Abstract
It is very natural when people compile their programs, they would require a compiler that gives the best program performance. Even though today’s compiler have reached the point in which they provide the users a large number of options, however, because of the unavailability of program input data and insufficient knowledge of the target architecture; it can still seriously limit the accuracy of compile-time performance models. Thus, the problem is how to choose the best combination of optimization options provided by compiler for a given program or program section. This gives rise the requirement of an orchestration algorithm that fast and effective to search for the best optimization combination for a program.
There have been several algorithms developed, such as Exhaustive Search (ES); Batch Elimination (BE); Iterative Elimination (IE); Combined Elimination (CE); Optimization Space Exploration (OSE); and Statistical Selection (SS). Based on those of algorithms, in this paper we proposed Heuristics Elimination (HE) algorithm, a simple algorithm that was mostly inspired by OSE with some differences. The HE algorithm uses a heuristic approach by applying genetic algorithm to find the best combination of compiler’s optimization options. It is unlike OSE, however, this proposed algorithm starts from a set of some possible combinations randomly selected, then they are iteratively refined by some genetic operators to find one optimal combination (as the solution).
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Hedayat, A., Sloane, N., Stufken, J.: Orthogonal Arrays: Theory and Applications. Springer (1999)
Chow, K., Wu, Y.: Feedback-directed selection and characterization of compiler optimizations. In: Second Workshop on Feedback Directed Optimizations, Israel (November 1999)
Box, G.E.P., Hunter, W.G., Hunter, J.S.: Statistics for Experimenters: an introduction to design, data analysis, and model building. John Wiley and Sons (1978)
Chow, K., Wu, Y.: Feedback-directed selection and characterization of compiler optimizations. In: Second workshop of Feedback-directed Optimizations, Israel (November 1999)
Nadia, N., Ajith, A., Luiza de Macedo, M.: Genetic Systems Programming - Theory and Experience. Springer (2006)
Sloane, N.J.A.: A Library of Orthogonal Arrays, http://www.research.att.com/njas/oadir/
Kulkarni, P., Hines, S., Hiser, J., Whalley, D., Davidson, J., Jones, D.: Fast Searches for Effective Optimization Phase Sequences. In: PLDI 2004: Proceeding of the ACM SIGPLAN 2004 Conference of Programming Language Design and Implementation, pp. 171–182. ACM Press, New York (2004)
Pinkers, R.P.J., Knijnenburg, P.M.W., Haneda, M., Wijshoff, H.A.G.: Statistical selection of compiler optimizations. In: The IEEE Computer Societies 12th Annual International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunications Systems (MAS - COTS 2004), Volendam, The Netherlands, pp. 494–501 (October 2004)
Triantafillis, S., Vacharajani, M., Vacharajani, N., August, D.I.: Compiler Optimization-space Exploration. In: Proceedings of the International Symposium on Code generation and Optimization, pp. 204–215 (2003)
Kisuki, T., Knijnenburg, P.M.W., O’Boyle, M.F.P., Bodin, F., Wijshoff, H.A.G.: A Feasibility Study in Iterative Compilation. In: Fukuda, A., Joe, K., Polychronopoulos, C.D. (eds.) ISHPC 1999. LNCS, vol. 1615, pp. 121–132. Springer, Heidelberg (1999)
Pan, Z., Eigenmann, R.: Compiler Optimization Orchestration for peak performance. Technical Report TR-ECE-04-01. School of Electrical and Computer Engineering, Purdue University (2004)
Pan, Z., Eigenmann, R.: Rating Compiler Optimizations for automatic performance tuning. In: SC 2004: High Performance Computing, Networking and Storage Conference, 10 pages (November 2004)
Pan, Z., Eigenmann, R.: Rating Compiler Optimizations for Automatic Performance Tuning. IEEE (2004)
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Suprapto, Wardoyo, R. (2013). Algorithms of the Combination of Compiler Optimization Options for Automatic Performance Tuning. In: Mustofa, K., Neuhold, E.J., Tjoa, A.M., Weippl, E., You, I. (eds) Information and Communication Technology. ICT-EurAsia 2013. Lecture Notes in Computer Science, vol 7804. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36818-9_10
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