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GPU Parallelization of the Finite Element Toolkit Gascoigne 3d

Authors: Liebchen, Manuel; Kaya, Utku; Lessig, Christian; Richter, Thomas;

GPU Parallelization of the Finite Element Toolkit Gascoigne 3d

Abstract

These scripts accompany the publication An adaptive finite element multigrad solver using GPU acceleration by Manuel Liebchen, Utku Kaya, Christian Lessig and Thomas Richter. See the preprint on arXiv. This is the GPU parallelization of the Gascoigne 3d multigrid method. Gascoigne 3d is a multi-purpose finite element toolkit, see its website for a brief description and the release on Zenodo. The most up-to-date version of Gascoigne 3d is hostet on a GitLab Server. Installation Gascoigne 3d is based on cmake. External dependencies are SuiteSparse and Eigen. A brief description for installing Gascoigne is found on its website. To activate CUDA for GPU acceleration you have to set the flag USE_CUDA in cmake. Multithreading is controlled by the flag WITH_THREADS. Test problems Besides the library, a couple of test problems is compiled. Sources are found in GASCOIGNE/examples/ and the binaries are within the build directory in BUILD/bin/. The test-problems must be started from the directories GASCOIGNE/examples/.../ as parameter data and a mesh is read from the disc. The test-cases reproduce the data used in the numerical section of the manuscript An adaptive finite element multigrad solver using GPU acceleration.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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Average