Characterizing function inlining with genetic programming
Name
62560239-MIT.pdf
Description
Full printable version
Size
3.65 MB
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Checksum (MD5)
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Author(s)
Yu, Chris, 1981-
Advisor(s)
Saman P. Amarasinghe.
Date Issued
2004
Publisher
Massachusetts Institute of Technology
Abstract
Function inlining is a compiler optimization where the function call is replaced by the code from the function itself. Using a form of machine learning called genetic programming, this thesis examines which factors are important in determining which function calls to inline to maximize performance. A number of different heuristics are generated for inlining decisions in the Trimaran compiler, which improve on performance from the current default inlining heuristic. Also, trends in function inlining are examined over the thousands of compilation runs that are completed.
Description
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2004.
Includes bibliographical references (leaves 74-75).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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