Pipelined Parallel JFNK Method and its Application in Neutron <i>k</i> Eigenvalue Problem

Liu Lixun; Zhang Han; Wu Yingjie; Guo Jiong; Li Fu

doi:10.13832/j.jnpe.2023.05.0015

Volume 44 Issue 5

Oct. 2023

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Liu Lixun, Zhang Han, Wu Yingjie, Guo Jiong, Li Fu. Pipelined Parallel JFNK Method and its Application in Neutron k Eigenvalue Problem[J]. Nuclear Power Engineering, 2023, 44(5): 15-22. doi: 10.13832/j.jnpe.2023.05.0015

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Liu Lixun, Zhang Han, Wu Yingjie, Guo Jiong, Li Fu. Pipelined Parallel JFNK Method and its Application in Neutron k Eigenvalue Problem[J]. Nuclear Power Engineering, 2023, 44(5): 15-22. doi: 10.13832/j.jnpe.2023.05.0015

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Pipelined Parallel JFNK Method and its Application in Neutron k Eigenvalue Problem

doi: 10.13832/j.jnpe.2023.05.0015

Key Laboratory of Advanced Reactor Engineering and Safety of Ministry of Education, Institute of Nuclear and New Energy Technology, Tsinghua University, Beijing, 100084, China

Received Date: 2022-11-01
Rev Recd Date: 2023-04-04
Publish Date: 2023-10-13

Abstract

Abstract

JFNK (Jacobian-free Newton-Krylov) is an efficient acceleration method for solving nonlinear problems such as neutron k eigenvalue and coupling of multiple physical fields in the reactor, and the generalized minimum residual (GMRES) algorithm is commonly used in Krylov iteration. The parallel JFNK method is a necessary means for solving large-scale problems, and its main problem lies in the low parallel efficiency of Gram-Schmidt (GS) orthogonalization procedure in GMRES, which causes massive collective communications. In this paper, the parallel JFNK method based on the parallel programming model of message passing interface and spatial domain decomposition technology is developed for the three-dimensional neutron k eigenvalue problem. Aiming at the poor parallel scalability of GS orthogonalization procedure, the pipelined method is studied to improve the parallel efficiency of parallel JFNK. Then, the computation time and parallel efficiency of parallel JFNK using classical GS orthogonalization, modified GS orthogonalization and pipelined method are compared. The IAEA-3D three-dimensional diffusion benchmark problem was used for numerical test. The results show that the parallel efficiency of pipelined parallel JFNK is significantly superior to that using classical or modified GS orthogonalization, and the convergence of pipelined parallel JFNK is not affected.
- Pipelined method,
- Parallel JFNK,
- Message passing interface (MPI),
- Collective communication,
- Nonblocking communication,
- Parallel efficiency

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References(13)

References

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