基于CUDA技术的先进组件中子学程序异构并行研究

Study on CUDA-based Heterogeneous Parallel for Advanced Assembly Neutronics Program

为了提升先进组件中子学程序KYLIN-Ⅱ处理复杂边界条件问题的计算性能,基于可编程显卡异构并行技术对KYLIN-Ⅱ程序开展了异构并行化研究,实现了共振、输运等模块的海量线程并行计算,并通过优化迭代策略减少了异构并行程序的原子操作次数。为验证异构并行程序的计算精度和加速效果,针对AFA3G超级组件、六角形板型燃料组件、多层套管型燃料栅元等测试例题开展计算,计算结果表明,异构并行程序不会影响计算结果精度,单张显卡异构并行后的KYLIN-Ⅱ程序可以达到10倍以上的加速比,优化迭代流程可以有效减少计算耗时。相对于传统的基于中央处理器(CPU)的多核并行机制,显卡异构并行显著降低了KYLIN-II程序大规模并行需要的经济成本,可以作为KYLIN-Ⅱ程序开展进一步并行优化的方向。

To improve the calculation performance of the advanced assembly neutronics program KYLIN-Ⅱ when handling the complicated boundary condition,the current paper studied the heterogeneous parallel in the KYLIN-Ⅱ program based on heterogeneous parallel technology of programmable graphics card,implemented massive thread parallel computing of resonance and transport modules,and reduced the number of atomic operations of heterogeneous parallel program by optimizing iterative strategies.In order to verify the calculation accuracy and acceleration effect of heterogeneous parallel programs,calculations were carried out for test examples such as AFA3G super assembly,hexagonal plate fuel assembly and multilayer sleeve fuel cell.The results indicate that heterogeneous parallel programs will not affect the accuracy of calculation results.The KYLIN-Ⅱ program after heterogeneous parallel of a single graphics card can achieve an acceleration ratio of more than 10 times.Optimizing the iterative process can effectively reduce the calculation time.Compared with the traditional multi-core parallel mechanism based on central processing unit(CPU),heterogeneous parallel of graphics card significantly reduces the economic cost of large-scale parallel of KYLIN-Ⅱ program,which can be used as the direction of further parallel optimization of KYLIN-Ⅱ program.