A fast parallel Poisson solver on irregular domains applied to beam dynamics simulations

We discuss the scalable parallel solution of the Poisson equation within a Particle-In-Cell (PIC) code for the simulation of electron beams in particle accelerators of irregular shape. The problem is discretized by Finite Differences. Depending on the treatment of the Dirichlet boundary the resultin...

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Veröffentlicht in:Journal of computational physics Jg. 229; H. 12; S. 4554 - 4566
Hauptverfasser: Adelmann, A., Arbenz, P., Ineichen, Y.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Kidlington Elsevier Inc 20.06.2010
Elsevier
Schlagworte:
AGGLOMERATION
Algebraic multigrid
ALGORITHMS
BEAM DYNAMICS
CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS
COMPARATIVE EVALUATIONS
Computational techniques
Computer simulation
DIRICHLET PROBLEM
Distributed memory
Dynamics
ELECTRON BEAMS
Exact sciences and technology
Irregular domains
ITERATIVE METHODS
Mathematical analysis
Mathematical methods in physics
MATHEMATICAL SOLUTIONS
Microprocessors
Physics
POISSON EQUATION
Preconditioned conjugate gradient algorithm
SIMULATION
Solvers
SPACE CHARGE
Poisson equation
Irregular domains
Beam dynamics
Preconditioned conjugate gradient algorithm
Space-charge
Algebraic multigrid
Particle beams
Preconditioned conjugate gradient
Space charge
Calculation methods
Particle accelerators
Algorithms
Electron beams
Dynamics
Multigrid
Calculation
Preconditioning
algorithm
ISSN:0021-9991, 1090-2716
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Beschreibung
Zusammenfassung:We discuss the scalable parallel solution of the Poisson equation within a Particle-In-Cell (PIC) code for the simulation of electron beams in particle accelerators of irregular shape. The problem is discretized by Finite Differences. Depending on the treatment of the Dirichlet boundary the resulting system of equations is symmetric or ‘mildly’ nonsymmetric positive definite. In all cases, the system is solved by the preconditioned conjugate gradient algorithm with smoothed aggregation (SA) based algebraic multigrid (AMG) preconditioning. We investigate variants of the implementation of SA-AMG that lead to considerable improvements in the execution times. We demonstrate good scalability of the solver on distributed memory parallel processor with up to 2048 processors. We also compare our iterative solver with an FFT-based solver that is more commonly used for applications in beam dynamics.
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ISSN:0021-9991
1090-2716
DOI:10.1016/j.jcp.2010.02.022