Dynamic Optimization through the use of Automatic Runtime Specialization
John H. Whaley · DSpace@MIT (Massachusetts Institute of Technology) · 1999
Profile-driven optimizations and dynamic optimization through specialization have taken optimizations to a new level. By using actual runtime data, optimizers can generate code that is specially tuned for the task at hand. However, most existing compilers that perform these optimizations require separate test runs to gather profile information, and/or user annotations in the code. In this thesis, I describe runtime optimizations that a dynamic compiler can perform automatically --- without user annotations --- by utilizing realtime performance data. I describe the implementation of the dynamic optimizations in the framework of a Java Virtual Machine and give performance results.