Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Rongfen Lin"'
Autor:
Honghui Shang, Li Shen, Yi Fan, Zhiqian Xu, Chu Guo, Jie Liu, Wenhao Zhou, Huan Ma, Rongfen Lin, Yuling Yang, Fang Li, Zhuoya Wang, Yunquan Zhang, Zhenyu Li
Publikováno v:
SC22: International Conference for High Performance Computing, Networking, Storage and Analysis.
Quantum computational chemistry (QCC) is the use of quantum computers to solve problems in computational quantum chemistry. We develop a high performance variational quantum eigensolver (VQE) simulator for simulating quantum computational chemistry p
Autor:
Mingfan Li, Qian Xiao, Junshi Chen, Rongfen Lin, Fei Wang, Guang R. Gao, Han Lin, Jose Monsalve Diaz, Hong An
Publikováno v:
Information Sciences. 570:831-847
Deep learning technology is widely used in many modern fields and a number of models and software frameworks have been proposed. However, it is still very difficult to process deep learning tasks efficiently on traditional high performance computing
Autor:
Hong An, Rongfen Lin, Han Lin, Mingfan Li, Fei Wang, Junshi Chen, Guofeng Lv, Wenting Han, Qian Xiao
Publikováno v:
CCF Transactions on High Performance Computing. 2:348-361
To explore the potential of distributed training on deep neural networks, we implement several distributed algorithms with the basis of swFlow on the world-leading supercomputer, Sunway TaihuLight. Based on two naive designs of parameter server and r
Autor:
Yunquan Zhang, Yingxiang Gao, Dexun Chen, You Fu, Xiaohui Duan, Libo Zhang, Honghui Shang, Xin Liu, Fang Li, Yangjun Wu, Rongfen Lin, Ying Liu
Publikováno v:
SC
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,
Autor:
Fang Li, Qiang Sun, Qian Xiao, Xing-Yu Gao, Lei Xu, Chen Xin, Hai-Feng Song, Rongfen Lin, Leilei Zhu, Honghui Shang, Li-Fang Wang, Yunquan Zhang, Fei Wang
Publikováno v:
SC
The atomic kinetic Monte Carlo method plays an important role in multi-scale physical simulations because it bridges the micro and macro worlds. However, its accuracy is limited by empirical potentials. We therefore propose herein a triple-encoding a
Autor:
Mingfan Li, Junshi Chen, Qian Xiao, Fei Wang, Qingcai Jiang, Xuncheng Zhao, Rongfen Lin, Hong An, Xiao Liang, Lixin He
Efficient numerical methods are promising tools for delivering unique insights into the fascinating properties of physics, such as the highly frustrated quantum many-body systems. However, the computational complexity of obtaining the wave functions
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e3b6704723074479e946a8574e60f4c1
http://arxiv.org/abs/2108.13830
http://arxiv.org/abs/2108.13830
Autor:
Rongfen Lin, Chao Yang, Qiao Sun, Lijuan Jiang, Peng Zhang, Wanwang Yin, Wenjing Ma, Yulong Ao, Fangfang Liu
Publikováno v:
ICPP
The matrix-matrix multiplication is an essential building block that can be found in various scientific and engineering applications. High-performance implementations of the matrix-matrix multiplication on state-of-the-art processors may be of great
Publikováno v:
SYNASC
In this paper, the problem of finding all zeros of an continuously interval function in a given interval is considered.A new method for solving this problem is proposed. It is based on the idea of isolating the endpoints of interval zeros and the tec