期刊
JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING
卷 157, 期 -, 页码 1-12出版社
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.jpdc.2021.06.004
关键词
Particle-in-cell; Unstructured mesh; GPU
资金
- National Science Foundation [ACI 1533581]
- U.S. Department of Energy, Office of Science [DE-AC5207NA27344, DE-SC0018275]
- Office of Science of the U.S. Department of Energy [DE-AC05-00OR22725]
- U.S. Department of Energy (DOE) [DE-SC0018275] Funding Source: U.S. Department of Energy (DOE)
This paper introduces a framework for efficient and performance-portable mesh-based PIC simulations on GPU systems: PUMIPic. Performance evaluation of mesh-based PIC shows that it can utilize partitioned mesh and maintain scalability.
Unstructured mesh particle-in-cell, PIC, simulations executing on the current and next generation of massively parallel systems require new methods for both the mesh and particles to achieve performance and scalability on GPUs. The traditional approach to implementing PIC simulations defines data structures and algorithms in terms of particles with a full copy of the unstructured mesh on every process. To effectively scale the unstructured mesh and particles, mesh-based PIC uses the unstructured mesh as the predominant data structure with the particles stored in terms of the mesh entities. This paper details the PUMIPic library, a framework for developing efficient and performance-portable mesh-based PIC simulations on GPU systems. A pseudo physics simulation based on a five-dimensional gyro-kinetic code for modeling plasma physics is used to examine the performance of PUMIPic. Scaling studies of the unstructured mesh partition and number of particles are performed up to 4096 nodes of the Summit system at Oak Ridge National Laboratory. The studies show that mesh-based PIC can utilize a partitioned mesh and maintain scaling up to system limitations. (C) 2021 Elsevier Inc. All rights reserved.
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