Massively Parallel Finite Element Programming

Timo Heister; Martin Kronbichler; Wolfgang Bangerth

Massively Parallel Finite Element Programming

Timo Heister, Martin Kronbichler, Wolfgang Bangerth

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Today's large finite element simulations require parallel algorithms to scale on clusters with thousands or tens of thousands of processor cores. We present data structures and algorithms to take advantage of the power of high performance computers in generic finite element codes. Existing generic finite element libraries often restrict the parallelization to parallel linear algebra routines. This is a limiting factor when solving on more than a few hundreds of cores. We describe routines for distributed storage of all major components coupled with efficient, scalable algorithms. We give an overview of our effort to enable the modern and generic finite element library deal. II to take advantage of the power of large clusters. In particular, we describe the construction of a distributed mesh and develop algorithms to fully parallelize the finite element calculation. Numerical results demonstrate good scalability.

Original language	English (US)
Title of host publication	17th European MPI Users Group Meeting
Publisher	SPRINGER-VERLAG BERLIN
Pages	122-+
State	Published - 2010
Externally published	Yes

Bibliographical note

KAUST Repository Item: Exported on 2022-06-27
Acknowledged KAUST grant number(s): KUS-C1-016-04
Acknowledgements: Timo Heister is partly supported by the German Research Foundation (DFG) through GK 1023. Martin Kronbichler is supported by the Graduate School in Mathematics and Computation (FMB). Wolfgang Bangerth was partially supported by Award No. KUS-C1-016-04 made by King Abdul-lah University of Science and Technology (KAUST), by a grant from the NSF-funded Computational Infrastructure in Geodynamics initiative through Award No. EAR-0426271, and by an Alfred P. Sloan Research Fellowship. The computations were done on the Hurr3 cluster of the Institute for Applied Mathematics and Computational Science (IAMCS) at Texas A&M University. Hurr is supported by Award No. KUS-C1-016-04 made by King Abdullah Uni-versity of Science and Technology (KAUST).
This publication acknowledges KAUST support, but has no KAUST affiliated authors.

Cite this

@inproceedings{eb52819857f44175a5df5663a959fa7b,

title = "Massively Parallel Finite Element Programming",

abstract = "Today's large finite element simulations require parallel algorithms to scale on clusters with thousands or tens of thousands of processor cores. We present data structures and algorithms to take advantage of the power of high performance computers in generic finite element codes. Existing generic finite element libraries often restrict the parallelization to parallel linear algebra routines. This is a limiting factor when solving on more than a few hundreds of cores. We describe routines for distributed storage of all major components coupled with efficient, scalable algorithms. We give an overview of our effort to enable the modern and generic finite element library deal. II to take advantage of the power of large clusters. In particular, we describe the construction of a distributed mesh and develop algorithms to fully parallelize the finite element calculation. Numerical results demonstrate good scalability.",

author = "Timo Heister and Martin Kronbichler and Wolfgang Bangerth",

note = "KAUST Repository Item: Exported on 2022-06-27 Acknowledged KAUST grant number(s): KUS-C1-016-04 Acknowledgements: Timo Heister is partly supported by the German Research Foundation (DFG) through GK 1023. Martin Kronbichler is supported by the Graduate School in Mathematics and Computation (FMB). Wolfgang Bangerth was partially supported by Award No. KUS-C1-016-04 made by King Abdul-lah University of Science and Technology (KAUST), by a grant from the NSF-funded Computational Infrastructure in Geodynamics initiative through Award No. EAR-0426271, and by an Alfred P. Sloan Research Fellowship. The computations were done on the Hurr3 cluster of the Institute for Applied Mathematics and Computational Science (IAMCS) at Texas A&M University. Hurr is supported by Award No. KUS-C1-016-04 made by King Abdullah Uni-versity of Science and Technology (KAUST). This publication acknowledges KAUST support, but has no KAUST affiliated authors.",

year = "2010",

language = "English (US)",

pages = "122--+",

booktitle = "17th European MPI Users Group Meeting",

publisher = "SPRINGER-VERLAG BERLIN",

}

TY - GEN

T1 - Massively Parallel Finite Element Programming

AU - Heister, Timo

AU - Kronbichler, Martin

AU - Bangerth, Wolfgang

N1 - KAUST Repository Item: Exported on 2022-06-27 Acknowledged KAUST grant number(s): KUS-C1-016-04 Acknowledgements: Timo Heister is partly supported by the German Research Foundation (DFG) through GK 1023. Martin Kronbichler is supported by the Graduate School in Mathematics and Computation (FMB). Wolfgang Bangerth was partially supported by Award No. KUS-C1-016-04 made by King Abdul-lah University of Science and Technology (KAUST), by a grant from the NSF-funded Computational Infrastructure in Geodynamics initiative through Award No. EAR-0426271, and by an Alfred P. Sloan Research Fellowship. The computations were done on the Hurr3 cluster of the Institute for Applied Mathematics and Computational Science (IAMCS) at Texas A&M University. Hurr is supported by Award No. KUS-C1-016-04 made by King Abdullah Uni-versity of Science and Technology (KAUST). This publication acknowledges KAUST support, but has no KAUST affiliated authors.

PY - 2010

Y1 - 2010

N2 - Today's large finite element simulations require parallel algorithms to scale on clusters with thousands or tens of thousands of processor cores. We present data structures and algorithms to take advantage of the power of high performance computers in generic finite element codes. Existing generic finite element libraries often restrict the parallelization to parallel linear algebra routines. This is a limiting factor when solving on more than a few hundreds of cores. We describe routines for distributed storage of all major components coupled with efficient, scalable algorithms. We give an overview of our effort to enable the modern and generic finite element library deal. II to take advantage of the power of large clusters. In particular, we describe the construction of a distributed mesh and develop algorithms to fully parallelize the finite element calculation. Numerical results demonstrate good scalability.

AB - Today's large finite element simulations require parallel algorithms to scale on clusters with thousands or tens of thousands of processor cores. We present data structures and algorithms to take advantage of the power of high performance computers in generic finite element codes. Existing generic finite element libraries often restrict the parallelization to parallel linear algebra routines. This is a limiting factor when solving on more than a few hundreds of cores. We describe routines for distributed storage of all major components coupled with efficient, scalable algorithms. We give an overview of our effort to enable the modern and generic finite element library deal. II to take advantage of the power of large clusters. In particular, we describe the construction of a distributed mesh and develop algorithms to fully parallelize the finite element calculation. Numerical results demonstrate good scalability.

UR - http://hdl.handle.net/10754/679361

M3 - Conference contribution

SP - 122-+

BT - 17th European MPI Users Group Meeting

PB - SPRINGER-VERLAG BERLIN

ER -

Massively Parallel Finite Element Programming

Abstract

Bibliographical note

Other files and links

Fingerprint

Cite this