik, Iceland, 15, [Conference or Workshop Item]

Abstract

Carbon nanotubes possess many interesting properties, which make them a promising material for a variety of applications. In this paper, we present a unified framework for the simulation of the mechanical behavior of carbon nanotubes. It allows the creation, simulation and visualization of these structures, extending previous work by the research group ”MISMO” at TU Darmstadt. In particular, we develop and integrate a new matrix-free iterative solving procedure, employing the conjugate gradient method, that drastically reduces the memory consumption in comparison to the existing approaches. The increase in operations for the memory saving approach is partially offset by a well scaling shared-memory parallelization. In addition the hotspots in the code have been vectorized. Altogether, the resulting simulation framework enables the simulation of complex carbon nanotubes on commodity multicore desktop computers.

Item Type: Conference or Workshop Item
Erschienen: 2015
Creators: Burger, Michael and Bischof, Christian and Schröppel, Christian and Wackerfuß, Jens
Title: A Unified and Memory Efficient Framework for Simulating Mechanical Behavior of Carbon Nanotubes
Language: English
Abstract:

Carbon nanotubes possess many interesting properties, which make them a promising material for a variety of applications. In this paper, we present a unified framework for the simulation of the mechanical behavior of carbon nanotubes. It allows the creation, simulation and visualization of these structures, extending previous work by the research group ”MISMO” at TU Darmstadt. In particular, we develop and integrate a new matrix-free iterative solving procedure, employing the conjugate gradient method, that drastically reduces the memory consumption in comparison to the existing approaches. The increase in operations for the memory saving approach is partially offset by a well scaling shared-memory parallelization. In addition the hotspots in the code have been vectorized. Altogether, the resulting simulation framework enables the simulation of complex carbon nanotubes on commodity multicore desktop computers.

Volume: 15
Divisions: 20 Department of Computer Science
20 Department of Computer Science > Scientific Computing
Exzellenzinitiative
Zentrale Einrichtungen
Zentrale Einrichtungen > University IT-Service and Computing Centre (HRZ) > Hochleistungsrechner
Zentrale Einrichtungen > University IT-Service and Computing Centre (HRZ)
Exzellenzinitiative > Graduate Schools > Graduate School of Computational Engineering (CE)
Exzellenzinitiative > Graduate Schools
Event Title: Proceedings of the International Conference on Computational Science
Event Location: Reykjavik, Iceland
Date Deposited: 26 Mar 2015 12:47
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Alternative keywordsLanguage
parallelization, vectorization, simulation, software engineering, carbon nanotubes, matrix- free solverEnglish
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