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Issue No. 01 - Jan.-Feb. (2012 vol. 14)
ISSN: 1521-9615
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
<p>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.</p>
Component, graphics processors, Monte Carlo, physics, scientific computing

K. P. Esler, L. Shulenburger, J. Kim and D. M. Ceperley, "Accelerating Quantum Monte Carlo Simulations of Real Materials on GPU Clusters," in Computing in Science & Engineering, vol. 14, no. , pp. 40-51, 2010.
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