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https://doi.org/10.1007/3-540-...
Part of book or chapter of book . 1991 . Peer-reviewed
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Data parallelism in logic programming

Authors: Succi G; Marino G;

Data parallelism in logic programming

Abstract

Many researchers have been trying to use the implicit parallelism of logic languages parallelizing the execution of independent clauses. However this approach has the disadvantage of requiring a heavy overhead for processes scheduling and synchronizing, for data migration and for collecting the results. In this paper it is proposed a different approach, the data parallel one. The focus is on large collections of data and the core idea is to parallelize the execution of element-wise operations. The target language is SEL, a Subset Equational Language. An abstract machine for it, the SAM (Subset Abstract Machine), is outlined, which, under certain points of views, belongs to the WAM family. The data parallel structure of the SAM is here explained and some examples of how it works are given. Eventually it is explained the role of abstract analyzers in this framework and it is presented the plan for the future research.

Keywords

Logic Programming; Data parallelism

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
3
Average
Average
Average
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