Open-Source Multi-GPU-Accelerated QM/MM Simulations with AMBER and QUICK

被引:31
|
作者
Cruzeiro, Vinicius Wilian D. [1 ,2 ]
Manathunga, Madushanka [3 ]
Merz, Kenneth M., Jr. [3 ]
Gotz, Andreas W. [1 ]
机构
[1] Univ Calif San Diego, San Diego Supercomp Ctr, La Jolla, CA 92093 USA
[2] Univ Calif San Diego, Dept Chem & Biochem, La Jolla, CA 92093 USA
[3] Michigan State Univ, Dept Chem, Dept Biochem & Mol Biol, Inst Cyber Enabled Res, E Lansing, MI 48824 USA
基金
美国国家科学基金会;
关键词
MOLECULAR-DYNAMICS SIMULATIONS; GRAPHICAL PROCESSING UNITS; REPULSION INTEGRAL EVALUATION; DENSITY-FUNCTIONAL THEORY; COUPLED-CLUSTER THEORY; PARTICLE MESH EWALD; QUANTUM-CHEMISTRY; HIGHLY EFFICIENT; IMPLEMENTATION; RESOLUTION;
D O I
10.1021/acs.jcim.1c00169
中图分类号
R914 [药物化学];
学科分类号
100701 ;
摘要
The quantum mechanics/molecular mechanics (QM/MM) approach is an essential and well-established tool in computational chemistry that has been widely applied in a myriad of biomolecular problems in the literature. In this publication, we report the integration of the QUantum Interaction Computational Kernel (QUICK) program as an engine to perform electronic structure calculations in QM/MM simulations with AMBER. This integration is available through either a file-based interface (FBI) or an application programming interface (API). Since QUICK is an open-source GPU-accelerated code with multi-GPU parallelization, users can take advantage of "free of charge" GPU-acceleration in their QM/MM simulations. In this work, we discuss implementation details and give usage examples. We also investigate energy conservation in typical QM/MM simulations performed at the microcanonical ensemble. Finally, benchmark results for two representative systems in bulk water, the N-methylacetamide (NMA) molecule and the photoactive yellow protein (PYP), show the performance of QM/MM simulations with QUICK and AMBER using a varying number of CPU cores and GPUs. Our results highlight the acceleration obtained from a single or multiple GPUs; we observed speedups of up to 53x between a single GPU vs a single CPU core and of up to 2.6x when comparing four GPUs to a single GPU. Results also reveal speedups of up to 3.5x when the API is used instead of FBI.
引用
收藏
页码:2109 / 2115
页数:7
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