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


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
Issue number1
StatePublished - Jan 2012


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

ASJC Scopus subject areas

  • General Computer Science
  • General Engineering


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