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Under certain circumstances the sparsity pattern will be destroyed and adding/setting values would then result in an expensive reallocation. Assume that in the first global iteration only one half of the values is set to non-zero. Before the linear solver is called the sparse matrix is compressed thus reducing the allocated space in each row. In the subsequent iterations, which might add or set the other half of the matrix values reallocations would be necessary.
Under certain circumstances the sparsity pattern will be destroyed and adding/setting values would then result in an expensive reallocation. Assume that in the first global iteration only one half of the values is set to non-zero. Before the linear solver is called the sparse matrix is compressed thus reducing the allocated space in each row. In the subsequent iterations, which might add or set the other half of the matrix values reallocations would be necessary.
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