上海交通大学学报(自然版) ›› 2013, Vol. 47 ›› Issue (08): 1198-1204.

• 航空、航天 • 上一篇    下一篇

基于计算统一设备架物Fortran的直接模拟蒙特卡洛方法并行优化

严立,戴欣怡,陈佳洛,王平阳,欧阳华   

  1. (上海交通大学 机械与动力工程学院,上海 200240)
     
  • 收稿日期:2012-10-30 出版日期:2013-08-29 发布日期:2013-08-29
  • 基金资助:

    上海市自然科学基金(12ZR1414700),上海交通大学研究生创新能力培养专项基金资助项目

Parallel Optimization of Direct Simulation Monte Carlo Method Using Compute Unified Device Architecture Fortran

YAN Li,DAI Xinyi,CHEN Jialuo,WANG Pingyang,OUYANG Hua
  

  1. (School of Mechanical Engineering, Shanghai Jiaotong University, Shanghai 200240, China)
  • Received:2012-10-30 Online:2013-08-29 Published:2013-08-29

摘要:

利用基于图形处理器(GPU)的计算统一设备架构(CUDA) Fortran编程平台,对直接模拟蒙特卡洛(DSMC)方法进行并行优化,并以高超声速气动热计算为例,考察了串行与并行计算速度以及不同仿真分子数对并行效率的影响.结果表明,在保证计算精度不变的情况下,程序取得了4~10倍的加速比,并且加速性能高低与计算规模大小成正比.
 
 

关键词: 直接模拟蒙特卡洛; Fortran; 图形处理器; 计算统一设备架构, 气动热

Abstract:

Direct simulation Monte Carlo (DSMC) method is currently the most widely used numerical method for rarefied flow calculation. Based on the Fortran programming platform of GPU (Graphics Processing Unit) and CUDA (Compute Unified Device Architecture), the DSMC method was optimized. Taking the calculation of high supersonic aerodynamic heating as an example, the effect of serial and parallel computing speed and simulation molecules on parallel efficiency was studied. The comparison shows that the parallel results are consistent with each other and parallel program achieved an acceleration of 4 to 10 times. And accelerating performance is proportional to the size of calculation. The application of GPU parallel technology will greatly promote the development of DSMC method.
 

Key words: direct simulation Monte Carlo (DSMC), Fortran, graphic processing unit (GPU), compute unified device architecture (CUDA), aerodynamic heating

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