机构

• 计算技术研究所 [2]
• 高能物理研究所 [2]
• 合肥物质科学研究院 [2]
• 力学研究所 [1]
• 物理研究所 [1]
• 长春光学精密机械与物... [1]
• 更多

采集方式

• OAI收割 [10]
• iSwitch采集 [1]

内容类型

• 期刊论文 [9]
• 会议论文 [2]

发表日期

• 2023 [2]
• 2022 [2]
• 2020 [2]
• 2017 [2]
• 2012 [1]
• 2010 [1]
• 更多

学科主题

• Engineerin... [1]
• Engineerin... [1]

筛选

浏览/检索结果: 共11条，第1-10条 帮助 条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择题名升序题名降序提交时间升序提交时间降序作者升序作者降序发表日期升序发表日期降序 Optimizing Training Efficiency and Cost of Hierarchical Federated Learning in Heterogeneous Mobile-Edge Cloud Computing 期刊论文  OAI收割 IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS, 2023, 卷号: 42, 期号: 5, 页码: 1518-1531 作者:  Cui, Yangguang;  Cao, Kun;  Zhou, Junlong;  Wei, Tongquan   |  收藏  |  浏览/下载：16/0  |  提交时间：2023/12/04 Training  Servers  Cloud computing  Delays  Costs  Computational modeling  Prototypes  Device frequency determination  federated learning (FL)  high efficiency  low cost  mobile-edge cloud computing (MECC)  user selection   基于张量虚拟机的深度神经网络模型加速方法 期刊论文  OAI收割 计算机应用, 2023, 卷号: 43 作者:  申云飞;  申飞;  李芳;  张俊   |  收藏  |  浏览/下载：8/0  |  提交时间：2024/11/20 Tensor Virtual Machine (TVM)  Deep Neural Network (DNN)  Field-Programmable Gate Array (FPGA)  edge device  model deployment  model acceleration  张量虚拟机  深度神经网络  现场可编程门阵列  边缘设备  模型部署  模型加速   Simulation of plasma transport in MPS-LD linear plasma device by using BOUT plus 期刊论文  OAI收割 PLASMA PHYSICS AND CONTROLLED FUSION, 2022, 卷号: 64 作者:  Wang, Yue;  Sang, Chaofeng;  Li, Nami;  Huang, Yao;  Zhang, Yanjie   |  收藏  |  浏览/下载：39/0  |  提交时间：2022/12/22 linear plasma device  plasma transport  BOUT plus  edge plasma   Effect of the trailing-edge flap on tones due to self-excited oscillation within the leading-edge slat cove 期刊论文  OAI收割 PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART G-JOURNAL OF AEROSPACE ENGINEERING, 2022 作者:  Lu WS(陆维爽);  Liu, Peiqing;  Guo, Hao   |  收藏  |  浏览/下载：31/0  |  提交时间：2022/10/23 high-lift device  leading-edge slat  aerodynamic noise  acoustic characteristics  trailing-edge flap   A deep neural network compression algorithm based on knowledge transfer for edge devices 期刊论文  OAI收割 COMPUTER COMMUNICATIONS, 2020, 卷号: 163, 页码: 186-194 作者:  Chen, Yanming;  Li, Chao;  Gong, Luqi;  Wen, Xiang;  Zhang, Yiwen   |  收藏  |  浏览/下载：74/0  |  提交时间：2020/12/10 Edge device  Deep learning  Neural network compression  Knowledge transfer   Efficient and Accurate Classification Enabled by a Lightweight CNN 会议论文  OAI收割 ELECTR NETWORK, MAY 15-18, 2020 作者:  Miao, Weiwei;  Zeng, Zeng;  Wang, Chuanjun   |  收藏  |  浏览/下载：36/0  |  提交时间：2021/02/27 edge device  lightweight convolutional neural network(L-CNN)  fault diagnosis   Modulation depth of series squids modified by josephson junction area 期刊论文  iSwitch采集 Chinese physics b, 2017, 卷号: 26, 期号: 9, 页码: 6 作者:  Liu, Jie;  Gao, He;  Li, Gang;  Li, Zheng Wei;  Ahmada, Kamal 收藏  |  浏览/下载：57/0  |  提交时间：2019/04/23 Superconducting quantum interference device (squid)  Josephson junction  Transition edge sensor   Modulation depth of series SQUIDs modified by Josephson junction area 期刊论文  OAI收割 CHINESE PHYSICS B中国物理. B, 2017, 卷号: 26, 期号: 9, 页码: 98501 作者:  Ahmada, K;  Li, G;  Gao, H;  Gao H(高鹤);  Liu, J   |  收藏  |  浏览/下载：54/0  |  提交时间：2019/08/27 superconducting quantum interference device (SQUID)  Josephson junction  transition edge sensor   Mechanical properties of polymeric nanostructures fabricated through directed self-assembly of symmetric diblock and triblock copolymers 期刊论文  OAI收割 journal of vacuum science & technology b, 2012, 卷号: 30, 期号: 6, 页码: 文献号：06f204 Delcambre SP; Ji SX; Nealey PF 收藏  |  浏览/下载：13/0  |  提交时间：2013/10/09 FORMING BLOCK-COPOLYMERS  LINE EDGE ROUGHNESS  CHEMICALLY NANOPATTERNED SURFACES  DEVICE-ORIENTED STRUCTURES  THIN-FILMS  DENSITY MULTIPLICATION  EQUILIBRIUM BEHAVIOR  PATTERNED SURFACES  CAPILLARY FORCES  CYLINDER   Image parallel processing based on GPU (EI CONFERENCE) 会议论文  OAI收割 2010 IEEE International Conference on Advanced Computer Control, ICACC 2010, March 27, 2010 - March 29, 2010, 445 Hoes Lane - P.O.Box 1331, Piscataway, NJ 08855-1331, United States 作者:  Wang J.-L.;  Wang J.-L. 收藏  |  浏览/下载：31/0  |  提交时间：2013/03/25 In order to solve the compute-intensive character of image processing  based on advantages of GPU parallel operation  parallel acceleration processing technique is proposed for image. First  efficient architecture of GPU is introduced that improves computational efficiency  comparing with CPU. Then  Sobel edge detector and homomorphic filtering  two representative image processing algorithms  are embedded into GPU to validate the technique. Finally  tested image data of different resolutions are used on CPU and GPU hardware platform to compare computational efficiency of GPU and CPU. Experimental results indicate that if data transfer time  between host memory and device memory  is taken into account  speed of the two algorithms implemented on GPU can be improved approximately 25 times and 49 times as fast as CPU  respectively  and GPU is practical for image processing. 2010 IEEE.