The effect of ordering on preconditioned conjugate gradients

We investigate the effect of the ordering of the unknowns on the convergence of the preconditioned conjugate gradient method. We examine a wide range of ordering methods including nested dissection, minimum degree, and red-black and consider preconditionings without fill-in. We show empirically that there can be a significant difference in the number of iterations required by the conjugate gradient method and suggest reasons for this marked difference in performance.We also consider the effect of orderings when an incomplete factorization which allows some fill-in is performed. We consider the effect of automatically controlling the sparsity of the incomplete factorization through drop tolerances and level of fill-in.

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