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dc.contributor.authorAlmagor, L.
Cooper, Keith D.
Grosul, Alexander
Harvey, Timothy J.
Reeves, Steven W.
Subramanian, Devika
Torczon, Linda
Waterman, Todd
dc.date.accessioned 2017-08-02T22:03:01Z
dc.date.available 2017-08-02T22:03:01Z
dc.date.issued 2004-06-18
dc.identifier.urihttps://hdl.handle.net/1911/96327
dc.description.abstract Most modern compilers operate by applying a fixed sequence of code optimizations, called a compilation sequence, to all programs. Compiler writers determine a small set of good, general-purpose, compilation sequences by extensive hand-tuning over particular benchmarks. The compilation sequence makes a significant difference in the quality of the generated code; in particular, we know that a single universal compilation sequence does not produce the best results over all programs. Three questions arise in customizing compilation sequences: (1) What is the incremental benefit of using a customized sequence instead of a universal sequence? (2) What is the average computational cost of constructing a customized sequence? (3) When does the benefit exceed the cost? We present one of the first empirically derived cost-benefit tradeoff curves for custom compilation sequences. These curves are for two randomized sampling algorithms: descent with randomized restarts and genetic algorithms. They demonstrate the dominance of these two methods over simple random sampling in sequence spaces where the probability of finding a good sequence is very low. Further, these curves allow compilers to decide whether custom sequence generation is worthwhile, by explicitly relating the computational effort required to obtain a program-specific sequence to the incremental improvement in quality of code generated by that sequence.
dc.format.extent 12 pp
dc.language.iso eng
dc.rights You are granted permission for the noncommercial reproduction, distribution, display, and performance of this technical report in any format, but this permission is only for a period of forty-five (45) days from the most recent time that you verified that this technical report is still available from the Computer Science Department of Rice University under terms that include this permission. All other rights are reserved by the author(s).
dc.title Compilation Order Matters: Exploring the Structure of the Space of Compilation Sequences Using Randomized Search Algorithms
dc.type Technical report
dc.date.note June 18, 2004
dc.identifier.digital TR04-436
dc.type.dcmi Text
dc.identifier.citation Almagor, L., Cooper, Keith D., Grosul, Alexander, et al.. "Compilation Order Matters: Exploring the Structure of the Space of Compilation Sequences Using Randomized Search Algorithms." (2004) https://hdl.handle.net/1911/96327.


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