Implementation of the CPU/GPU hybrid parallel method of characteristics neutron transport calculation using the heterogeneous cluster with dynamic workload assignment

Song, Peitao; Zhang, Zhijian; Zhang, Qian; Liang, Liang; Zhao, Qiang

doi:10.1016/j.anucene.2019.106957

Cited by 13 publications

(3 citation statements)

References 13 publications

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“…The theoretical foundations including IGA, ITO-SIMP and CPU/GPU heterogeneous computing [40,41] are summarized in this section.…”

Section: Basic Theorymentioning

confidence: 99%

A Hybrid Parallel Strategy for Isogeometric Topology Optimization via CPU/GPU Heterogeneous Computing

Xia,

Gao,

et al. 2024

CMES

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This paper aims to solve large-scale and complex isogeometric topology optimization problems that consume significant computational resources. A novel isogeometric topology optimization method with a hybrid parallel strategy of CPU/GPU is proposed, while the hybrid parallel strategies for stiffness matrix assembly, equation solving, sensitivity analysis, and design variable update are discussed in detail. To ensure the high efficiency of CPU/GPU computing, a workload balancing strategy is presented for optimally distributing the workload between CPU and GPU. To illustrate the advantages of the proposed method, three benchmark examples are tested to verify the hybrid parallel strategy in this paper. The results show that the efficiency of the hybrid method is faster than serial CPU and parallel GPU, while the speedups can be up to two orders of magnitude.

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“…The theoretical foundations including IGA, ITO-SIMP and CPU/GPU heterogeneous computing [40,41] are summarized in this section.…”

Section: Basic Theorymentioning

confidence: 99%

A Hybrid Parallel Strategy for Isogeometric Topology Optimization via CPU/GPU Heterogeneous Computing

Xia,

Gao,

et al. 2024

CMES

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“…Firstly, the two-dimensional lattice calculation is performed. The two-dimensional method of characteristics (Song et al, 2020a) solver in hexagonal geometry for neutron transport calculation and the subgroup method with ultrafine groups for self-shielding calculation are utilized. For the typical assemblies, ultrafine-group cross-sections and neutron flux will be determined and the few-group homogenized micro cross-sections will be collapsed based on the flux-volume weight method and the principle of conservation of reaction rate.…”

Section: Models In Fsar Codementioning

confidence: 99%

FSAR: Full neutron spectrum code for advanced reactor simulation

Wang

Zhang

et al. 2023

Front. Energy Res.

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The full neutron spectrum code for advanced reactor simulation named FSAR has recently been developed at Nuclear Power Institute of China in order to meet the requirements of advanced reactor with large neutron energy range. Based on the two-step calculation scheme, FSAR consists of two-dimensional lattice calculation code and core calculation code. In two-dimensional lattice calculation, the subgroup method with ultrafine energy groups was implemented in the two-dimensional resonance self-shielding by incorporating the MOC to get the accurate self-shielded cross-section. For better consideration of the strong space coupling in different geometric sizes due to different mean free path of neutrons, the super-homogenization method and the leakage model were applied. In the core calculation, the discrete-ordinate method and micro burnup calculation method were used to simulate the core neutron transport and depletion. Preliminary calculation results showed that for the problems with wide spectrum, the self-shielded cross-sections have a good agreement with the Monte Carlo solution. The results shown in this paper indicate that FSAR has good performances of the cross-section generation in full neutron spectrum problem simulation.

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“…The ray parallel scheme was introduced into the 3-D MOC simulation with intra-node multi-GPUs parallelization by Zhang et al (2013). A CPU-GPU hybrid parallel MOC neutron transport calculation was implemented with a dynamic workload assignment (Liang et al, 2020;Song et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

GPU Based Two-Level CMFD Accelerating Two-Dimensional MOC Neutron Transport Calculation

et al. 2020

Self Cite

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The Graphics Processing Units (GPUs) are increasingly becoming the primary computational platform in the scientific fields, due to its cost-effectiveness and massively parallel processing capability. On the other hand, the coarse mesh finite difference (CMFD) method has been one of the most popular techniques to accelerate the neutron transport calculation. The GPU is employed into the method of characteristics (MOC) accelerated by two-level CMFD to solve the neutron transport equation. In this work, the Jacobi method, the successive over-relaxation (SOR) method with red-black ordering, and the preconditioned generalized minimum residual (PGMRES) method are applied to solve the linear system under the framework of CMFD. The performance of these linear system solvers is characterized on both CPU (Central Processing Unit) and GPU. The two-dimensional (2-D) C5G7 benchmark problem and an extended mock quarter-core problem are tested to verify the accuracy and efficiency of the algorithm with double precision, as well as the feasibility of massive parallelization. Numerical results demonstrate that the desired accuracy is maintained. Moreover, the results show that the few-group CMFD acceleration is effective to accelerate the multi-group CMFD calculation. The PGMRES method shows remarkable convergence characteristics compared to the Jacobi and the SOR methods. However, the SOR method shows better performance on GPU for solving the linear system of CMFD calculation, which reaches about 2,400x speedup on GPU with two-level CMFD acceleration compared to the CPU-based MOC calculation.

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Implementation of the CPU/GPU hybrid parallel method of characteristics neutron transport calculation using the heterogeneous cluster with dynamic workload assignment

Cited by 13 publications

References 13 publications

A Hybrid Parallel Strategy for Isogeometric Topology Optimization via CPU/GPU Heterogeneous Computing

A Hybrid Parallel Strategy for Isogeometric Topology Optimization via CPU/GPU Heterogeneous Computing

FSAR: Full neutron spectrum code for advanced reactor simulation

GPU Based Two-Level CMFD Accelerating Two-Dimensional MOC Neutron Transport Calculation

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