Open Access
| Issue |
EPJ Web Conf.
Volume 302, 2024
Joint International Conference on Supercomputing in Nuclear Applications + Monte Carlo (SNA + MC 2024)
|
|
|---|---|---|
| Article Number | 02005 | |
| Number of page(s) | 14 | |
| Section | Deterministic Transport Codes: Algorithms, HPC & GPU | |
| DOI | https://doi.org/10.1051/epjconf/202430202005 | |
| Published online | 15 October 2024 | |
- C. Lee, W.S. Yang. MC2-3: Multigroup cross section generation code for fast reactor analysis[J]. Nuclear Science and Engineering, 2017, 187(3):268–290. [CrossRef] [Google Scholar]
- S. Santandrea, L. Graziano, D. Sciannandrone. Accelerated polynomial axial expansions for full 3D neutron transport MOC in the APOLLO3® code system as applied to the ASTRID fast breeder reactor, Annals of Nuclear Energy, Volume 113, 2018, Pages 194–236. [CrossRef] [Google Scholar]
- B.M. Kochunas. A hybrid parallel algorithm for the 3-D method of characteristics solution of the Boltzmann transport equation on high performance compute clusters [D]. Michigan, USA: University of Michigan, 2013. [Google Scholar]
- Z. Liu, H. Wu, L. Cao. Geometry pretreatment method for the 3D modular characteristic method based on AutoCAD [J]. Annals of Nuclear Energy, 2017, 109:440–450. [CrossRef] [Google Scholar]
- J.R. Askew. A characteristics formulation of the neutron transport equation in complicated geometries [R], Atomic Energy Establishment Winfrith Report M1108, 1972. [Google Scholar]
- J. L. Greathouse and M. Daga. Efficient Sparse Matrix-Vector Multiplication on GPUs Using the CSR Storage Format, SC ‘14: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, New Orleans, LA, USA, 2014, pp. 769–780. [Google Scholar]
- N.Z. Cho. Benchmark Problem 3A: MOX Fuel-Loaded Small PWR Core, MOX Fuel with Zoning, 7 Group Homogenized Cells. [Google Scholar]
- L. Wei, Y. Zheng, X. Du, et al. Development of SARAX code system for full-range spectrum adaptability in advanced reactor analysis[J]. Annals of Nuclear Energy, 2022, 165:108664. [Google Scholar]
- M. Leinhauser, J. Young, S. Bastrakov, et al. Performance analysis of PIConGPU: particle-in-cell on GPUs using NVIDIA’s NSight systems and NSight compute[R]. Oak Ridge National Lab.(ORNL), Oak Ridge, TN (United States), 2021. [Google Scholar]
- S. Williams, A. Waterman, D.A. Patterson. Roofline: an insightful visual performance model for multicore architectures[J]. Communications of the ACM, 2009, 52(4):65–76. [CrossRef] [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.