Abstract
Although many data-parallel functional languages exist, *Lisp [22], NESL have investigated incorporating data-parallelism with a lazy language. This paper describes data-parallel extensions which have been incorporated into the lazy functional lan guage Haskell. We describe PODS, parallel data structures that share many of the characteristics of Haskell arrays-their distinguishing feature however is they are unbounded. We present POD comprehensions . a framework within which communication and parallel operations on PODs can be expressed. The semant ics of these extensions is given in terms of translation rules into a core set of primitive parallel operations. Particular attention is given to th e non-strict nature of these extensions. Development of the higher order parallel map, fold, and scan is presented , a trio of functions that is widely accepted as being fundamental to a data-parallel paradigm [21]. Ladner [12] classifies a problem as being susceptible to parallel scanning if it is of a fixed size and can be solved by a finit e state transducer. We show that by utilising lazy evaluation, Ladner ’s requirements can be relaxed such that t he lazy version of scan presented here has the potential to scan an infinite POD.
This work has been supported through a SERC case award in association with Cambridge Parallel Processing.
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© 1994 British Computer Society
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Hill, J.M.D. (1994). The aim is laziness in a data-parallel language. In: O’Donnell, J.T., Hammond, K. (eds) Functional Programming, Glasgow 1993. Workshops in Computing. Springer, London. https://doi.org/10.1007/978-1-4471-3236-3_7
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