Abstract
The scalability of a parallel system is a measure of its capacity to effectively use an increasing number of processors. Several performance evaluation metrics have been developed to study the scalability of parallel algorithms and architectures. The isoefficiency function is one of those metrics. It relates the size of the problem being solved to the number of processors required to maintain efficiency at a fixed value. This work studies the scalability of Neville elimination, which is a method to solve a linear equation system. This process appears naturally when the Neville strategy of interpolation is used to solve linear systems. The scalability behavior of some algorithms of this method is studied on an IBM SP2 and also over a network of personal computers using the isoefficiency function and the scaled efficiency.
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