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Approximate data mapping in refresh-free DRAM for energy-efficient computing in modern mobile systems 期刊论文
COMPUTER COMMUNICATIONS, 2024, 卷号: 216, 页码: 151-158
作者:  Li, Sen;  Jin, Hui;  Gao, Yingke;  Wang, Ying;  Dai, Shuhong;  Xu, Yongjun;  Cheng, Long
收藏  |  浏览/下载:36/0  |  提交时间:2024/05/20
DRAM  Refresh  Approximate computing  Energy efficiency  Mobile communication systems  
10-Million Atoms Simulation of First-Principle Package LS3DF 期刊论文
JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY, 2024, 卷号: 39, 期号: 1, 页码: 45-62
作者:  Yan, Yu-Jin;  Li, Hai-Bo;  Zhao, Tong;  Wang, Lin-Wang;  Shi, Lin;  Liu, Tao;  Tan, Guang-Ming;  Jia, Wei-Le;  Sun, Ning-Hui
收藏  |  浏览/下载:1/0  |  提交时间:2024/12/06
single instruction multiple thread accelerator  electronic structure  high-performance computing  linearly scaling three-dimensional fragment (LS3DF)  
In-Memory Wallace Tree Multipliers Based on Majority Gates Within Voltage-Gated SOT-MRAM Crossbar Arrays 期刊论文
IEEE TRANSACTIONS ON VERY LARGE SCALE INTEGRATION (VLSI) SYSTEMS, 2024, 页码: 8
作者:  Hui, Yajuan;  Li, Qingzhen;  Wang, Leimin;  Liu, Cheng;  Zhang, Deming;  Miao, Xiangshui
收藏  |  浏览/下载:21/0  |  提交时间:2024/05/20
In-memory computing  majority gates  voltage-gated SOT-MRAM  Wallace tree multiplier  
Association between gaming disorder and regional homogeneity in highly involved male adult gamers: A pilot resting-state fMRI study 期刊论文
BRAIN AND BEHAVIOR, 2023, 页码: 12
作者:  Jiang, Wen-tao;  Liu, Xia;  Xu, Zi-yun;  Zhou, Zhi-feng;  Tie, Chang-jun;  Liu, Xiao-ying;  Yang, Ji-hui;  Li, Hai;  Lai, Wen-tao
收藏  |  浏览/下载:13/0  |  提交时间:2024/05/20
depression  gaming disorder  highly involved gamers  hippocampus  impulsivity  regional homogeneity  
Genomic and transcriptomic profiling indicates the prognosis significance of mutational signature for TMB-high subtype in Chinese patients with gastric cancer 期刊论文
JOURNAL OF ADVANCED RESEARCH, 2023, 卷号: 51, 页码: 121-134
作者:  Cheng, Yanan;  Bu, Dechao;  Zhang, Qiaoling;  Sun, Rebecca;  Lyle, Stephen;  Zhao, Gang;  Dong, Li;  Li, Hui;  Zhao, Yi;  Yu, Jinpu;  Hao, Xishan
收藏  |  浏览/下载:17/0  |  提交时间:2023/12/04
Gastric cancer  Comprehensive genomic profiling  TMB  Mutational signature  Tumor metabolism  
Parallel Software-Based Self-Testing with Bounded Model Checking for Kilo-Core Networks-on-Chip 期刊论文
JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY, 2023, 卷号: 38, 期号: 2, 页码: 405-421
作者:  Zhang, Ying;  Ji, Peng-Fei;  Zhu, Pan-Wei;  Peng, Zebo;  Li, Hua-Wei;  Jiang, Jian-Hui
收藏  |  浏览/下载:22/0  |  提交时间:2023/12/04
software-based self-testing (SBST)  parallel test  kilo-core networks-on-chip (NoCs)  online testing  
香山开源高性能RISC-V处理器设计与实现 期刊论文
计算机研究与发展, 2023, 卷号: 60, 期号: 3, 页码: 476
作者:  王凯帆;  徐易难;  余子濠;  唐丹;  陈国凯;  陈熙;  勾凌睿;  胡轩;  金越;  李乾若;  李昕;  蔺嘉炜;  刘彤;  刘志刚;  王华强;  王诲喆;  张传奇;  张发旺;  张林隽;  张紫飞;  张梓悦;  赵阳洋;  周耀阳;  邹江瑞;  蔡晔;  郇丹丹;  李祖松;  赵继业;  何伟;  孙凝晖;  包云岗
收藏  |  浏览/下载:15/0  |  提交时间:2024/05/20
RISC-V  high performance processor  open source  chip design  agile development  RISC-V  高性能处理器  开源  芯片设计  敏捷开发  
社交知识图谱研究综述 期刊论文
计算机学报, 2023, 卷号: 46, 期号: 2, 页码: 304
作者:  江旭晖;  沈英汉;  李子健;  王元卓;  尹芷仪;  沈华伟
收藏  |  浏览/下载:10/0  |  提交时间:2024/05/20
social knowledge graph  social network  knowledge graph  knowledge reasoning  graph representation learning  knowledge extraction  graph integration  社交知识图谱  社交网络  知识图谱  知识推理  图表示学习  知识抽取  网络融合  
GIPS-Mix for Accurate Identification of Isomeric Components in Glycan Mixtures Using Intelligent Group-Opting Strategy 期刊论文
ANALYTICAL CHEMISTRY, 2022, 页码: 9
作者:  Huang, Chuncui;  Hou, Meijie;  Yan, Jingyu;  Wang, Hui;  Wang, Yu;  Cao, Cuiyan;  Wang, Yaojun;  Gao, Huanyu;  Ma, Xinyue;  Zheng, Yi;  Bu, Dongbo;  Chai, Wengang;  Li, Yan;  Sun, Shiwei
收藏  |  浏览/下载:23/0  |  提交时间:2023/07/12
Deep images enhancement for turbid underwater images based on unsupervised learning 期刊论文
COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2022, 卷号: 202, 页码: 10
作者:  Zhou, Wen-Hui;  Zhu, Deng-Ming;  Shi, Min;  Li, Zhao-Xin;  Duan, Ming;  Wang, Zhao-Qi;  Zhao, Guo-Liang;  Zheng, Cheng-Dong
收藏  |  浏览/下载:20/0  |  提交时间:2023/07/12
Image enhancement  Visual perception  Underwater dataset  Deep learning