Getting Feedback on a Compiler's Optimization Decisions, Enabling More Code-Optimization Opportunities
Gyeong Il Min, Sewon Park, Miseon Han, Seon Wook Kim · IEIE Transactions on Smart Processing and Computing · 2015
Short execution time is the major performance factor for computer systems. This performance factor is directly determined by code quality, which is influenced by the compiler’s optimizations. However, a compiler has limitations when optimizing source code due to insufficient information. Thus, if programmers can learn the reasons why a compiler fails to apply optimizations, they can rewrite code that is more easily understood by the compiler, and thus improve performance. In this paper, we propose a compiler that provides a programmer with reasons for failed optimization and recognizes programmer’s additional information to obtain better optimization. As a result, we obtain performance improvement, i.e., reducing execution time and code size, by taking advantage of additional optimization opportunities.