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Novel 3D GPU based numerical parallel diffusion algorithms in cylindrical coordinates for health care simulation

Author

Listed:
  • Jiang, Beini
  • Dai, Weizhong
  • Khaliq, Abdul
  • Carey, Michelle
  • Zhou, Xiaobo
  • Zhang, Le

Abstract

Modeling diffusion processes, such as drug deliver, bio-heat transfer, and the concentration change of cytokine for computational biology research, requires intensive computing resources as one must employ sequential numerical algorithms to obtain accurate numerical solutions, especially for real-time in vivo 3D simulation. Thus, it is necessary to develop a new numerical algorithm compatible with state-of-the-art computing hardware. The purpose of this article is to integrate the graphics processing unit (GPU) technology with the locally-one-dimension (LOD) numerical method for solving partial differential equations, and to develop a novel 3D numerical parallel diffusion algorithm (GNPD) in cylindrical coordinates based on GPU technology, which can be used in the neuromuscular junction research.

Suggested Citation

  • Jiang, Beini & Dai, Weizhong & Khaliq, Abdul & Carey, Michelle & Zhou, Xiaobo & Zhang, Le, 2015. "Novel 3D GPU based numerical parallel diffusion algorithms in cylindrical coordinates for health care simulation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 109(C), pages 1-19.
    • Handle: RePEc:eee:matcom:v:109:y:2015:i:c:p:1-19
    DOI: 10.1016/j.matcom.2014.07.003
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    Cited by:

    1. Le Zhang & Chunqiu Zheng & Tian Li & Lei Xing & Han Zeng & Tingting Li & Huan Yang & Jia Cao & Badong Chen & Ziyuan Zhou, 2017. "Building Up a Robust Risk Mathematical Platform to Predict Colorectal Cancer," Complexity, Hindawi, vol. 2017, pages 1-14, October.
    2. Klimeš, Lubomír & Mauder, Tomáš & Charvát, Pavel & Štětina, Josef, 2018. "Front tracking in modelling of latent heat thermal energy storage: Assessment of accuracy and efficiency, benchmarking and GPU-based acceleration," Energy, Elsevier, vol. 155(C), pages 297-311.

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