GPU-accelerated visualisation of ADS granular flow target model

被引:0
|
作者
Tian, Yan-Shan [1 ,2 ]
Zhou, Qingguo [1 ]
Sun, Hong-Yu [1 ]
Wu, Jiong [1 ]
Zhang, Xun-Chao [3 ]
Li, Kuan-Ching [4 ]
机构
[1] School of Information Science and Technology, Lanzhou University, Lanzhou, China
[2] School of Mathematics and Computer Science, Ningxia Normal University, Guyuan, Ningxia, China
[3] Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou, Gansu,730000, China
[4] Department of Computer Science and Information Engineering, Providence University, Taiwan
关键词
Edge detection - Finite difference method - Application programming interfaces (API) - Computer graphics - Program processors - Granular materials - Parallel architectures - Computer graphics equipment - Particles (particulate matter) - Visualization;
D O I
10.1504/IJHPCN.2015.072824
中图分类号
学科分类号
摘要
This paper presents a discrete element method to handle particle collision detection and responses in transport simulation (the simulation of transport of protons and neutrons in granular flow target geometric model) based on GPUs. Discrete element method was adopted in the realisation of large-scale particle visualisation. The method simulates and solves edge detection, position judging, motion direction, calculation of the next collision point using GPU acceleration during the process of transport, and demonstrates the complete interaction process through OpenGL. Results show that the model presented exploits the acceleration of GPUs and has gained remarkable functional improvement compared with traditional method using solely CPUs. In addition, we used the MCNPX to calculate this model with high-speed proton bombardment. The distribution of power energies verifies that the granular flow target model is reliable and feasible. © 2015 Inderscience Enterprises Ltd.
引用
收藏
页码:381 / 389
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