Self-tuning resource aware specialisation for prolog

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Self-tuning resource aware specialisation for prolog
The paper develops a self-tuning resource aware partial evaluation technique for Prolog programs, which derives its own control strategies tuned for the underlying computer architecture and Prolog compiler using a genetic algorithm approach. The algorithm is based on mutating the annotations of offline partial evaluation. Using a set of representative sample queries it decides upon the fitness of annotations, controlling the trade-off between code explosion, speedup gained and specialisation time. The user can specify the importance of each of these factors in determining the quality of the produced code, tailouring the specialisation to the particular problem at hand. We present experimental results for our implemented technique on a series of benchmarks. The results are compared against the aggressive termination based binding-time analysis and optimised using different measures for the quality of code. We also show that our technique avoids some classical pitfalls of partial eva...
Stephen-John Craig, Michael Leuschel
Added 28 Jun 2010
Updated 28 Jun 2010
Type Conference
Year 2005
Where PPDP
Authors Stephen-John Craig, Michael Leuschel
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