使用图形处理器（GPU）加速量子力学/分子力学-量子蒙特卡罗（QM/MM-QMC）模拟
Acceleration of a QM/MM-QMC simulation using GPU.
作者信息
Uejima Yutaka, Terashima Tomoharu, Maezono Ryo
机构信息
School of Information Science, Japan Advanced Institute of Science and Technology, Asahidai 1-1, Nomi, Ishikawa 923-1292, Japan.
出版信息
J Comput Chem. 2011 Jul 30;32(10):2264-72. doi: 10.1002/jcc.21809. Epub 2011 May 3.
We accelerated an ab initio molecular QMC calculation by using GPGPU. Only the bottle-neck part of the calculation is replaced by CUDA subroutine and performed on GPU. The performance on a (single core CPU + GPU) is compared with that on a (single core CPU with double precision), getting 23.6 (11.0) times faster calculations in single (double) precision treatments on GPU. The energy deviation caused by the single precision treatment was found to be within the accuracy required in the calculation, ∼10(-5) hartree. The accelerated computational nodes mounting GPU are combined to form a hybrid MPI cluster on which we confirmed the performance linearly scales to the number of nodes.
我们通过使用通用并行图形处理单元（GPGPU）加速了从头算分子量子蒙特卡罗（QMC）计算。仅计算中的瓶颈部分被统一计算设备架构（CUDA）子程序替换并在图形处理器（GPU）上执行。将（单核中央处理器+GPU）的性能与（具有双精度的单核中央处理器）的性能进行比较，发现在GPU上进行单精度（双精度）处理时计算速度快23.6（11.0）倍。发现单精度处理引起的能量偏差在计算所需的精度范围内，约为10^(-5)哈特里。安装了GPU的加速计算节点被组合形成一个混合消息传递接口（MPI）集群，在该集群上我们确认性能随节点数量线性扩展。
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