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.
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Haneda, M., Knijnenburg, P.M.W., Wijshoff, H.A.G.: Automatic Selection of Compiler Options using Non-Parametric Inferential statistics. In: 14th International Conference on Parallel Architectures and Compilation Techniques (PACT 2005) (2005)
Adve, V.: The Next Generation of Compilers. In: Proc. of CGO (2009)
Duranton, M., Black-Schaffer, D., Yehia, S., De Bosschere, K.: Computing Systems: Research Challenges Ahead The HiPEAC Vision 2011/2012
Kulkarni, P.A., Hines, S.R., Whalley, D.B., et al.: Fast and Efficient Searches for Effective Optimization-phase Sequences. Transactions on Architecture and Code Optimization (2005)
Leather, H., O’Boyle, M., Worton, B.: Raced Profiles: Efficient Selection of Competing Compiler Optimizations. In: Proc. of LCTES (2009)
Agakov, F., Bonilla, E., Cavazos, J., et al.: Using Machine Learning to Focus Iterative Optimization. In: Proc. of CGO (2006)
Cooper, K.D., Schielke, P.J., Subramanian, D.: Optimizing for Reduced Code Space using Genetic Algorithms. SIGPLAN Not. 34(7) (1999)
Khedkar, U., Govindrajan, R.: Compiler Analysis and Optimizations: What is New? In: Proc. of Hipc (2003)
Beszédes, Á., Gergely, T., Gyimóthy, T., Lóki, G., Vidács, L.: Optimizing for Space: Measurements and Possibilities for Improvement. In: Proc. of GCC Developers Summit (2003)
GCC, the GNU Compiler Collection - online documentation, http://gcc.gnu.org/onlinedocs/
Novillo, D.: Performance Tuning with GCC. Red Hat Magazine (September 2005)
SPEC-Standard Performance Evaluation Corporation, http://www.spec.org/cpu2006
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Chebolu, N.A.B.S., Wankar, R., Chillarige, R.R. (2012). Tuning the Optimization Parameter Set for Code Size. In: Sombattheera, C., Loi, N.K., Wankar, R., Quan, T. (eds) Multi-disciplinary Trends in Artificial Intelligence. MIWAI 2012. Lecture Notes in Computer Science(), vol 7694. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35455-7_20
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DOI: https://doi.org/10.1007/978-3-642-35455-7_20
Publisher Name: Springer, Berlin, Heidelberg
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