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Hauptverfasser: Merson, Jacob, Picu, Catalin, Shephard, Mark S.
Format: Preprint
Veröffentlicht: 2023
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Online-Zugang:https://arxiv.org/abs/2306.09427
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author Merson, Jacob
Picu, Catalin
Shephard, Mark S.
author_facet Merson, Jacob
Picu, Catalin
Shephard, Mark S.
contents This article presents MuMFiM, an open source application for multiscale modeling of fibrous materials on massively parallel computers. MuMFiM uses two scales to represent fibrous materials such as biological network materials (extracellular matrix, connective tissue, etc.). It is designed to make use of multiple levels of parallelism, including distributed parallelism of the macro and microscales as well as GPU accelerated data-parallelism of the microscale. Scaling results of the GPU accelerated microscale show that solving microscale problems concurrently on the GPU can lead to a 1000x speedup over the solution of a single RVE on the GPU. In addition, we show nearly optimal strong and weak scaling results of MuMFiM on up to 128 nodes of AiMOS (Rensselaer Polytechnic Institute) which is composed of IBM AC922 nodes with 6 Volta V100 GPU and 2 20 core Power 9 CPUs each. We also show how MuMFiM can be used to solve problems of interest to the broader engineering community, in particular providing an example of the facet capsule ligament (FCL) of the human spine undergoing uniaxial extension.
format Preprint
id arxiv_https___arxiv_org_abs_2306_09427
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle A new open source framework for multiscale modeling of fibrous materials on heterogeneous supercomputers
Merson, Jacob
Picu, Catalin
Shephard, Mark S.
Distributed, Parallel, and Cluster Computing
Mathematical Software
This article presents MuMFiM, an open source application for multiscale modeling of fibrous materials on massively parallel computers. MuMFiM uses two scales to represent fibrous materials such as biological network materials (extracellular matrix, connective tissue, etc.). It is designed to make use of multiple levels of parallelism, including distributed parallelism of the macro and microscales as well as GPU accelerated data-parallelism of the microscale. Scaling results of the GPU accelerated microscale show that solving microscale problems concurrently on the GPU can lead to a 1000x speedup over the solution of a single RVE on the GPU. In addition, we show nearly optimal strong and weak scaling results of MuMFiM on up to 128 nodes of AiMOS (Rensselaer Polytechnic Institute) which is composed of IBM AC922 nodes with 6 Volta V100 GPU and 2 20 core Power 9 CPUs each. We also show how MuMFiM can be used to solve problems of interest to the broader engineering community, in particular providing an example of the facet capsule ligament (FCL) of the human spine undergoing uniaxial extension.
title A new open source framework for multiscale modeling of fibrous materials on heterogeneous supercomputers
topic Distributed, Parallel, and Cluster Computing
Mathematical Software
url https://arxiv.org/abs/2306.09427