NECP-X的多重并行策略及效率优化

Multilevel Parallel Strategy and Efficiency Optimization in NECP-X

  • 摘要: 特征线方法在应用于全堆芯三维输运计算时面临着计算时间长、内存需求量大的问题,而大规模并行是最有效的解决办法。我国超级计算机的快速发展使大规模并行计算逐渐成为可能,而如何发展相应的并行算法成为当务之急。本文基于数值反应堆物理计算程序NECP-X研究特征线方法的空间、角度和特征线多重并行策略。为实现高效并行,空间并行采用了区域分解的并行方式;为充分考虑角度并行的负载平衡,采用了“贪婪算法”角度区域分解算法;为节省内存和提高效率,应用并分析了共享式内存并行模式下动态调度的特征线并行方案。数值结果表明,NECP-X中的空间、角度和特征线并行效率较高,可充分利用并行资源,实现大规模并行。

     

    Abstract: Long computing time and abundant memory requirement are two most critical issues for the method of characteristics (MOC) applied for the three-dimensional whole-core transport calculation. The massive parallel is an effective method to solve these problems. With the rapid development of supercomputers in China, massive parallel computing is becoming possible. How to develop parallel algorithm becomes a top priority. In this paper, a multilevel parallel strategy of space, angle and characteristic rays was studied in the numerical reactor neutronics code NECP-X. To realize efficient parallel computing, space parallel was developed based on domain decomposition method. To get good load-balance of angle parallel, a greed algorithm for angle domain decomposition was applied. To save memory and increase efficiency in the characteristic ray parallel, a dynamic scheduling feature within shared memory architectures was used and analyzed. The numerical results show that the parallel efficiency of space, angle and characteristic rays in NECP-X is high. NECP-X can take full advantage of parallel resources and achieve large-scale parallelism.

     

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