Iterative Solution on GPU of Linear Systems Arising from the A-V Edge-FEA of Time-Harmonic Electromagnetic Phenomena

We present a performance analysis of a parallel implementation to both preconditioned Conjugate Gradient and preconditioned Bi-conjugate Gradient solvers using graphic processing units with CUDA programming model. The solvers were optimized for the solution of sparse systems of equations arising from Finite Element Analysis of electromagnetic phenomena involved in the diffusion of underground currents under time-harmonic current excitation. We used a shifted Incomplete Cholesky factorization as preconditioner. Results show a significant speedup by using the GPU compared to a serial CPU implementation.