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Conference Paper/Proceeding/Abstract 119 views 4 downloads

An Application of Answer Set Programming: Superoptimisation -- A Preliminary Report / Tom, Crick

Proceedings of the 11th International Workshop on Non-Monotonic Reasoning, Issue: IFL-06-04, Pages: 258 - 265

Swansea University Author: Tom, Crick

Abstract

Answer set programming (ASP) is a declarative problem-solving technique that uses the computation of answer set semantics to provide solutions. Despite comprehensive implementations and a strong theoretical basis, ASP has yet to be used for more than a handful of large-scale applications. This paper...

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Published in: Proceedings of the 11th International Workshop on Non-Monotonic Reasoning
ISSN: 1860-8477
Published: Lake District, UK Technische Universität Clausthal 2006
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URI: https://cronfa.swan.ac.uk/Record/cronfa43778
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spelling 2018-10-15T15:01:29.9137120 v2 43778 2018-09-12 An Application of Answer Set Programming: Superoptimisation -- A Preliminary Report 200c66ef0fc55391f736f6e926fb4b99 0000-0001-5196-9389 Tom Crick Tom Crick true false 2018-09-12 EDUC Answer set programming (ASP) is a declarative problem-solving technique that uses the computation of answer set semantics to provide solutions. Despite comprehensive implementations and a strong theoretical basis, ASP has yet to be used for more than a handful of large-scale applications. This paper describes such a large-scale application and presents some preliminary results. The TOAST (Total Optimisation using Answer Set Technology) project seeks to generate optimal machine code for simple, acyclic functions using a technique known as superoptimisation. ASP is used as a scalable computational engine for conducting searches over complex, non-regular do- mains. The experimental results suggest this is a viable approach to the optimisation problem and demonstrates the value of using parallel answer set solvers. Conference Paper/Proceeding/Abstract Proceedings of the 11th International Workshop on Non-Monotonic Reasoning IFL-06-04 258 265 Technische Universität Clausthal Lake District, UK 1860-8477 30 5 2006 2006-05-30 11th International Workshop on Non-Monotonic Reasoning (NMR 2006) COLLEGE NANME School of Education COLLEGE CODE EDUC Swansea University 2018-10-15T15:01:29.9137120 2018-09-12T08:16:54.6274125 College of Arts and Humanities College of Arts and Humanities Martin Brain 1 Tom Crick 0000-0001-5196-9389 2 Marina De Vos 3 John Fitch 4 0043778-12092018081829.pdf NMR-camera-ready.pdf 2018-09-12T08:18:29.2900000 Output 91607 application/pdf Accepted Manuscript true 2018-09-12T00:00:00.0000000 true eng
title An Application of Answer Set Programming: Superoptimisation -- A Preliminary Report
spellingShingle An Application of Answer Set Programming: Superoptimisation -- A Preliminary Report
Tom, Crick
title_short An Application of Answer Set Programming: Superoptimisation -- A Preliminary Report
title_full An Application of Answer Set Programming: Superoptimisation -- A Preliminary Report
title_fullStr An Application of Answer Set Programming: Superoptimisation -- A Preliminary Report
title_full_unstemmed An Application of Answer Set Programming: Superoptimisation -- A Preliminary Report
title_sort An Application of Answer Set Programming: Superoptimisation -- A Preliminary Report
author_id_str_mv 200c66ef0fc55391f736f6e926fb4b99
author_id_fullname_str_mv 200c66ef0fc55391f736f6e926fb4b99_***_Tom, Crick
author Tom, Crick
format Conference Paper/Proceeding/Abstract
container_title Proceedings of the 11th International Workshop on Non-Monotonic Reasoning
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publishDate 2006
institution Swansea University
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publisher Technische Universität Clausthal
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description Answer set programming (ASP) is a declarative problem-solving technique that uses the computation of answer set semantics to provide solutions. Despite comprehensive implementations and a strong theoretical basis, ASP has yet to be used for more than a handful of large-scale applications. This paper describes such a large-scale application and presents some preliminary results. The TOAST (Total Optimisation using Answer Set Technology) project seeks to generate optimal machine code for simple, acyclic functions using a technique known as superoptimisation. ASP is used as a scalable computational engine for conducting searches over complex, non-regular do- mains. The experimental results suggest this is a viable approach to the optimisation problem and demonstrates the value of using parallel answer set solvers.
published_date 2006-05-30T13:58:27Z
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