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

页码：40 / 51

页数：12

共 50 条

[41] Analysis of the ionization potentials of small superalkali lithium clusters based on quantum Monte Carlo simulations
Brito, B. G. A.
Hai, G. -Q.
Candido, Ladir
[J]. CHEMICAL PHYSICS LETTERS, 2018, 708 : 54 - 60
[42] Delayed Update Algorithms for Quantum Monte Carlo Simulation on GPU
McDaniel, Tyler
D'Azevedo, Ed
Li, Ying Wai
Kent, Paul
Wong, Ming
Wong, Kwai
[J]. PROCEEDINGS OF XSEDE16: DIVERSITY, BIG DATA, AND SCIENCE AT SCALE, 2016,
[43] GPU-accelerated variational path integral Monte Carlo simulations
Hinde, Robert J.
Harrison, Robert
Peterson, Greg
Kakani, Venkata Prasanth
Mudhasani, Shanthan
[J]. ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, 2010, 240
[44] GPU implementation of the Rosenbluth generation method for static Monte Carlo simulations
Guo, Yachong
Baulin, Vladimir A.
[J]. COMPUTER PHYSICS COMMUNICATIONS, 2017, 216 : 95 - 101
[45] Quantum Monte Carlo simulations of tunneling in quantum adiabatic optimization
Brady, Lucas T.
van Dam, Wim
[J]. PHYSICAL REVIEW A, 2016, 93 (03)
[46] Understanding Quantum Tunneling through Quantum Monte Carlo Simulations
Isakov, Sergei V.
Mazzola, Guglielmo
Smelyanskiy, Vadim N.
Jiang, Zhang
Boixo, Sergio
Neven, Hartmut
Troyer, Matthias
[J]. PHYSICAL REVIEW LETTERS, 2016, 117 (18)
[47] Accelerating Convergence in Fock Space Quantum Monte Carlo Methods
Neufeld, Verena A.
Thom, Alex J. W.
[J]. JOURNAL OF CHEMICAL THEORY AND COMPUTATION, 2020, 16 (03) : 1503 - 1510
[48] GPU-Accelerated Monte Carlo Simulations of Dense Stellar Systems
Pattabiraman, B.
Umbreit, S.
Liao, W.
Rasio, F.
Kalogera, V.
Choudhary, A.
[J]. ADVANCES IN COMPUTATIONAL ASTROPHYSICS: METHODS, TOOLS AND OUTCOMES, 2012, 453 : 329 - 332
[49] Deep Particles Embedding: accelerating Monte-Carlo dose simulations
Martinot, S.
Komodakis, N.
Vakalopoulou, M.
Bus, N.
Robert, C.
Deutsch, E.
Paragios, N.
[J]. RADIOTHERAPY AND ONCOLOGY, 2023, 182 : S1526 - S1527
[50] Accelerating Hybrid Monte Carlo simulations of the Hubbard model on the hexagonal lattice
Krieg, Stefan
Luu, Thomas
Ostmeyer, Johann
Papaphilippou, Philippos
Urbach, Carsten
[J]. COMPUTER PHYSICS COMMUNICATIONS, 2019, 236 : 15 - 25

← 1 2 3 4 5 →