Abstract

. Great hopes in the exploitation of the (implicit) parallelism inherent in functional programs have driven a number of projects. General frustration resulted wherever implementations on distributed memory machines were attempted. The grain size of potentially parallel tasks is too small to amortize the enormous costs of the necessary communication. The management of the parallelism is expensive. Decision making in the network operating system suffers from the fact, that most parameters such as the number of potentially parallel tasks and their execution times are dynamic. This article tries to summarise the state of the art in the parallel implementation of functional languages, to give reasons why attempts have failed to show performance, and argues why this will probably remain so. Similar arguments will hold for other declarative languages and mechanisms with implicit fine grain parallelism such as logic and constraint languages. 1 Introduction Parallel architectures are a big pro...

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