Practical methods for GPU-based whole-core Monte Carlo depletion calculation

被引:1
|
作者
Kim, Kyung Min [1 ]
Choi, Namjae [1 ,2 ]
Lee, Han Gyu [1 ]
Joo, Han Gyu [1 ]
机构
[1] Seoul Natl Univ, 1 Gwanak ro, Seoul 08826, South Korea
[2] Idaho Natl Lab, 1955 N Fremont Ave, Idaho Falls, ID 83415 USA
基金
新加坡国家研究基金会;
关键词
PRAGMA; Multilevel spectral collapse; Chebyshev rational approximation method; Vectorized Gauss -Seidel; Consumer -grade GPUs; TRANSPORT; SHIFT; CAPABILITIES; CODE;
D O I
10.1016/j.net.2023.04.021
中图分类号
TL [原子能技术]; O571 [原子核物理学];
学科分类号
0827 ; 082701 ;
摘要
Several practical methods for accelerating the depletion calculation in a GPU-based Monte Carlo (MC) code PRAGMA are presented including the multilevel spectral collapse method and the vectorized Chebyshev rational approximation method (CRAM). Since the generation of microscopic reaction rates for each nuclide needed for the construction of the depletion matrix of the Bateman equation requires either enormous memory access or tremendous physical memory, both of which are quite burdensome on GPUs, a new method called multilevel spectral collapse is proposed which combines two types of spectra to generate microscopic reaction rates: an ultrafine spectrum for an entire fuel pin and coarser spectra for each depletion region. Errors in reaction rates introduced by this method are mitigated by a hybrid usage of direct online reaction rate tallies for several important fissile nuclides. The linear system to appear in the solution process adopting the CRAM is solved by the Gauss-Seidel method which can be easily vectorized on GPUs. With the accelerated depletion methods, only about 10% of MC calculation time is consumed for depletion, so an accurate full core cycle depletion calculation for a commercial power reactor (BEAVRS) can be done in 16 h with 24 consumer-grade GPUs.& COPY; 2023 Korean Nuclear Society, Published by Elsevier Korea LLC. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
引用
收藏
页码:2516 / 2533
页数:18
相关论文
共 50 条
  • [21] Practical acceleration of direct whole-core calculation employing graphics processing units
    Choi, Namjae
    Kang, Junsu
    Lee, Han Gyu
    Joo, Han Gyu
    PROGRESS IN NUCLEAR ENERGY, 2021, 133 (133)
  • [22] Development of a GPU-Based Monte Carlo Dose Calculation Code for Coupled Electron-Photon Transport
    Jia, X.
    Gu, X.
    Sempau, J.
    Choi, D.
    Majumdar, A.
    Jiang, S.
    MEDICAL PHYSICS, 2010, 37 (06)
  • [23] Experimental evaluation of a GPU-based Monte Carlo dose calculation algorithm in the Monaco treatment planning system
    Paudel, Moti R.
    Kim, Anthony
    Sarfehnia, Arman
    Ahmad, Sayed B.
    Beachey, David J.
    Sahgal, Arjun
    Keller, Brian M.
    JOURNAL OF APPLIED CLINICAL MEDICAL PHYSICS, 2016, 17 (06): : 230 - 241
  • [24] GPU-based cross-platform Monte Carlo proton dose calculation engine in the framework of Taichi
    Wei-Guang Li
    Cheng Chang
    Yao Qin
    Zi-Lu Wang
    Kai-Wen Li
    Li-Sheng Geng
    Hao Wu
    NuclearScienceandTechniques, 2023, 34 (05) : 156 - 166
  • [25] A Method for Automatic Commissioning of a GPU-Based Monte Carlo Code for Clinica Photon Beam Dose Calculation
    Tian, Z.
    Townson, R.
    Graves, Y.
    Jia, X.
    Jiang, S.
    MEDICAL PHYSICS, 2013, 40 (06)
  • [26] Development of a GPU-based Monte Carlo dose calculation code for coupled electron-photon transport
    Jia, Xun
    Gu, Xuejun
    Sempau, Josep
    Choi, Dongju
    Majumdar, Amitava
    Jiang, Steve B.
    PHYSICS IN MEDICINE AND BIOLOGY, 2010, 55 (11): : 3077 - 3086
  • [27] GPU-based cross-platform Monte Carlo proton dose calculation engine in the framework of Taichi
    Li, Wei-Guang
    Chang, Cheng
    Qin, Yao
    Wang, Zi-Lu
    Li, Kai-Wen
    Geng, Li-Sheng
    Wu, Hao
    NUCLEAR SCIENCE AND TECHNIQUES, 2023, 34 (05)
  • [28] GPU-based cross-platform Monte Carlo proton dose calculation engine in the framework of Taichi
    Wei-Guang Li
    Cheng Chang
    Yao Qin
    Zi-Lu Wang
    Kai-Wen Li
    Li-Sheng Geng
    Hao Wu
    Nuclear Science and Techniques, 2023, 34
  • [29] GPU-based multifrontal methods in power flow calculation
    Xu D.
    Chen Y.
    Wang W.
    Jiang H.
    Zheng R.
    Gaodianya Jishu, 10 (3301-3307): : 3301 - 3307
  • [30] Whole-core depletion calculation using domain decomposed continuous-energy Monte Carlo simulation via McBOX with p-CMFD acceleration and inline feedback
    Jo, YuGwon
    Kim, HyeonTae
    Kim, Yonghee
    Cho, Nam Zin
    ANNALS OF NUCLEAR ENERGY, 2020, 139