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GPU-accelerated fem solver for three dimensional electromagnetic analysis

  • Published:
Journal of Electronics (China)

Abstract

A new Graphics Processing Unit (GPU) parallelization strategy is proposed to accelerate sparse finite element computation for three dimensional electromagnetic analysis. The parallelization strategy is employed based on a new compression format called sliced ELL Four (sliced ELL-F). The sliced ELL-F format-based parallelization strategy is designed for hastening many addition, dot product, and Sparse Matrix Vector Product (SMVP) operations in the Conjugate Gradient Norm (CGN) calculation of finite element equations. The new implementation of SMVP on GPUs is evaluated. The proposed strategy executed on a GPU can efficiently solve sparse finite element equations, especially when the equations are huge sparse (size of most rows in a coefficient matrix is less than 8). Numerical results show the sliced ELL-F format-based parallelization strategy can reach significant speedups compared to Compressed Sparse Row (CSR) format.

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Authors and Affiliations

  1. National Key Laboratory of Science and Technology on Antennas and Microwaves, Xidian University, Xi’an, 710071, China

    Jin Tian, Xiaowei Shi & Xu Le

  2. Institute of China Innovation, East China Normal University, Shanghai, 200062, China

    Li Gong

  3. Rm. 501, No. 55, Ln. 650, Zhongjiang Rd., Putuo Dist., Shanghai, 200062, China

    Jin Tian

Authors
  1. Jin Tian
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  2. Li Gong
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  3. Xiaowei Shi
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  4. Xu Le
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Corresponding author

Correspondence to Jin Tian.

Additional information

Supported by the National Natural Science Foundation of China (No. 60801039).

Communication author: Tian Jin, born in 1982, female, Ph.D. candidate.

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Tian, J., Gong, L., Shi, X. et al. GPU-accelerated fem solver for three dimensional electromagnetic analysis. J. Electron.(China) 28, 615–622 (2011). https://doi.org/10.1007/s11767-012-0766-2

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  • DOI: https://doi.org/10.1007/s11767-012-0766-2

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