Examples of Fuzziness in Compilers and Runtime Systems

In this paper, I review some techniques used in compilers and runtime systems for parallel and distributed computation, involving aspects of fuzziness. Fuzziness is in a general sense considered as being present if the techniques applied classify, rate or otherwise handle information with some range of tolerance, if they operate with similarities, uncertainties, or do not seek for perfect/optimal solutions (but apply heuristics or approximations). In many cases, fuzziness, in this sense, is already used but may need a better theoretical basis; and in others, its integration may improve approaches, opens up new perspectives or become relevant for future applications, as in distributed computing. In this paper, I focus on the potential application of fuzzy theory, providing a simplified – but in many cases sufficiently accurate – approach on sound theoretical principles. Other important theoretical approaches – as far as they are applied in compilers for dealing with approximateness – are the determination of bounds guaranteeing minimal quality or maximal runtime, or statistics providing means and variances. As a spin-off, so to speak, the paper investigates – from the point of the user – the various forms and benefits of fuzziness, concluding with a brief philosophical discussion of fuzziness.