TOAST: Applying Answer Set Programming to Superoptimisation
Author(s) -
Martin Brain,
Tom Crick,
Marina De Vos,
John Fitch
Publication year - 2006
Publication title -
lecture notes in computer science
Language(s) - English
Resource type - Book series
SCImago Journal Rank - 0.249
H-Index - 400
eISSN - 1611-3349
pISSN - 0302-9743
ISBN - 3-540-36635-0
DOI - 10.1007/11799573_21
Subject(s) - computer science , answer set programming , scalability , set (abstract data type) , programming language , simple (philosophy) , variety (cybernetics) , theoretical computer science , scale (ratio) , code (set theory) , artificial intelligence , database , philosophy , physics , epistemology , quantum mechanics
Answer set programming (ASP) is a form of declarative programming particularly suited to difficult combinatorial search problems. However, it has yet to be used for more than a handful of large-scale applications, which are needed to demonstrate the strengths of ASP and to motivate the development of tools and methodology. This paper describes such a large-scale application, the TOAST (Total Optimisation using Answer Set Technology) system, which seeks to generate optimal machine code for simple, acyclic functions using a technique known as superoptimisation. ASP is used as a scalable computational engine to handle searching over complex, non-regular search spaces, with the experimental results suggesting that this is a viable approach to the optimisation problem and demonstrates the scalability of a variety of solvers.
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