A FINE-GRAINED DEMAND DRIVEN IPO INFRASTRUCTURE

摘要

Provided are methods and systems for inter-procedural optimization (IPO). A new IPO architecture (referred to as "ThinLTO") is designed to address the weaknesses and limitations of existing IPO approaches, such as traditional Link Time Optimization (LTO) and Lightweight Inter-Procedural Optimization (LIPO), and become a new link-time-optimization standard. With ThinLTO, demand-driven and summary-based fine grain importing maximizes the potential of Cross-Module Optimization (CMO), which enables as much useful CMO as possible. ThinLTO also provides for global indexing, which enables fast function importing; parallelizes some performance-critical but expensive inter-procedural analyses and transformations; utilizes demand-driven, lazy importing of debug information that minimizes memory consumption for the debug build; and allows easy integration of third-party distributed build systems. In addition, ThinLTO may also be implemented using an IPO server, thereby removing the need for the serial step.