Hernández-Esparza Raymundo, Mejía-Chica Sol-Milena, Zapata-Escobar Andy D, Guevara-García Alfredo, Martínez-Melchor Apolinar, Hernández-Pérez Julio-M, Vargas Rubicelia, Garza Jorge
Departamento de Química, Universidad Autónoma Metropolitana-Iztapalapa, San Rafael Atlixco 186. Col. Vicentina, Iztapalapa, C. P. 09340, México.
J Comput Chem. 2014 Dec 5;35(31):2272-8. doi: 10.1002/jcc.23752.
Using a grid-based method to search the critical points in electron density, we show how to accelerate such a method with graphics processing units (GPUs). When the GPU implementation is contrasted with that used on central processing units (CPUs), we found a large difference between the time elapsed by both implementations: the smallest time is observed when GPUs are used. We tested two GPUs, one related with video games and other used for high-performance computing (HPC). By the side of the CPUs, two processors were tested, one used in common personal computers and other used for HPC, both of last generation. Although our parallel algorithm scales quite well on CPUs, the same implementation on GPUs runs around 10× faster than 16 CPUs, with any of the tested GPUs and CPUs. We have found what one GPU dedicated for video games can be used without any problem for our application, delivering a remarkable performance, in fact; this GPU competes against one HPC GPU, in particular when single-precision is used.
通过基于网格的方法搜索电子密度中的关键点，我们展示了如何使用图形处理单元（GPU）加速该方法。当将GPU实现与中央处理器（CPU）上使用的实现进行对比时，我们发现两种实现所花费的时间存在很大差异：使用GPU时观察到的时间最短。我们测试了两个GPU，一个与视频游戏相关，另一个用于高性能计算（HPC）。在CPU方面，测试了两个处理器，一个用于普通个人计算机，另一个用于HPC，两者均为最新一代。尽管我们的并行算法在CPU上扩展性相当好，但在任何测试的GPU和CPU上，相同的实现方式在GPU上运行的速度比16个CPU快约10倍。我们发现，专门用于视频游戏的一个GPU可以毫无问题地用于我们的应用程序，实际上还能提供出色的性能；该GPU可与一个HPC GPU相媲美，特别是在使用单精度时。
