Using Evolutionary Algorithms to Optimize Execution Time and Code Size in Iterative Compilation

• Main Authors: Chou, Yanchuan, 周彥全
• Other Authors: Lin, Naiwei
• Format: Others
• Language: zh-TW
• Published: 2012
• Online Access: http://ndltd.ncl.edu.tw/handle/45985658286655008582

碩士 === 國立中正大學 === 資訊工程研究所 === 100 === Modern compilers usually provide a large number of optimization options to aid users to fine tune their programs for the best performance. However, applying such optimization options involves complex knowledge about compiler optimization, so most users do not have the capability to utilize these optimization options. Iterative Compilation is currently the most common approach to searching for the optimal set of optimization options for a program. There are several interesting performance metrics in compiler optimization: execution time, compilation time, code size, memory space, power consumption, and other computing resources. This research investigates multi-objective optimization of execution time and code size in Iterative Compilation using the popular multi-objective evolutionary algorithms NSGA-II and MOEA/D. The experimental results show that the optimization sequences chosen by both algorithms are superior to the ones generated by the random search algorithm and the ones corresponding to the optimization levels provided by the compiler.