Implementation and performance evaluation of a GPU particle-in-cell code
Name
824777909-MIT.pdf
Description
Full printable version
Size
10.22 MB
Format
Adobe PDF
Checksum (MD5)
61863a7a3103546674d77542f7af6f1c
Author(s)
Payne, Joshua Estes
Advisor(s)
Ian H. Hutchinson.
Alternative Title
Implementation and performance evaluation of a graphical processing unit particle-in-cell code
Date Issued
2012
Publisher
Massachusetts Institute of Technology
Abstract
In this thesis, I designed and implemented a particle-in-cell (PIC) code on a graphical processing unit (GPU) using NVIDA's Compute Unified Architecture (CUDA). The massively parallel nature of computing on a GPU nessecitated the development of new methods for various steps of the PIC method. I investigated different algorithms and data structures used in the past for GPU PIC codes, as well as developed some of new ones. The results of this research and development were used to implement an efficient multi-GPU version of the 3D3v PIC code SCEPTIC3D. The performance of the SCEPTIC3DGPU code was evaluated and compared to that of the CPU version on two different systems. For test cases with a moderate number of particles per cell, the GPU version of the code was 71x faster than the system with a newer processor, and 160x faster than the older system. These results indicate that SCEPTIC3DCPU can run problems on a modest workstation that previously would have required a large cluster.
Description
Thesis (S.M. and S.B.)--Massachusetts Institute of Technology, Dept. of Nuclear Science and Engineering; and, (S.B.)--Massachusetts Institute of Technology, Dept. of Physics, 2012.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 105-107).
Subjects
Nuclear Science and Engineering.
Physics.
MIT Department
Massachusetts Institute of Technology. Department of Nuclear Science and Engineering
Massachusetts Institute of Technology. Department of Physics
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