The aim is laziness in a data-parallel language

Hill, Jonathan M. D.

doi:10.1007/978-1-4471-3236-3_7

Cited by 2 publications

(3 citation statements)

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“…Unlike our earlier work, we use the BMF as is-all the operations presented here can be interpreted as though they were being expressed on lists. This stance contradicts an earlier paper (Hill, 1993a) in which we said that lists were unsuitable for data-parallel evaluation in a non-strict language. We still believe this to be true, but we have tried to sugar the pill somewhat.…”

Section: Introductioncontrasting

confidence: 57%

“…As we have already mentioned, a parallel fold has O(log N ) time complexity, if the function being folded is O(1) and associative. Whenever and the initial state of the for-loop form a monoid ( and x form a monoid if is associative and has x as its left and right identity), then by the first duality theorem (Bird and Wadler, 1988) the fold-left can be safely transformed into a fold-right, or more interestingly a parallel O(log N ) fold (Hill, 1993a).…”

Section: Parallelizing Simple Loopsmentioning

confidence: 99%

“…We still believe this to be true, but we have tried to sugar the pill somewhat. By using a purely combinator approach to programming, it is possible to give the impression of using lists, whilst actually implementing these list-like objects on top of more suitable data-parallel data structures (Hill, 1993a(Hill, , b, 1994 …”

Section: Introductionmentioning

confidence: 99%

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Parallelizing Imperative Functional Programs: the Vectorization Monad

Hill

Clarke

Bornat

1996

Journal of Symbolic Computation

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Traditionally a vectorizing compiler matches the iterative constructs of a program against a set of predefined templates. If a loop contains no dependency cycles then a map template can be used; other simple dependencies can often be expressed in terms of fold or scan templates. This paper addresses the template matching problem within the context of functional programming. A small collection of program identities are used to specify vectorizable for-loops. By incorporating these program identities within a monad, all well-typed for-loops in which the body of the loop is expressed using the vectorization monad can be vectorized. This technique enables the elimination of template matching from a vectorizing compiler, and the proof of the safety of vectorization can be performed by a type inference mechanism.

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Section: Introductioncontrasting

confidence: 57%

Section: Parallelizing Simple Loopsmentioning

confidence: 99%