Tuning the optimization parameter set for code size

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Abstract

Determining nearly optimal optimization options for modern day compilers is a combinatorial problem. Added to this, specific to a given application, platform and optimization objective, fine tuning the parameter set being used by various optimization passes, enhance the complexity further. In this paper we propose a greedy based iterative approach and investigate the impact of fine-tuning the parameter set on the code size. The effectiveness of our approach is demonstrated on some of benchmark programs from SPEC2006 benchmark suite that there is a significant impact of tuning the parameter values on the code size. © 2012 Springer-Verlag.

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APA

Chebolu, N. A. B. S., Wankar, R., & Chillarige, R. R. (2012). Tuning the optimization parameter set for code size. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7694 LNAI, pp. 214–223). https://doi.org/10.1007/978-3-642-35455-7_20

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