中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
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CAS IR Grid
机构
地质与地球物理研究所 [1]
计算技术研究所 [1]
长春光学精密机械与物... [1]
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OAI收割 [3]
内容类型
期刊论文 [2]
会议论文 [1]
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2020 [1]
2016 [1]
2010 [1]
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An efficient hybrid model for thermal analysis of deep borehole heat exchangers
期刊论文
OAI收割
GEOTHERMAL ENERGY, 2020, 卷号: 8, 期号: 1, 页码: 31
作者:
Zhao, Yazhou
;
Pang, Zhonghe
;
Huang, Yonghui
;
Ma, Zhibo
  |  
收藏
  |  
浏览/下载:47/0
  |  
提交时间:2020/07/07
Deep borehole heat exchanger
Efficient modeling
Analytical formulation
Heat propagation front
Accuracy and calculation acceleration
Efficient level of detail for texture-based flow visualization
期刊论文
OAI收割
COMPUTER ANIMATION AND VIRTUAL WORLDS, 2016, 卷号: 27, 期号: 2, 页码: 123-140
作者:
Lu, Daying
;
Zhu, Dengming
;
Wang, Zhaoqi
;
Gao, Jinzhu
  |  
收藏
  |  
浏览/下载:25/0
  |  
提交时间:2019/12/13
level of detail
texture-based visualization
noise optimization
efficient acceleration
smooth animation
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.