Zobrazeno 1 - 10
of 80
pro vyhledávání: '"Jia, Xiaotao"'
Autor:
Duan, Cenlin, Yang, Jianlei, Wang, Yiou, Wang, Yikun, Qi, Yingjie, He, Xiaolin, Yan, Bonan, Wang, Xueyan, Jia, Xiaotao, Zhao, Weisheng
Bit-level sparsity in neural network models harbors immense untapped potential. Eliminating redundant calculations of randomly distributed zero-bits significantly boosts computational efficiency. Yet, traditional digital SRAM-PIM architecture, limite
Externí odkaz:
http://arxiv.org/abs/2404.09497
Autor:
Duan, Cenlin, Yang, Jianlei, He, Xiaolin, Qi, Yingjie, Wang, Yikun, Wang, Yiou, He, Ziyan, Yan, Bonan, Wang, Xueyan, Jia, Xiaotao, Pan, Weitao, Zhao, Weisheng
Processing-in-memory (PIM), as a novel computing paradigm, provides significant performance benefits from the aspect of effective data movement reduction. SRAM-based PIM has been demonstrated as one of the most promising candidates due to its enduran
Externí odkaz:
http://arxiv.org/abs/2310.20424
Autor:
Zhao, Yinglin, Yang, Jianlei, Li, Bing, Cheng, Xingzhou, Ye, Xucheng, Wang, Xueyan, Jia, Xiaotao, Wang, Zhaohao, Zhang, Youguang, Zhao, Weisheng
The performance and efficiency of running large-scale datasets on traditional computing systems exhibit critical bottlenecks due to the existing "power wall" and "memory wall" problems. To resolve those problems, processing-in-memory (PIM) architectu
Externí odkaz:
http://arxiv.org/abs/2204.09989
Autor:
Wang, Xueyan, Yang, Jianlei, Zhao, Yinglin, Jia, Xiaotao, Yin, Rong, Chen, Xuhang, Qu, Gang, Zhao, Weisheng
Publikováno v:
IEEE Transactions on Computers, 2021
Triangles are the basic substructure of networks and triangle counting (TC) has been a fundamental graph computing problem in numerous fields such as social network analysis. Nevertheless, like other graph computing problems, due to the high memory-c
Externí odkaz:
http://arxiv.org/abs/2112.00471
Autor:
Yang, Yaqian, Jia, Xiaotao, Yang, Xinmao, Wang, Jie, Fang, Yan, Ying, Xiaoping, Zhang, Meiqian, Wei, Jing, Pan, Yanfang
Publikováno v:
In Brain Research 15 July 2024 1835
Autor:
Wang, Xueyan, Yang, Jianlei, Zhao, Yinglin, Qi, Yingjie, Liu, Meichen, Cheng, Xingzhou, Jia, Xiaotao, Chen, Xiaoming, Qu, Gang, Zhao, Weisheng
Triangle counting (TC) is a fundamental problem in graph analysis and has found numerous applications, which motivates many TC acceleration solutions in the traditional computing platforms like GPU and FPGA. However, these approaches suffer from the
Externí odkaz:
http://arxiv.org/abs/2007.10702
Computing-in-memory (CIM) is proposed to alleviate the processor-memory data transfer bottleneck in traditional Von-Neumann architectures, and spintronics-based magnetic memory has demonstrated many facilitation in implementing CIM paradigm. Since ha
Externí odkaz:
http://arxiv.org/abs/2006.01425
Bayesian method is capable of capturing real world uncertainties/incompleteness and properly addressing the over-fitting issue faced by deep neural networks. In recent years, Bayesian Neural Networks (BNNs) have drawn tremendous attentions of AI rese
Externí odkaz:
http://arxiv.org/abs/2005.03857
Bayesian inference is an effective approach for solving statistical learning problems, especially with uncertainty and incompleteness. However, Bayesian inference is a computing-intensive task whose efficiency is physically limited by the bottlenecks
Externí odkaz:
http://arxiv.org/abs/1902.06886
Autor:
Yang, Yaqian, Jia, Xiaotao, Qu, Mengyang, Yang, Xinmao, Fang, Yan, Ying, Xiaoping, Zhang, Meiqian, Wei, Jing, Pan, Yanfang
Publikováno v:
In Heliyon June 2023 9(6)