Abstract Compared with CUDA and OpenCL, OpenACC has the advantages of simple programming, openness, and good portability for GPU acceleration. An OpenMP/OpenACC implementation for molecular dynamics of silicon crystal on GPUs is proposed. First, to make effective use of vectorization and streaming, data structure conversion and data dependence elimination are designed. Second, the parallel version on the single GPU is realized by adding OpenACC guidance sentences, with very few modifications. Third, a patch block strategy is proposed to realize the parallel version on single machine multi‐GPUs using OpenMP+OpenACC, which greatly simplifies the construction of shadow area and the exchange of shadow area data. Experimental results show that 23 to 25 speedup is achieved for the single GPU at different scales over the serial program on Intel(R) Xeon(R) CPU E5‐2690 v4, and 6.37 speedup is achieved over the single GPU when the number of atoms reaches 2,097,152 on 8GPUs on single machine.

Raman spectroscopy provides chemical and compositional information that can serve as a structural fingerprint for various materials. Therefore, simulations of Raman spectra, including both quantum perturbation analyses and ground-state calculations are of significant interest. However, highly accurate full quantum mechanical (QM) simulations of Raman spectra have previously been confined to small systems. For large systems such as biological materials, the computational cost of full QM simulations is extremely high, and their extension to such systems remains challenging. In the work described here, by employing robust new algorithms and advances in implementation for the many-core architectures, we are able to perform fast, accurate, and massively parallel full ab initio simulations of the Raman spectra of biological systems with excellent strong and weak scaling, thereby providing a starting point for applying QM approaches to structural studies of such systems.