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 in | Geochemistry, geophysics, geosystems : G3 Vol. 19; no. 9; pp. 3596 - 3604 | 
|---|---|
| Main Authors | , , , , | 
| Format | Journal Article | 
| Language | English | 
| Published | 
        Washington
          John Wiley & Sons, Inc
    
        01.09.2018
     Wiley  | 
| Subjects | |
| Online Access | Get full text | 
| ISSN | 1525-2027 1525-2027  | 
| DOI | 10.1029/2018GC007508 | 
Cover
| 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. 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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