Zobrazeno 1 - 10
of 976
pro vyhledávání: '"Chen, Junshi"'
First-principles density functional theory (DFT) with plane wave (PW) basis set is the most widely used method in quantum mechanical material simulations due to its advantages in accuracy and universality. However, a perceived drawback of PW-based DF
Externí odkaz:
http://arxiv.org/abs/2406.10765
The performance gap between memory and processor has grown rapidly. Consequently, the energy and wall-clock time costs associated with moving data between the CPU and main memory predominate the overall computational cost. The Processing-in-Memory (P
Externí odkaz:
http://arxiv.org/abs/2402.18592
Autor:
Qiao, Liang, Shi, Jun, Hao, Xiaoyu, Fang, Xi, Zhao, Minfan, Zhu, Ziqi, Chen, Junshi, An, Hong, Li, Bing, Yuan, Honghui, Wang, Xinyang, Tang, Xulong
Tensor program tuning is essential for the efficient deployment of deep neural networks. Search-based approaches have demonstrated scalability and effectiveness in automatically finding high-performance programs for specific hardware. However, the se
Externí odkaz:
http://arxiv.org/abs/2402.02361
Radio signals are used broadly as navigation aids, and current and future terrestrial wireless communication systems have properties that make their dual-use for this purpose attractive. Sub-6 GHz carrier frequencies enable widespread coverage for da
Externí odkaz:
http://arxiv.org/abs/2309.02121
Opportunistic navigation using cellular signals is appealing for scenarios where other navigation technologies face challenges. In this paper, long-term evolution (LTE) downlink signals from two neighboring commercial base stations (BS) are received
Externí odkaz:
http://arxiv.org/abs/2301.07560
Accurate understanding of electromagnetic propagation properties in real environments is necessary for efficient design and deployment of cellular systems. In this paper, we show a method to estimate high-resolution channel parameters with a massive
Externí odkaz:
http://arxiv.org/abs/2211.09746
Autor:
Liang, Xiao, Li, Mingfan, Xiao, Qian, An, Hong, He, Lixin, Zhao, Xuncheng, Chen, Junshi, Yang, Chao, Wang, Fei, Qian, Hong, Shen, Li, Jia, Dongning, Gu, Yongjian, Liu, Xin, Wei, Zhiqiang
Publikováno v:
2023 Mach. Learn.: Sci. Technol. 4 015035
For decades, people are developing efficient numerical methods for solving the challenging quantum many-body problem, whose Hilbert space grows exponentially with the size of the problem. However, this journey is far from over, as previous methods al
Externí odkaz:
http://arxiv.org/abs/2204.07816
Autor:
Gu, Jun, Feng, Jiawang, Hao, Xiaoyu, Fang, Tao, Zhao, Chun, An, Hong, Chen, Junshi, Xu, Mingyue, Li, Jian, Han, Wenting, Yang, Chao, Li, Fang, Chen, Dexun
During the era of global warming and highly urbanized development, extreme and high impact weather as well as air pollution incidents influence everyday life and might even cause the incalculable loss of life and property. Although with the vast deve
Externí odkaz:
http://arxiv.org/abs/2112.04668
Autor:
Jiang, Qingcai, Cao, Zhenwei, Cui, Xinhui, Wan, Lingyun, Qin, Xinming, Cao, Huanqi, An, Hong, Chen, Junshi, Liu, Jie, Hu, Wei, Yang, Jinlong
Publikováno v:
In Parallel Computing June 2024 120
Autor:
Li, Mingfan, Chen, Junshi, Xiao, Qian, Jiang, Qingcai, Zhao, Xuncheng, Lin, Rongfen, Wang, Fei, An, Hong, Liang, Xiao, He, Lixin
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:
http://arxiv.org/abs/2108.13830