Accelerating Quantum Monte Carlo Simulations of Real Materials on GPU Clusters

K. Esler, Jeongnim Kim, David M. Ceperley, Luke Shulenburger

Computing in Science & Engineering · 2010 · 76 citations · 10 references

Concepts

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.

References

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