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Accelerating Quantum Monte Carlo Simulations of Real Materials on GPU Clusters
Jan.-Feb. 2012 (vol. 14 no. 1)
pp. 40-51
Kenneth P. Esler, University of Illinois at Urbana-Champaign
Jeongnim Kim, University of Illinois at Urbana-Champaign
David M. Ceperley, University of Illinois at Urbana-Champaign
Luke Shulenburger, Carnegie Institution of Washington

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.

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Index Terms:
Component, graphics processors, Monte Carlo, physics, scientific computing
Kenneth P. Esler, Jeongnim Kim, David M. Ceperley, Luke Shulenburger, "Accelerating Quantum Monte Carlo Simulations of Real Materials on GPU Clusters," Computing in Science and Engineering, vol. 14, no. 1, pp. 40-51, Jan.-Feb. 2012, doi:10.1109/MCSE.2010.122
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