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Parallelization of the Fast Multipole Method for Molecular Dynamics Simulations on Multicore Computers

机译:快速多极方法的并行化,用于多核计算机上的分子动力学模拟

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We have parallelized the fast multipole method (FMM) on multicore computers using OpenMP programming model. The FMM is the one of the fastest approximate force calculation algorithms for molecular dynamics simulations. Its computational complexity is linear. Parallelization of FMM on multicore computers using OpenMP has been reported since the multicore processors become increasingly popular. However the number of those FMM implementations is not large. The main reason is that those FMM implementations have moderate or low parallel efficiency for high expansion orders due to sophisticated formulae of the FMM. In addition, parallel efficiency of those implementations for high expansion orders rapidly drops to 40% or lower as the number of threads increases to 8 or higher. Our FMM implementation on multicore computers using a combination approach as well as a newly developed formula and a computational procedure (A2P) solved the above issues. Test results of our FMM implementation on a multicore computer show that our parallel efficiency with 8 threads is at least 70% for moderate and high expansion orders p = 4, 5,6, 7. Moreover, the parallel efficiency for moderate and high expansion orders gradually drops from 96% to 70% as the number of threads increases.
机译:我们已经使用OpenMP编程模型在多核计算机上并行化了快速多极方法(FMM)。 FMM是用于分子动力学模拟的最快的近似力计算算法之一。它的计算复杂度是线性的。自从多核处理器变得越来越流行以来,已经报道了使用OpenMP在多核计算机上并行化FMM。但是,那些FMM实现的数量并不多。主要原因是由于FMM的公式复杂,这些FMM实现对于高扩展订单具有中等或较低的并行效率。此外,随着线程数增加到8个或更多,这些实现的并行执行效率在高扩展级时迅速下降到40%或更低。我们在多核计算机上使用组合方法以及新开发的公式和计算过程(A2P)来实施FMM解决了上述问题。在多核计算机上执行FMM的测试结果表明,对于中等和高扩展阶数,我们的8个线程的并行效率至少为70%p = 4,5,6,7。此外,对于中等和高扩展阶数的并行效率随着线程数量的增加,从96%逐渐下降到70%。

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