Graphics Processing Unit Acceleration and Parallelization of GENESIS for Large-Scale Molecular Dynamics Simulations

The graphics processing unit (GPU) has become a popular computational platform for molecular dynamics (MD) simulations of biomolecules. A significant speedup in the simulations of small- or medium-size systems using only a few computer nodes with a single or multiple GPUs has been reported. Because of GPU memory limitation and slow communication between GPUs on different computer nodes, it is not straightforward to accelerate MD simulations of large biological systems that contain a few million or more atoms on massively parallel supercomputers with GPUs. In this study, we develop a new scheme in our MD software, GENESIS, to reduce the, total computational time on such computers. Computationally intensive real-space nonbonded interactions are computed mainly on GPUs in the scheme, while less intensive bonded interactions and communication intensive reciprocal-space interactions are performed on CPUs. On the basis of the midpoint cell method as a domain decomposition scheme, we invent the single particle interaction list for reducing the GPU memory usage. Since total computational time is limited by the reciprocal-space computation, we utilize the RESPA multiple time-step integration and reduce the CPU resting time by assigning a subset of nonbonded interactions on CPUs as well as on GPUs when the reciprocal space computation is skipped. We validated our GPU implementations in GENESIS on BPTI and a membrane protein, porin, by MD simulations and an alanine-tripeptide by REMD simulations. Benchmark calculations on TSUBAME supercomputer showed that an MD simulation of a million atoms system was scalable up to 256 computer nodes with GPUs.