2026-09-18T19:59:56Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/333922022-01-13T07:54:29Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Saman P. Amarasinghe.
Yu, Chris, 1981-
Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2006-07-13T15:20:32Z
2006-07-13T15:20:32Z
2004
2004
http://hdl.handle.net/1721.1/33392
62560239
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2004.
Includes bibliographical references (leaves 74-75).
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.
by Chris Yu.
M.Eng.
75 leaves
2815540 bytes
2818608 bytes
application/pdf
application/pdf
eng
Massachusetts Institute of Technology
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http://dspace.mit.edu/handle/1721.1/7582
Electrical Engineering and Computer Science.
Characterizing function inlining with genetic programming
Thesis
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Publication
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