Multiphysics simulations: Challenges and opportunities

David E. Keyes; Lois C. McInnes; Carol Woodward; William Gropp; Eric Myra; Michael Pernice; John Bell; Jed Brown; Alain Clo; Jeffrey Connors; Emil Constantinescu; Don Estep; Kate Evans; Charbel Farhat; Ammar Hakim; Glenn Hammond; Glen Hansen; Judith Hill; Tobin Isaac; Xiangmin Jiao; Kirk Jordan; Dinesh Kaushik; Efthimios Kaxiras; Alice Koniges; Kihwan Lee; Aaron Lott; Qiming Lu; John Magerlein; Reed Maxwell; Michael McCourt; Miriam Mehl; Roger Pawlowski; Amanda P. Randles; Daniel Reynolds; Beatrice Rivière; Ulrich Rüde; Tim Scheibe; John Shadid; Brendan Sheehan; Mark Shephard; Andrew Siegel; Barry Smith; Xianzhu Tang; Cian Wilson; Barbara Wohlmuth

doi:10.1177/1094342012468181

Multiphysics simulations: Challenges and opportunities

David E. Keyes, Lois C. McInnes, Carol Woodward, William Gropp, Eric Myra, Michael Pernice, John Bell, Jed Brown, Alain Clo, Jeffrey Connors, Emil Constantinescu, Don Estep, Kate Evans, Charbel Farhat, Ammar Hakim, Glenn Hammond, Glen Hansen, Judith Hill, Tobin Isaac, Xiangmin JiaoKirk Jordan, Dinesh Kaushik, Efthimios Kaxiras, Alice Koniges, Kihwan Lee, Aaron Lott, Qiming Lu, John Magerlein, Reed Maxwell, Michael McCourt, Miriam Mehl, Roger Pawlowski, Amanda P. Randles, Daniel Reynolds, Beatrice Rivière, Ulrich Rüde, Tim Scheibe, John Shadid, Brendan Sheehan, Mark Shephard, Andrew Siegel, Barry Smith, Xianzhu Tang, Cian Wilson, Barbara Wohlmuth

Lehrstuhl für Numerische Mathematik

Publikation: Beitrag in Fachzeitschrift › Artikel › Begutachtung

272 Zitate (Scopus)

Abstract

We consider multiphysics applications from algorithmic and architectural perspectives, where "algorithmic" includes both mathematical analysis and computational complexity, and "architectural" includes both software and hardware environments. Many diverse multiphysics applications can be reduced, en route to their computational simulation, to a common algebraic coupling paradigm. Mathematical analysis of multiphysics coupling in this form is not always practical for realistic applications, but model problems representative of applications discussed herein can provide insight. A variety of software frameworks for multiphysics applications have been constructed and refined within disciplinary communities and executed on leading-edge computer systems. We examine several of these, expose some commonalities among them, and attempt to extrapolate best practices to future systems. From our study, we summarize challenges and forecast opportunities.

Originalsprache	Englisch
Seiten (von - bis)	4-83
Seitenumfang	80
Fachzeitschrift	International Journal of High Performance Computing Applications
Jahrgang	27
Ausgabenummer	1
DOIs	https://doi.org/10.1177/1094342012468181
Publikationsstatus	Veröffentlicht - Feb. 2013

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Keyes, D. E., McInnes, L. C., Woodward, C., Gropp, W., Myra, E., Pernice, M., Bell, J., Brown, J., Clo, A., Connors, J., Constantinescu, E., Estep, D., Evans, K., Farhat, C., Hakim, A., Hammond, G., Hansen, G., Hill, J., Isaac, T., ... Wohlmuth, B. (2013). Multiphysics simulations: Challenges and opportunities. International Journal of High Performance Computing Applications, 27(1), 4-83. https://doi.org/10.1177/1094342012468181

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title = "Multiphysics simulations: Challenges and opportunities",

abstract = "We consider multiphysics applications from algorithmic and architectural perspectives, where {"}algorithmic{"} includes both mathematical analysis and computational complexity, and {"}architectural{"} includes both software and hardware environments. Many diverse multiphysics applications can be reduced, en route to their computational simulation, to a common algebraic coupling paradigm. Mathematical analysis of multiphysics coupling in this form is not always practical for realistic applications, but model problems representative of applications discussed herein can provide insight. A variety of software frameworks for multiphysics applications have been constructed and refined within disciplinary communities and executed on leading-edge computer systems. We examine several of these, expose some commonalities among them, and attempt to extrapolate best practices to future systems. From our study, we summarize challenges and forecast opportunities.",

keywords = "Multiphysics, implicit and explicit algorithms, loose and tight coupling., multimodel, multirate, multiscale, strong and weak coupling",

author = "Keyes, {David E.} and McInnes, {Lois C.} and Carol Woodward and William Gropp and Eric Myra and Michael Pernice and John Bell and Jed Brown and Alain Clo and Jeffrey Connors and Emil Constantinescu and Don Estep and Kate Evans and Charbel Farhat and Ammar Hakim and Glenn Hammond and Glen Hansen and Judith Hill and Tobin Isaac and Xiangmin Jiao and Kirk Jordan and Dinesh Kaushik and Efthimios Kaxiras and Alice Koniges and Kihwan Lee and Aaron Lott and Qiming Lu and John Magerlein and Reed Maxwell and Michael McCourt and Miriam Mehl and Roger Pawlowski and Randles, {Amanda P.} and Daniel Reynolds and Beatrice Rivi{\`e}re and Ulrich R{\"u}de and Tim Scheibe and John Shadid and Brendan Sheehan and Mark Shephard and Andrew Siegel and Barry Smith and Xianzhu Tang and Cian Wilson and Barbara Wohlmuth",

