The linearly scaling 3D fragment method for large scale electronic structure calculations [electronic resource].
- Published:
- Berkeley, Calif. : Lawrence Berkeley National Laboratory, 2009.
Oak Ridge, Tenn. : Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy. - Physical Description:
- 5 : digital, PDF file
- Additional Creators:
- Lawrence Berkeley National Laboratory and United States. Department of Energy. Office of Scientific and Technical Information
Access Online
- Restrictions on Access:
- Free-to-read Unrestricted online access
- Summary:
- The Linearly Scaling three-dimensional fragment (LS3DF) method is an O(N) ab initio electronic structure method for large-scale nano material simulations. It is a divide-and-conquer approach with a novel patching scheme that effectively cancels out the artificial boundary effects, which exist in all divide-and-conquer schemes. This method has made ab initio simulations of thousand-atom nanosystems feasible in a couple of hours, while retaining essentially the same accuracy as the direct calculation methods. The LS3DF method won the 2008 ACM Gordon Bell Prize for algorithm innovation. Our code has reached 442 Tflop/s running on 147,456 processors on the Cray XT5 (Jaguar) at OLCF, and has been run on 163,840 processors on the Blue Gene/P (Intrepid) at ALCF, and has been applied to a system containing 36,000 atoms. In this paper, we will present the recent parallel performance results of this code, and will apply the method to asymmetric CdSe/CdS core/shell nanorods, which have potential applications in electronic devices and solar cells.
- Report Numbers:
- E 1.99:lbnl-2857e
lbnl-2857e - Other Subject(s):
- Note:
- Published through SciTech Connect.
07/28/2009.
"lbnl-2857e"
Wang, Lin-Wang; Strohmaier, Erich; Shan, Hongzhang; Bailey, David; Meza, Juan; Lee, Byounghak; Zhao, Zhengji.
Computational Research Division
National Energy Research Scientific Computing Division - Funding Information:
- DE-AC02-05CH11231
View MARC record | catkey: 14444384