11606

Efficient Preconditioned Conjugate Gradient Parallelization on GPU

A. F. P. Camargos, V. C. Silva
Universidade de Sao Paulo – Escola Politecnica, Sao Paulo, Brasil
19th International Conference on the Computation of Electromagnetic Fields (Compumag), 2013
@article{camargos2013efficient,

   title={Efficient Preconditioned Conjugate Gradient Parallelization on GPU},

   author={Camargos, AFP and Silva, VC},

   year={2013}

}

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We present a performance analysis of a parallel implementation of both conjugate gradient and preconditioned conjugate gradient solvers using graphic processing units with CUDA parallel programming model. The solvers were optimized for a fast solution of sparse systems of equations arising from Finite Element Analysis (FEA) of electromagnetic phenomena. The preconditioners were Incomplete Cholesky factorization and Incomplete LU factorization. Results show that the speedup factor for the incomplete Cholesky decomposition was above 3 compared to the CPU implementation.
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