Flexible and Scalable Particle‐in‐Cell Methods With Adaptive Mesh Refinement for Geodynamic Computations

Particle‐in‐cell (PIC) methods couple mesh‐based methods for the solution of continuum mechanics problems with the ability to advect and evolve properties on particles. PIC methods have a long history and numerous applications in geodynamic modeling. However, they are historically either implemented...

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Published inGeochemistry, geophysics, geosystems : G3 Vol. 19; no. 9; pp. 3596 - 3604
Main Authors Gassmöller, Rene, Lokavarapu, Harsha, Heien, Eric, Puckett, Elbridge Gerry, Bangerth, Wolfgang
Format Journal Article
LanguageEnglish
Published Washington John Wiley & Sons, Inc 01.09.2018
Wiley
Subjects
Online AccessGet full text
ISSN1525-2027
1525-2027
DOI10.1029/2018GC007508

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Abstract Particle‐in‐cell (PIC) methods couple mesh‐based methods for the solution of continuum mechanics problems with the ability to advect and evolve properties on particles. PIC methods have a long history and numerous applications in geodynamic modeling. However, they are historically either implemented in sequential codes or in parallel codes with structured, statically partitioned meshes. Yet today's codes increasingly use adaptive mesh refinement (AMR) of unstructured coarse meshes, dynamic repartitioning, and scale to thousands of processors. Optimally balancing the work per processor for a PIC method in these environments is a difficult problem, and many existing implementations are not sufficient for this task. Thus, there is a need to revisit these algorithms for future applications. Here we describe challenges and solutions to implement PIC methods in the context of large‐scale parallel geodynamic modeling codes that use dynamically changing meshes. We also provide guidance for how to address bottlenecks that impede the efficient implementation of these algorithms and demonstrate with numerical tests that our algorithms can be implemented with optimal complexity and that they are suitable for large‐scale, practical applications. We provide a reference implementation in the Advanced Solver for Problems in Earth's ConvecTion (ASPECT), an open source code for geodynamic modeling built on the DEAL.II finite element library. Key Points Particle‐in‐cell methods require new algorithms when applied to dynamically partitioned, adaptively refined finite‐element calculations We present approaches for particle generation, sorting, and hybrid load balancing in hierarchically refined finite‐element computations We show scalability and applicability of the developed methods for problems in computational geodynamics
AbstractList Abstract Particle‐in‐cell (PIC) methods couple mesh‐based methods for the solution of continuum mechanics problems with the ability to advect and evolve properties on particles. PIC methods have a long history and numerous applications in geodynamic modeling. However, they are historically either implemented in sequential codes or in parallel codes with structured, statically partitioned meshes. Yet today's codes increasingly use adaptive mesh refinement (AMR) of unstructured coarse meshes, dynamic repartitioning, and scale to thousands of processors. Optimally balancing the work per processor for a PIC method in these environments is a difficult problem, and many existing implementations are not sufficient for this task. Thus, there is a need to revisit these algorithms for future applications. Here we describe challenges and solutions to implement PIC methods in the context of large‐scale parallel geodynamic modeling codes that use dynamically changing meshes. We also provide guidance for how to address bottlenecks that impede the efficient implementation of these algorithms and demonstrate with numerical tests that our algorithms can be implemented with optimal complexity and that they are suitable for large‐scale, practical applications. We provide a reference implementation in the Advanced Solver for Problems in Earth's ConvecTion (ASPECT), an open source code for geodynamic modeling built on the DEAL.II finite element library.
Particle‐in‐cell (PIC) methods couple mesh‐based methods for the solution of continuum mechanics problems with the ability to advect and evolve properties on particles. PIC methods have a long history and numerous applications in geodynamic modeling. However, they are historically either implemented in sequential codes or in parallel codes with structured, statically partitioned meshes. Yet today's codes increasingly use adaptive mesh refinement (AMR) of unstructured coarse meshes, dynamic repartitioning, and scale to thousands of processors. Optimally balancing the work per processor for a PIC method in these environments is a difficult problem, and many existing implementations are not sufficient for this task. Thus, there is a need to revisit these algorithms for future applications. Here we describe challenges and solutions to implement PIC methods in the context of large‐scale parallel geodynamic modeling codes that use dynamically changing meshes. We also provide guidance for how to address bottlenecks that impede the efficient implementation of these algorithms and demonstrate with numerical tests that our algorithms can be implemented with optimal complexity and that they are suitable for large‐scale, practical applications. We provide a reference implementation in the Advanced Solver for Problems in Earth's ConvecTion (ASPECT), an open source code for geodynamic modeling built on the DEAL.II finite element library.
