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
相关论文
共 50 条
  • [41] A GPU-accelerated image reduction pipeline
    Niwano, Masafumi
    Murata, Katsuhiro L.
    Adachi, Ryo
    Wang, Sili
    Tachibana, Yutaro
    Yatsu, Yoichi
    Kawai, Nobuyuki
    Shimokawabe, Takashi
    Itoh, Ryosuke
    PUBLICATIONS OF THE ASTRONOMICAL SOCIETY OF JAPAN, 2021, 73 (01) : 14 - 24
  • [42] A GPU-accelerated viewer for HEALPix maps
    Frolov, A., V
    ASTRONOMY AND COMPUTING, 2023, 45
  • [43] Porting WarpX to GPU-accelerated platforms
    Myers, A.
    Almgren, A.
    Amorim, L. D.
    Bell, J.
    Fedeli, L.
    Ge, L.
    Gott, K.
    Grote, D. P.
    Hogan, M.
    Huebl, A.
    Jambunathan, R.
    Lehe, R.
    Ng, C.
    Rowan, M.
    Shapoval, O.
    Thevenet, M.
    Vay, J-L
    Vincenti, H.
    Yang, E.
    Zaim, N.
    Zhang, W.
    Zhao, Y.
    Zoni, E.
    PARALLEL COMPUTING, 2021, 108
  • [44] Practical considerations for GPU-accelerated CT
    Mueller, Klaus
    Xu, Fang
    2006 3RD IEEE INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING: MACRO TO NANO, VOLS 1-3, 2006, : 1184 - +
  • [45] GPU-accelerated transportation simplex algorithm
    Mahajan, Mohit
    Nagi, Rakesh
    Journal of Parallel and Distributed Computing, 2024, 184
  • [46] GPU-accelerated transportation simplex algorithm
    Mahajan, Mohit
    Nagi, Rakesh
    JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING, 2024, 184
  • [47] GAMER: GPU-Accelerated Maze Routing
    Lin, Shiju
    Liu, Jinwei
    Young, Evangeline F. Y.
    Wong, Martin D. F.
    IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS, 2023, 42 (02) : 583 - 593
  • [48] GPU-accelerated adjoint algorithmic differentiation
    Gremse, Felix
    Hoefter, Andreas
    Razik, Lukas
    Kiessling, Fabian
    Naumann, Uwe
    COMPUTER PHYSICS COMMUNICATIONS, 2016, 200 : 300 - 311
  • [49] GPU-accelerated DEM implementation with CUDA
    Qi, Ji
    Li, Kuan-Ching
    Jiang, Hai
    Zhou, Qingguo
    Yang, Lei
    INTERNATIONAL JOURNAL OF COMPUTATIONAL SCIENCE AND ENGINEERING, 2015, 11 (03) : 330 - 337
  • [50] Benchmarking GPU-Accelerated Edge Devices
    Jo, Jongmin
    Jeong, Sucheol
    Kang, Pilsung
    2020 IEEE INTERNATIONAL CONFERENCE ON BIG DATA AND SMART COMPUTING (BIGCOMP 2020), 2020, : 117 - 120