In this article, we review some of the classical methods used for quickly obtaining low-precision approximations to the elementary functions. Then, for each of the three main classes of elementary function algorithms (shift-and-add algorithms, polynomial or rational approximations, and table-based methods) and for the additional, specific to approximate computing, “bit-manipulation” techniques, we examine what can be done for obtaining very fast estimates of a function, at the cost of a (controlled) loss in terms of accuracy.
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Jean‐Michel Muller (2020) studied this question.
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