Title :
Accelerating Quantum Monte Carlo Simulations of Real Materials on GPU Clusters
Author :
Esler, K.P. ; Kim, Jeongnim ; Ceperley, D.M. ; Shulenburger, L.
Author_Institution :
Univ. of Illinois at Urbana-Champaign, Urbana, IL, USA
Abstract :
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.
Keywords :
Monte Carlo methods; graphics processing units; multiprocessing systems; parallel processing; quantum computing; GPU cluster; QMC algorithm; continuum quantum Monte Carlo simulation; many core paradigm; Computational modeling; Graphics processing unit; Mathematical model; Monte Carlo methods; Quantum methods; Wave functions; Component; Monte Carlo; graphics processors; physics; scientific computing;
Journal_Title :
Computing in Science & Engineering
DOI :
10.1109/MCSE.2010.122
