Accelerating quantum monte carlo simulations of real materials on GPU clusters

Kenneth Esler, Jeongnim Kim, David Ceperley, Luke Shulenburger

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish (US)
Article number5601669
Pages (from-to)40-51
Number of pages12
JournalComputing in Science and Engineering
Volume14
Issue number1
DOIs
StatePublished - Jan 1 2012

Keywords

  • Component
  • graphics processors
  • Monte Carlo
  • physics
  • scientific computing

ASJC Scopus subject areas

  • Computer Science(all)
  • Engineering(all)

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