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

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

doi:10.3389/fenrg.2020.00124

Peitao Song, Liang Liang + Show 3 more

Open Access

https://doi.org/10.3389/fenrg.2020.00124

Copy DOI

Abstract

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 2400x speedup on GPU with two-level CMFD acceleration compared to the CPU-based MOC calculation.

Highlights

Significant advances in high-performance computing (HPC) systems enable the computational feasibility of high-fidelity, three-dimensional (3-D) whole-core neutron transport calculation
A two-level coarse mesh finite difference (CMFD) acceleration technique was implemented on both CPU and Graphics Processing Units (GPUs) to accelerate the 2-D method of characteristics (MOC) neutron transport calculation
In the two-level CMFD scheme, a few-group CMFD problem is used as a lower-order accelerator to the standard pinwise multi-group CMFD problem

Summary

Introduction

Significant advances in high-performance computing (HPC) systems enable the computational feasibility of high-fidelity, three-dimensional (3-D) whole-core neutron transport calculation. Several applications have been developed and deployed on the HPC systems based on the method of characteristics (MOC) (Askew, 1972). These applications employ the MOC as their routine 2-D or 3-D neutron transport method for practical whole-core simulations. The MOC code nTRACER (Jung et al, 2013) was developed as direct whole-core simulator by Seoul National University. Χg is the normalized fission spectrum, and keff represents the effective neutron multiplication factor or eigenvalue of the system. Equation (1) can be integrated along the characteristic line within a flat source region. The angular flux along the characteristic line can be expressed as Equation (3). The average angular flux along a specific segment is calculated by Equation (4)

Methods

Results

Conclusion