.png){kind=icon}
.png){kind=icon}
Return
Scalable plasma simulation with ELMFIRE using efficient data structures for process communication
.png){kind=icon}
PRE
AI
DOI：10.1016/j.cpc.2008.03.009.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
We describe the parallel full-f gyrokinetic particle-in-cell plasma simulation code ELMFIRE and the issue of solving an electrostatic potential from particle data distributed across several MPI (Message Passing Interface) processes. The potential is solved through a linear system with a strongly sparse matrix and ELMFIRE stores data of the estimated non-zero diagonals of the whole matrix in every MPI process. We present and compare several memory efficient structures for gathering the matrix data while keeping only a local part of the matrix in each process. We also demonstrate that these alternative structures improve scalability, thus enabling ELMFIRE to use more MPI processes and a finer time and space scale than before without sacrificing performance. (C) 2008 Elsevier B.V. All rights reserved.
Keywords:
plasma simulation
gyrokinetics
full-f
sparse matrix
matrix assembly
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
3.4
Papers:
1.2W
Citations:
3.7W