GPU-ACCELERATED FEM SOLVER FOR THREE DIMENSIONAL ELECTROMAGNETIC ANALYSIS  

作　　者：Tian Jin Gong Li Shi Xiaowei Le Xu 

机构地区：[1]National Key Laboratory of Science and Technology on Antennas and Microwaves, Xidian University, Xi＇ an 710071, China [2]Institute of China Innovation, East China Normal University, Shanghai 200062, China

出　　处：《Journal of Electronics(China)》2011年第4期615-622,共8页电子科学学刊（英文版）

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

摘　　要：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,espe-cially 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 signi?cant speedups compared to Compressed Sparse Row(CSR) format.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,espe-cially 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 signi？cant speedups compared to Compressed Sparse Row（CSR） format.

关 键 词：Finite Element Method(FEM) Graphics Processing Unit(GPU) Parallelization strategy Conjugate Gradient Norm(CGN) Sliced ELL Four(sliced ELL-F) 

分 类 号：TN011[电子电信—物理电子学]