note = "Funding Information: The workshop from which this document originated was sponsored by the Institute for Computing in Science, funded by the Office of Advanced Scientific Computing Research, Office of Science, U.S. Department of Energy, under Contract DE-AC02-06CH11357.",

year = "2013",

month = feb,

doi = "10.1177/1094342012468181",

language = "English",

volume = "27",

pages = "4--83",

journal = "International Journal of High Performance Computing Applications",

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Keyes, DE, McInnes, LC, Woodward, C, Gropp, W, Myra, E, Pernice, M, Bell, J, Brown, J, Clo, A, Connors, J, Constantinescu, E, Estep, D, Evans, K, Farhat, C, Hakim, A, Hammond, G, Hansen, G, Hill, J, Isaac, T, Jiao, X, Jordan, K, Kaushik, D, Kaxiras, E, Koniges, A, Lee, K, Lott, A, Lu, Q, Magerlein, J, Maxwell, R, McCourt, M, Mehl, M, Pawlowski, R, Randles, AP, Reynolds, D, Rivière, B, Rüde, U, Scheibe, T, Shadid, J, Sheehan, B, Shephard, M, Siegel, A, Smith, B, Tang, X, Wilson, C & Wohlmuth, B 2013, 'Multiphysics simulations: Challenges and opportunities', International Journal of High Performance Computing Applications, Jg. 27, Nr. 1, S. 4-83. https://doi.org/10.1177/1094342012468181

TY - JOUR

T1 - Multiphysics simulations

T2 - Challenges and opportunities

AU - Keyes, David E.

AU - McInnes, Lois C.

AU - Woodward, Carol

AU - Gropp, William

AU - Myra, Eric

AU - Pernice, Michael

AU - Bell, John

AU - Brown, Jed

AU - Clo, Alain

AU - Connors, Jeffrey

AU - Constantinescu, Emil

AU - Estep, Don

AU - Evans, Kate

AU - Farhat, Charbel

AU - Hakim, Ammar

AU - Hammond, Glenn

AU - Hansen, Glen

AU - Hill, Judith

AU - Isaac, Tobin

AU - Jiao, Xiangmin

AU - Jordan, Kirk

AU - Kaushik, Dinesh

AU - Kaxiras, Efthimios

AU - Koniges, Alice

AU - Lee, Kihwan

AU - Lott, Aaron

AU - Lu, Qiming

AU - Magerlein, John

AU - Maxwell, Reed

AU - McCourt, Michael

AU - Mehl, Miriam

AU - Pawlowski, Roger

AU - Randles, Amanda P.

AU - Reynolds, Daniel

AU - Rivière, Beatrice

AU - Rüde, Ulrich

AU - Scheibe, Tim

AU - Shadid, John

AU - Sheehan, Brendan

AU - Shephard, Mark

AU - Siegel, Andrew

AU - Smith, Barry

AU - Tang, Xianzhu

AU - Wilson, Cian

AU - Wohlmuth, Barbara

N1 - Funding Information: The workshop from which this document originated was sponsored by the Institute for Computing in Science, funded by the Office of Advanced Scientific Computing Research, Office of Science, U.S. Department of Energy, under Contract DE-AC02-06CH11357.

PY - 2013/2

Y1 - 2013/2

N2 - We consider multiphysics applications from algorithmic and architectural perspectives, where "algorithmic" includes both mathematical analysis and computational complexity, and "architectural" includes both software and hardware environments. Many diverse multiphysics applications can be reduced, en route to their computational simulation, to a common algebraic coupling paradigm. Mathematical analysis of multiphysics coupling in this form is not always practical for realistic applications, but model problems representative of applications discussed herein can provide insight. A variety of software frameworks for multiphysics applications have been constructed and refined within disciplinary communities and executed on leading-edge computer systems. We examine several of these, expose some commonalities among them, and attempt to extrapolate best practices to future systems. From our study, we summarize challenges and forecast opportunities.

AB - We consider multiphysics applications from algorithmic and architectural perspectives, where "algorithmic" includes both mathematical analysis and computational complexity, and "architectural" includes both software and hardware environments. Many diverse multiphysics applications can be reduced, en route to their computational simulation, to a common algebraic coupling paradigm. Mathematical analysis of multiphysics coupling in this form is not always practical for realistic applications, but model problems representative of applications discussed herein can provide insight. A variety of software frameworks for multiphysics applications have been constructed and refined within disciplinary communities and executed on leading-edge computer systems. We examine several of these, expose some commonalities among them, and attempt to extrapolate best practices to future systems. From our study, we summarize challenges and forecast opportunities.

KW - Multiphysics

KW - implicit and explicit algorithms

KW - loose and tight coupling.

KW - multimodel

KW - multirate

KW - multiscale

KW - strong and weak coupling

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DO - 10.1177/1094342012468181

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SN - 1094-3420

VL - 27

SP - 4

EP - 83

JO - International Journal of High Performance Computing Applications

JF - International Journal of High Performance Computing Applications

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ER -

Multiphysics simulations: Challenges and opportunities

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