Результаты исследований: Научные публикации в периодических изданиях › статья в журнале по материалам конференции › Рецензирование
Comparison of python 3 single-GPU parallelization technologies on the example of a charged particles dynamics simulation problem. / Boytsov, A.; Kadochnikov, I.; Zuev, M.; Bulychev, A.; Zolotuhin, Ya; Getmanov, I.
в: CEUR Workshop Proceedings, Том 2267, 01.01.2018, стр. 518-522.Результаты исследований: Научные публикации в периодических изданиях › статья в журнале по материалам конференции › Рецензирование
}
TY - JOUR
T1 - Comparison of python 3 single-GPU parallelization technologies on the example of a charged particles dynamics simulation problem
AU - Boytsov, A.
AU - Kadochnikov, I.
AU - Zuev, M.
AU - Bulychev, A.
AU - Zolotuhin, Ya
AU - Getmanov, I.
PY - 2018/1/1
Y1 - 2018/1/1
N2 - Low energy ion and electron beams, produced by ion sources and electron guns, find their use in surface modification, nuclear medicine and injection into high-energy accelerators. Simulation of particle dynamics is a necessary step for optimization of beam parameters. Since such simulations require significant computational resources, parallelization is highly desirable to be able to accomplish them in a reasonable amount of time. From the implementation standpoint, dynamically typed interpreted languages, such as Python 3, allow high development speed that comes at cost of performance. It is tempting to transfer all computationally heavy tasks on a GPU to alleviate this drawback. Using the example of a charged particles dynamics simulation problem, various GPU-parallelization technologies available in Python 3 are compared in terms of ease of use and computational speed. The reported study was funded by RFBR according to the research project No 18-32-00239/18. Computations were in part held on the basis of the heterogeneous computing cluster HybriLIT (LIT, JINR).
AB - Low energy ion and electron beams, produced by ion sources and electron guns, find their use in surface modification, nuclear medicine and injection into high-energy accelerators. Simulation of particle dynamics is a necessary step for optimization of beam parameters. Since such simulations require significant computational resources, parallelization is highly desirable to be able to accomplish them in a reasonable amount of time. From the implementation standpoint, dynamically typed interpreted languages, such as Python 3, allow high development speed that comes at cost of performance. It is tempting to transfer all computationally heavy tasks on a GPU to alleviate this drawback. Using the example of a charged particles dynamics simulation problem, various GPU-parallelization technologies available in Python 3 are compared in terms of ease of use and computational speed. The reported study was funded by RFBR according to the research project No 18-32-00239/18. Computations were in part held on the basis of the heterogeneous computing cluster HybriLIT (LIT, JINR).
KW - CUDA
KW - GPU computation
KW - Numba
KW - OpenCL
KW - Parallelization
KW - Particle dynamics
KW - Python3
UR - http://www.scopus.com/inward/record.url?scp=85060110304&partnerID=8YFLogxK
M3 - Conference article
AN - SCOPUS:85060110304
VL - 2267
SP - 518
EP - 522
JO - CEUR Workshop Proceedings
JF - CEUR Workshop Proceedings
SN - 1613-0073
T2 - 8th International Conference "Distributed Computing and Grid-Technologies in Science and Education", GRID 2018
Y2 - 10 September 2018 through 14 September 2018
ER -
ID: 45872311