Boosting free-energy perturbation calculations with GPU-Accelerated NAMD

Haochuan Chen, Julio D.C. Maia, Brian K. Radak, David J. Hardy, Wensheng Cai, Christophe Chipot, Emad Tajkhorshid

Research output: Contribution to journalArticlepeer-review


Harnessing the power of graphics processing units (GPUs) to accelerate molecular dynamics (MD) simulations in the context of free-energy calculations has been a longstanding effort toward the development of versatile, high-performance MD engines. We report a new GPU-based implementation in NAMD of free-energy perturbation (FEP), one of the oldest, most popular importance-sampling approaches for the determination of free-energy differences that underlie alchemical transformations. Compared to the CPU implementation available since 2001 in NAMD, our benchmarks indicate that the new implementation of FEP in traditional GPU code is about four times faster, without any noticeable loss of accuracy, thereby paving the way toward more affordable free-energy calculations on large biological objects. Moreover, we have extended this new FEP implementation to a code path highly optimized for a single-GPU node, which proves to be up to nearly 30 times faster than the CPU implementation. Through optimized GPU performance, the present developments provide the community with a cost-effective solution for conducting FEP calculations. The new FEP-enabled code has been released with NAMD 3.0.

Original languageEnglish (US)
Pages (from-to)5301-5307
Number of pages7
JournalJournal of Chemical Information and Modeling
Issue number11
StatePublished - Nov 23 2020

ASJC Scopus subject areas

  • General Chemistry
  • General Chemical Engineering
  • Computer Science Applications
  • Library and Information Sciences


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