A Multi-Scale Electromagnetic Particle Code with Adaptive Mesh Refinement and Its Parallelization
Author(s) -
Hideyuki Usui,
M. Nunami,
Toseo Moritaka,
Tatsuki Matsui,
Yohei Yagi
Publication year - 2011
Publication title -
procedia computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.334
H-Index - 76
ISSN - 1877-0509
DOI - 10.1016/j.procs.2011.04.254
Subject(s) - computer science , domain decomposition methods , load balancing (electrical power) , parallel computing , computation , computational science , scale (ratio) , code (set theory) , domain (mathematical analysis) , adaptive mesh refinement , algorithm , finite element method , physics , grid , mathematics , geometry , mathematical analysis , set (abstract data type) , quantum mechanics , thermodynamics , programming language
pace plasma phenomena occur in multi-scale processes from the electron scale to the magnetohydrodynamic scale. In order to investigate such multi-scale phenomena including plasma kinetic effects, we started to develop a new electromagnetic Particle-In-Cell (PIC) code with Adaptive Mesh Refinement (AMR) technique. AMR can realize high-resolution calculation saving computer resources by generating and removing hierarchical cells dynamically. In the parallelization, we adopt domain decomposition method and for good locality preserving and dynamical load balancing, we will use the Morton ordered curve. In the PIC method, particle calculation occupies most of the total calculation time. In our AMR-PIC code, time step intervals are also refined. To realize the load balancing between processes in the domain decomposition scheme, it is the most essential to consider the number of particle calculation loops for each cell among all hierarchical levels as a work weight for each processor. Therefore, we calculate the work weights based on the cost of particle calculation and hierarchical levels of each cell. Then we decompose the domain according to the Morton curve and the work weight, so that each processor has approximately the same amount of work. By performing a simple one-dimensional simulation, we confirmed that the dynamic load balancing is achieved and the computation time is reduced by introducing the dynamic domain decomposition scheme
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