Improving both the performance benefits and speed of optimization phase sequence searches

The issues of compiler optimization phase ordering and selection present important challenges to compiler developers in several domains, and in particular to the speed, code size, power, and costconstrained domain of embedded systems. Different sequences of optimization phases have been observed to provide the best performance for different applications. Compiler writers and embedded systems developers have recently addressed this problem by conducting iterative empirical searches using machine-learning based heuristic algorithms in an attempt to find the phase sequences that are most effective for each application. Such searches are generally performed at the program level, although a few studies have been performed at the function level. The finer granularity of functionlevel searches has the potential to provide greater overall performance benefits, but only at the cost of slower searches caused by a greater number of performance evaluations that often require expensive program sim...

• Type: Journal
• Year: 2010
• Where: LCTRTS
• Authors: Prasad A. Kulkarni, Michael R. Jantz, David B. Whalley
• Keywords: LCTRTS 2010, Optimization Phases, Performance, Performance Benefits, System Software