A major part of the computational burden in FEA is the solution of the assembled system of equations. Such problems cannot be solved on serial computers because of excessive computation time and memory requirements. Implementation on parallel processors is indispensable because of time requirements.
Iterative methods are indispensable because of memory requirements.
This research addresses that problem. Multi-p methods can be used independently as smoothers, or as preconditioners for other iterations such as conjugate gradient. The term multi-p processes includes both approaches. This research develops multi-p V cycle methods with particular emphasis on problems in 3D. Parallelization with respect to both computation costs, costs of communication among processors, and costs of using auxiliary memory are considered. The use of multi-p algorithms as preconditioners, . . .