Harvey M J, De Fabritiis G
High Performance Computing Service, Information and Communications Technologies, Imperial College London, South Kensington, London, SW7 2AZ, United Kingdom and Computational Biochemistry and Biophysics Lab (GRIB-IMIM), Universitat Pompeu Fabra, Barcelona Biomedical Research Park (PRBB), C/ Doctor Aiguader 88, 08003 Barcelona, Spain.
J Chem Theory Comput. 2009 Sep 8;5(9):2371-7. doi: 10.1021/ct900275y.
The smooth particle mesh Ewald summation method is widely used to efficiently compute long-range electrostatic force terms in molecular dynamics simulations, and there has been considerable work in developing optimized implementations for a variety of parallel computer architectures. We describe an implementation for Nvidia graphical processing units (GPUs) which are general purpose computing devices with a high degree of intrinsic parallelism and arithmetic performance. We find that, for typical biomolecular simulations (e.g., DHFR, 26K atoms), a single GPU equipped workstation is able to provide sufficient performance to permit simulation rates of ≈50 ns/day when used in conjunction with the ACEMD molecular dynamics package (1) and exhibits an accuracy comparable to that of a reference double-precision CPU implementation.
光滑粒子网格埃瓦尔德求和方法被广泛用于在分子动力学模拟中高效计算长程静电力项,并且在为各种并行计算机架构开发优化实现方面已经有了大量工作。我们描述了一种针对英伟达图形处理单元(GPU)的实现,GPU是具有高度内在并行性和算术性能的通用计算设备。我们发现,对于典型的生物分子模拟(例如,二氢叶酸还原酶,26K个原子),配备单个GPU的工作站与ACEMD分子动力学软件包(1)结合使用时,能够提供足够的性能,允许模拟速率达到约50纳秒/天,并且其精度与参考双精度CPU实现相当。