A Machine Learning Based Compiler Optimization Technique

Abstract

Since the last decade to upcoming era the need of machine learning based compilation approaches has become indispensable for every aspect of growing technology especially artificial intelligence and network computing areas. These approaches are used to enhance the result quality by their improved performance as well as handles compiler optimization problems namely optimization selection and phase ordering. It has enthused from a vague research place in middle of the road movement. Wealth of present compiler optimization techniques leads to finding the best heuristic parameters to tune each optimization tactic using machine learning. In this research paper, we highlighted the term machine learning and compiler along with relationship between compiler optimization and machine learning with the identity of the concept of models, training, and approaches.