Accelerating Quantum Monte Carlo Simulations of Real Materials on GPU Clusters

被引：57
|
作者：
Esler, Kenneth P. [1 ]
Kim, Jeongnim [1 ]
Ceperley, David M. [2 ]
Shulenburger, Luke [3 ]
机构：
[1] Univ Illinois, NCSA, Urbana, IL 61801 USA
[2] Univ Illinois, Dept Phys, Urbana, IL 61801 USA
[3] Carnegie Inst Sci, Washington, DC 20005 USA
来源：
COMPUTING IN SCIENCE & ENGINEERING | 2012年 / 14卷 / 01期
基金：
美国国家科学基金会;
关键词：
Component; graphics processors; Monte Carlo; physics; scientific computing;
D O I：
10.1109/MCSE.2010.122
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
More accurate than mean-field methods and more scalable than quantum chemical methods, continuum quantum Monte Carlo (QMC) is an invaluable tool for predicting the properties of matter from fundamental principles. Because QMC algorithms offer multiple forms of parallelism, they're ideal candidates for acceleration in the many-core paradigm.
引用
收藏
页码：40 / 51
页数：12
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