TY - JOUR
T1 - Boosting free-energy perturbation calculations with GPU-Accelerated NAMD
AU - Chen, Haochuan
AU - Maia, Julio D.C.
AU - Radak, Brian K.
AU - Hardy, David J.
AU - Cai, Wensheng
AU - Chipot, Christophe
AU - Tajkhorshid, Emad
N1 - Publisher Copyright:
© 2020 American Chemical Society.
PY - 2020/11/23
Y1 - 2020/11/23
N2 - 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.
AB - 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.
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U2 - 10.1021/acs.jcim.0c00745
DO - 10.1021/acs.jcim.0c00745
M3 - Article
C2 - 32805108
AN - SCOPUS:85096814576
SN - 1549-9596
VL - 60
SP - 5301
EP - 5307
JO - Journal of Chemical Information and Modeling
JF - Journal of Chemical Information and Modeling
IS - 11
ER -