【摘要】 基于计算机的分子动力学仿真具有理论分析方法和实验方法无法比拟的优点,但分子动力学仿真算法计算量非常大,特别是在对碳纳米管的大规模粒子数进行仿真处理时,普通的基于CPU的串行算法执行效率低且耗时多。为此,提出基于统一计算设备架构的碳纳米管分子动力学的图形处理单元(GPU)并行算法,设计并实现仿真算法中适合GPU并行运算的分裂算法,将具有竞争资源的运算以非竞争方式运行。实验结果表明,与CPU串行仿真算法相比,分裂算法的运算速度较快,且在只有16个GPU流处理器显卡上可获得十多倍的加速比。更多还原

【Abstract】 Molecular dynamics simulation has advantages dramatically superior to both theoretical analysis and experiments. How ever,due to the extremely high cost of computation resources during the simulation of a large number of Carbon Nano Tube( CNT) particles,typical CPU serial algorithm implementation is non-efficient and slow. A Compute Unified Device Architecture( CUDA) based parallel algorithm of CNT molecular dynamics is proposed in this paper to take advantage of the data parallelism of Graphic Processing Unit( GPU). A CNT is divided to several blocks and processed parallel in the GPU. Experimental results show that the algorithm can obtain a speed-up more than 10 times to the CPU serial algorithm in a low-configured graphics card that has only 16 GPU stream processors.更多还原