The general distributed data interface (GDDI) that was developed for the fragment molecular orbital (FMO) method is combined with the shared memory OpenMP parallel middleware to support a threading multilevel parallelism. First, GDDI partitions [logical] compute nodes into groups, which are statically or dynamically assigned to different fragments. A small number of processes are created on each compute node. Each process subsequently spawns multiple threads for the actual computation. The performance of the hybrid GDDI/OpenMP approach relative to the pure GDDI model was examined in terms of the FMO/RI-MP2 method; that is, the second-order Moller-Plesset (MP2) correlation energy was evaluated using the resolution-of-the-identity (RI) and the FMO approximations. The GDDI and OpenMP workload balances are handled by an arithmetic progression and a loop fusion, respectively. Other OpenMP properties, such as or shared memory, are combined with the low memory demand of the RI two-electron integrals to enhance the performance. Benchmark calculations demonstrate that because the hybrid parallel model can make use of multiprocessor resources more efficiently than the regular distributed memory-based GDDI model, calculations for small to large water clusters containing 139-2165 molecules and an ionic liquid cluster exhibit node linear scaling and speedups of a factor of 10×.
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http://dx.doi.org/10.1021/acs.jctc.9b00409 | DOI Listing |
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