Parallel Simulation Based on GPU-Acceleration

  • Jun Du
  • Qiang Liang
  • Yongchun Xia
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 324)


GPU has much intensive computation capacity and wide bandwidth, and with the advantage of high performance and low power cost, the heterogeneous architecture of CPU and GPU make good effect in many fields. With the appearance of CUDA that carried out by Nvidia, the GPU is used for general-purpose computation is easier and cheaper, there are many high performance computation questions in simulation field, such as the simulation of the electromagnetic environment, the solution of higher order differential equations, the simulation data processing, large-scale combat simulation and so on, among these, some of the questions that are involved data-intensive computation, are suitable for acceleration by GPU. With the development and maturity of GPGPU, the heterogeneous parallel computation will play an important role in parallel simulation.


paralle simulation GPU acceleration general-purpose computation heterogeneous paralleling 


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  1. 1.
    Nvidia. NVIDIA CUDA Compute Unified Device Architechture Programming Guide [OL] (2008)Google Scholar
  2. 2.
    Wu, E.-H.: The Technology Status and Challenge of GPGPU. Software Paper 15(10), 1493–1504 (2004)Google Scholar
  3. 3.
    Xiao, J.: Ability Test for Matrix-Multiplication and FFT Based on CUDA. Computer Engineering 35(10) (2009)Google Scholar
  4. 4.
    Zhang, Q.-D.: Research on String Matching Algorithms Based on GPU. Computer Application 26(7), 7 (2006)Google Scholar
  5. 5.
    Mao, H.-Q.: The Research on the 3D Real-time Rendering Optimized Base on GPU, p. 3. Wuhan University (2010)Google Scholar
  6. 6.
    Li, Y.: The Research of Real-time Infrared Image Generation Based on GPU. Xi’An University of Electronic Science & Technology (2007)Google Scholar
  7. 7.
    Yang, Z.-L.: Acceleration Algorithm of Electromagnetic calculation Based on GPU. Electronic Paper 35(6), 6 (2007)Google Scholar
  8. 8.
    Tan, C.-F.: Research on the Parallel Implementation of Genetic Algorithm on CUDA Platform. Computer Engineering & Science (2009)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Jun Du
    • 1
  • Qiang Liang
    • 1
  • Yongchun Xia
    • 1
  1. 1.Academy of Armored Force EngineeringBeijingChina

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