Haochuan Chen, Julio D. C. Maia, Brian K. Radak, David J. Hardy, Wensheng Cai,
Christophe Chipot, and Emad Tajkhorshid.
Boosting free-energy perturbation calculations with GPU-accelerated
NAMD.
Journal of Chemical Information and Modeling, 60:5301-5307,
2020.
(PMC: PMC7686227)
CHEN2020-ET
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
towards 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 towards 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.