Particle‐in‐cell (PIC) methods couple mesh‐based methods for the solution of continuum mechanics problems with the ability to advect and evolve properties on particles. PIC methods have a long history and numerous applications in geodynamic modeling. However, they are historically either implemented in sequential codes or in parallel codes with structured, statically partitioned meshes. Yet today's codes increasingly use adaptive mesh refinement (AMR) of unstructured coarse meshes, dynamic repartitioning, and scale to thousands of processors. Optimally balancing the work per processor for a PIC method in these environments is a difficult problem, and many existing implementations are not sufficient for this task. Thus, there is a need to revisit these algorithms for future applications. Here we describe challenges and solutions to implement PIC methods in the context of large‐scale parallel geodynamic modeling codes that use dynamically changing meshes. We also provide guidance for how to address bottlenecks that impede the efficient implementation of these algorithms and demonstrate with numerical tests that our algorithms can be implemented with optimal complexity and that they are suitable for large‐scale, practical applications. We provide a reference implementation in the Advanced Solver for Problems in Earth's ConvecTion (ASPECT), an open source code for geodynamic modeling built on the DEAL.II finite element library. Key Points Particle‐in‐cell methods require new algorithms when applied to dynamically partitioned, adaptively refined finite‐element calculations We present approaches for particle generation, sorting, and hybrid load balancing in hierarchically refined finite‐element computations We show scalability and applicability of the developed methods for problems in computational geodynamics
Particle‐in‐cell (PIC) methods couple mesh‐based methods for the solution of continuum mechanics problems with the ability to advect and evolve properties on particles. PIC methods have a long history and numerous applications in geodynamic modeling. However, they are historically either implemented in sequential codes or in parallel codes with structured, statically partitioned meshes. Yet today's codes increasingly use adaptive mesh refinement (AMR) of unstructured coarse meshes, dynamic repartitioning, and scale to thousands of processors. Optimally balancing the work per processor for a PIC method in these environments is a difficult problem, and many existing implementations are not sufficient for this task. Thus, there is a need to revisit these algorithms for future applications. Here we describe challenges and solutions to implement PIC methods in the context of large‐scale parallel geodynamic modeling codes that use dynamically changing meshes. We also provide guidance for how to address bottlenecks that impede the efficient implementation of these algorithms and demonstrate with numerical tests that our algorithms can be implemented with optimal complexity and that they are suitable for large‐scale, practical applications. We provide a reference implementation in the Advanced Solver for Problems in Earth's ConvecTion (ASPECT), an open source code for geodynamic modeling built on the DEAL.II finite element library. Particle‐in‐cell methods require new algorithms when applied to dynamically partitioned, adaptively refined finite‐element calculations We present approaches for particle generation, sorting, and hybrid load balancing in hierarchically refined finite‐element computations We show scalability and applicability of the developed methods for problems in computational geodynamics
Author Heien, Eric
Gassmöller, Rene
Bangerth, Wolfgang
Lokavarapu, Harsha
Puckett, Elbridge Gerry
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Copyright 2018. American Geophysical Union. All Rights Reserved.
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Snippet Particle‐in‐cell (PIC) methods couple mesh‐based methods for the solution of continuum mechanics problems with the ability to advect and evolve properties on...
Abstract Particle‐in‐cell (PIC) methods couple mesh‐based methods for the solution of continuum mechanics problems with the ability to advect and evolve...
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SubjectTerms Adaptive mesh refinement
Algorithms
Codes
Convection
Earth
Geodynamic software
High performance computing
Mechanics
Methods
Modelling
Numerical modeling
Particle in cell method
Scalable algorithm
Solutions
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Title Flexible and Scalable Particle‐in‐Cell Methods With Adaptive Mesh Refinement for Geodynamic Computations
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