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Generating Optimal Code Using Answer Set Programming

Tom Crick Orcid Logo, Martin Brain, Marina De Vos, John Fitch

Logic Programming and Nonmonotonic Reasoning, Volume: 5753, Pages: 554 - 559

Swansea University Author: Tom Crick Orcid Logo

Abstract

This paper presents the Total Optimisation using Answer Set Technology (TOAST) system, which can be used to generate optimal code sequences for machine architectures via a technique known as superoptimisation. Answer set programming (ASP) is utilised as the modelling and computational framework for...

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Published in: Logic Programming and Nonmonotonic Reasoning
ISBN: 978-3-642-04237-9 978-3-642-04238-6
ISSN: 0302-9743 1611-3349
Published: Potsdam, Germany Springer 2009
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URI: https://cronfa.swan.ac.uk/Record/cronfa43399
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spelling 2022-12-18T17:48:34.2537400 v2 43399 2018-08-14 Generating Optimal Code Using Answer Set Programming 200c66ef0fc55391f736f6e926fb4b99 0000-0001-5196-9389 Tom Crick Tom Crick true false 2018-08-14 EDUC This paper presents the Total Optimisation using Answer Set Technology (TOAST) system, which can be used to generate optimal code sequences for machine architectures via a technique known as superoptimisation. Answer set programming (ASP) is utilised as the modelling and computational framework for searching over the large, complex search spaces and for proving the functional equivalence of two code sequences. Experimental results are given showing the progress made in solver performance over the previous few years, along with an outline of future developments to the system and applications within compiler toolchains. Book chapter Logic Programming and Nonmonotonic Reasoning 5753 554 559 Springer Potsdam, Germany 978-3-642-04237-9 978-3-642-04238-6 0302-9743 1611-3349 14 9 2009 2009-09-14 10.1007/978-3-642-04238-6_57 https://link.springer.com/chapter/10.1007%2F978-3-642-04238-6_57 10th International Conference on Logic Programming and Nonmonotonic Reasoning (LPNMR 2009) COLLEGE NANME Education COLLEGE CODE EDUC Swansea University 2022-12-18T17:48:34.2537400 2018-08-14T15:45:17.0980503 Faculty of Humanities and Social Sciences School of Social Sciences - Education and Childhood Studies Tom Crick 0000-0001-5196-9389 1 Martin Brain 2 Marina De Vos 3 John Fitch 4 0043399-12092018065450.pdf paper51_camera_ready.pdf 2018-09-12T06:54:50.9670000 Output 95693 application/pdf Accepted Manuscript true 2018-09-12T00:00:00.0000000 true eng
title Generating Optimal Code Using Answer Set Programming
spellingShingle Generating Optimal Code Using Answer Set Programming
Tom Crick
title_short Generating Optimal Code Using Answer Set Programming
title_full Generating Optimal Code Using Answer Set Programming
title_fullStr Generating Optimal Code Using Answer Set Programming
title_full_unstemmed Generating Optimal Code Using Answer Set Programming
title_sort Generating Optimal Code Using Answer Set Programming
author_id_str_mv 200c66ef0fc55391f736f6e926fb4b99
author_id_fullname_str_mv 200c66ef0fc55391f736f6e926fb4b99_***_Tom Crick
author Tom Crick
author2 Tom Crick
Martin Brain
Marina De Vos
John Fitch
format Book chapter
container_title Logic Programming and Nonmonotonic Reasoning
container_volume 5753
container_start_page 554
publishDate 2009
institution Swansea University
isbn 978-3-642-04237-9
978-3-642-04238-6
issn 0302-9743
1611-3349
doi_str_mv 10.1007/978-3-642-04238-6_57
publisher Springer
college_str Faculty of Humanities and Social Sciences
hierarchytype
hierarchy_top_id facultyofhumanitiesandsocialsciences
hierarchy_top_title Faculty of Humanities and Social Sciences
hierarchy_parent_id facultyofhumanitiesandsocialsciences
hierarchy_parent_title Faculty of Humanities and Social Sciences
department_str School of Social Sciences - Education and Childhood Studies{{{_:::_}}}Faculty of Humanities and Social Sciences{{{_:::_}}}School of Social Sciences - Education and Childhood Studies
url https://link.springer.com/chapter/10.1007%2F978-3-642-04238-6_57
document_store_str 1
active_str 0
description This paper presents the Total Optimisation using Answer Set Technology (TOAST) system, which can be used to generate optimal code sequences for machine architectures via a technique known as superoptimisation. Answer set programming (ASP) is utilised as the modelling and computational framework for searching over the large, complex search spaces and for proving the functional equivalence of two code sequences. Experimental results are given showing the progress made in solver performance over the previous few years, along with an outline of future developments to the system and applications within compiler toolchains.
published_date 2009-09-14T03:54:39Z
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score 11.013731