A quantitative performance analysis for Stokes solvers at the extreme scale.

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Details zur Publikation

Autor(en): Gmeiner B, Huber M, John L, Rüde U, Wohlmuth BI
Verlagsort: arXiv
Jahr der Veröffentlichung: 2015
Sprache: Englisch


Abstract


This article presents a systematic quantitative performance analysis for large finite element computations on extreme scale computing systems. Three parallel iterative solvers for the Stokes system, discretized by low order tetrahedral elements, are compared with respect to their numerical efficiency and their scalability running on up to 786 432 parallel threads. A genuine multigrid method for the saddle point system using an Uzawa-type smoother provides the best overall performance with respect to memory consumption and time-to-solution. The largest system solved on a Blue Gene/Q system has more than ten trillion (1.1 · 1013) unknowns and requires about 13 minutes compute time. Despite the matrix free and highly optimized implementation, the memory requirement for the solution vector and the auxiliary vectors is about 200 TByte. Brandt’s notion of “textbook multigrid efficiency” is employed to study the algorithmic performance of iterative solvers. A recent extension of this paradigm to “parallel textbook multigrid efficiency” makes it possible to assess also the efficiency of parallel iterative solvers for a given hardware architecture in absolute terms. The efficiency of the method is demonstrated for simulating incompressible fluid flow in a pipe filled with spherical obstacles.



FAU-Autoren / FAU-Herausgeber

Gmeiner, Björn Dr.-Ing.
Lehrstuhl für Informatik 10 (Systemsimulation)
Huber, Markus
Lehrstuhl für Informatik 10 (Systemsimulation)
Rüde, Ulrich Prof. Dr.
Lehrstuhl für Informatik 10 (Systemsimulation)


Autor(en) der externen Einrichtung(en)
Technische Universität München (TUM)


Zitierweisen

APA:
Gmeiner, B., Huber, M., John, L., Rüde, U., & Wohlmuth, B.I. (2015). A quantitative performance analysis for Stokes solvers at the extreme scale. arXiv.

MLA:
Gmeiner, Björn, et al. A quantitative performance analysis for Stokes solvers at the extreme scale. arXiv, 2015.

BibTeX: 

Zuletzt aktualisiert 2018-07-08 um 21:23