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Research Interests
Ph.D. Thesis
A Model-based
Framework for Exploring the Application of
Opitimizations
Abstract
Although optimizations have
been applied by compilers for over 40 years, much of the research
has been devoted to the development of particular optimizations.
Certain problems with respect to the application of optimizations
have yet to be adequately addressed, including applying only
beneficial optimizations, ordering optimizations, selecting
optimization configurations and combining optimizations. With the
rapidly growing use of cost-sensitive embedded systems, handling
these problems to maximize the benefits from applying optimizations
becomes all the more important. several approaches have been
proposed for handling some of these problems, there is no general,
uniform way to effectively address the problems. This work proposes
to develop a unifying framework through models for systematically
exploring the application of optimizations, particularly in embedded
systems. The framework will provide both analytical and experimental
models for understanding, predicting and verifying the properties of
optimizations (i.e., performance impact and interactions). Also,
practical and automatic strategies to drive the application of
optimizations based on the models will be part of the framework. By
applying these model-based optimization strategies, the goal is that
optimizing compilers will be able to produce higher quality code
than what is possible with current
approaches. |
