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Calculating Parallel Programs in Coq Using List Homomorphisms.

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Title: Calculating Parallel Programs in Coq Using List Homomorphisms.
Authors: Loulergue, Frédéric frederic.loulergue@univ-orleans.fr, Bousdira, Wadoud1 wadoud.bousdira@univ-orleans.fr, Tesson, Julien2 Julien.Tesson@lacl.fr
Source: International Journal of Parallel Programming. Apr2017, Vol. 45 Issue 2, p300-319. 20p.
Subjects: Parallel programs (Computer programs), Parallel computers, Parallel programming, Programming languages, Computer software
Abstract: SyDPaCC is a set of libraries for the Coq proof assistant. It allows to write naive functional programs (i.e. with high complexity) that are considered as specifications, and to transform them into more efficient versions. These more efficient versions can then be automatically parallelised before being extracted from Coq into source code for the functional language OCaml together with calls to the Bulk Synchronous Parallel ML library. In this paper we present a new core version of SyDPaCC for the development of parallel programs correct-by-construction using the theory of list homomorphisms and algorithmic skeletons implemented and verified in Coq. The framework is illustrated on the maximum prefix sum problem. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Parallel Programming is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Calculating Parallel Programs in Coq Using List Homomorphisms.
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  Data: <searchLink fieldCode="AR" term="%22Loulergue%2C+Frédéric%22">Loulergue, Frédéric</searchLink><i> frederic.loulergue@univ-orleans.fr</i><br /><searchLink fieldCode="AR" term="%22Bousdira%2C+Wadoud%22">Bousdira, Wadoud</searchLink><relatesTo>1</relatesTo><i> wadoud.bousdira@univ-orleans.fr</i><br /><searchLink fieldCode="AR" term="%22Tesson%2C+Julien%22">Tesson, Julien</searchLink><relatesTo>2</relatesTo><i> Julien.Tesson@lacl.fr</i>
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Parallel+Programming%22">International Journal of Parallel Programming</searchLink>. Apr2017, Vol. 45 Issue 2, p300-319. 20p.
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  Data: <searchLink fieldCode="DE" term="%22Parallel+programs+%28Computer+programs%29%22">Parallel programs (Computer programs)</searchLink><br /><searchLink fieldCode="DE" term="%22Parallel+computers%22">Parallel computers</searchLink><br /><searchLink fieldCode="DE" term="%22Parallel+programming%22">Parallel programming</searchLink><br /><searchLink fieldCode="DE" term="%22Programming+languages%22">Programming languages</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+software%22">Computer software</searchLink>
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  Data: SyDPaCC is a set of libraries for the Coq proof assistant. It allows to write naive functional programs (i.e. with high complexity) that are considered as specifications, and to transform them into more efficient versions. These more efficient versions can then be automatically parallelised before being extracted from Coq into source code for the functional language OCaml together with calls to the Bulk Synchronous Parallel ML library. In this paper we present a new core version of SyDPaCC for the development of parallel programs correct-by-construction using the theory of list homomorphisms and algorithmic skeletons implemented and verified in Coq. The framework is illustrated on the maximum prefix sum problem. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of International Journal of Parallel Programming is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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