pages={3596--3604},
year={2018}
}
+
+@TechReport{Saad1991,
+ Title = {{A {F}lexible {I}nner-{O}uter {P}reconditioned {GMRES} {A}lgorithm}},
+ Author = {Y. Saad},
+ Institution = {Minnesota Supercomputer Institute},
+ Year = {1991},
+ Address = {University of Minnesota},
+ Number = {91-279},
+ Url = {citeseer.ist.psu.edu/saad93flexible.html}
+}
/**
* Implementation of the Generalized minimal residual method with flexible
- * preconditioning method.
+ * preconditioning (flexible GMRES or FGMRES).
*
- * This version of the GMRES method allows for the use of a different
+ * This flexible version of the GMRES method allows for the use of a different
* preconditioner in each iteration step. Therefore, it is also more robust
* with respect to inaccurate evaluation of the preconditioner. An important
- * application is also the use of a Krylov space method inside the
+ * application is the use of a Krylov space method inside the
* preconditioner. As opposed to SolverGMRES which allows one to choose
* between left and right preconditioning, this solver always applies the
* preconditioner from the right.
*
* FGMRES needs two vectors in each iteration steps yielding a total of
* <tt>2*SolverFGMRES::AdditionalData::max_basis_size+1</tt> auxiliary
- * vectors.
+ * vectors. Otherwise, FGMRES requires roughly the same number of operations
+ * per iteration compared to GMRES, except one application of the
+ * preconditioner less at each restart and at the end of solve().
+ *
+ * For more details see @cite Saad1991.
*
* @author Guido Kanschat, 2003
*/