Accelerated molecular dynamics simulation of Silicon Crystals on TaihuLight using OpenACC

Liang, Jianguo; Hua, Rong; Zhang, Hao; Zhu, Wenqiang; Fu, You

doi:10.1016/j.parco.2020.102667

Cited by 4 publications

(2 citation statements)

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“…Second, it cannot copy only necessary data into GPU memory. To this end, we implement the conversion of data structure AOS to the structure of array (SOA) 19 …”

Section: Methodsmentioning

confidence: 99%

“…To give full play to the advantages of multi-scale parallel computing mode, Hou et al independently developed an efficient and highly scalable MD simulation program for crystalline silicon, and carried out large-scale heterogeneous parallel computing tests on Mole8.5 and Tianhe-1A. 9,10,18 Our work was mainly carried out on this basis, and we completed the parallel acceleration of OpenACC based bulk silicon MD simulation program on Sunway TaihuLight, 19 and then further improved its performance by using OpenACC+Athread. 20 Ami Marowka points out that the 3P challenges of high-performance programming-performance, portability, and productivity-have become more difficult than ever in the era of heterogeneous computing.…”

Section: Related Surveys and Our Contributionsmentioning

confidence: 99%

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A novel acceleration method for molecular dynamics of crystal silicon on GPUs using OpenACC

Liang

Hua

et al. 2022

Softw Pract Exp

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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.

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“…Second, it cannot copy only necessary data into GPU memory. To this end, we implement the conversion of data structure AOS to the structure of array (SOA) 19 …”

Section: Methodsmentioning

confidence: 99%