Model-Based Framework: An Approach for Profit-Driven Optimization

Although optimizations have been applied for a number of years to improve the performance of software, problems that have been long-standing remain, which include knowing what optimizations to apply and how to apply them. To systematically tackle these problems, we need to understand the properties of optimizations. In our current research, we are investigating the profitability property, which is useful for determining the benefit of applying an optimization. Due to the high cost of applying optimizations and then experimentally evaluating their profitability, we use an analytic model framework for predicting the profitability of optimizations. In this paper, we target scalar optimizations, and in particular, describe framework instances for Partial Redundancy Elimination (PRE) and Loop Invariant Code Motion (LICM). We implemented the framework for both optimizations and compare profitdriven PRE and LICM with a heuristic-driven approach. Our experiments demonstrate that a model-based...

• Type: Conference
• Year: 2005
• Where: CGO
• Authors: Min Zhao, Bruce R. Childers, Mary Lou Soffa
• Keywords: CGO 2005, Model-based Approach, Profitability Property, Scalar Optimizations, Software Engineering