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 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.展开更多
基金Supported by the National Natural Science Foundation of China (No. 60801039)
文摘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.
