Parallel processing strategies for solving differential equations and approximation problems
The n ed for effective parallel methods for solving problems in science and engineering well recognized. Not only do we require algorithms which map well onto practical parallel machines, we also need methods which have well understood convergence and stability properties. In this thesis we devise techniques and parallel algorithms for solving differential equations and for data approximation, the two fundamental building blocks in scientific and engineering computing.
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