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Erschienen in:
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2011 | OriginalPaper | Buchkapitel

7. Multi-objective Optimizations

verfasst von : Paul Lokuciejewski, Peter Marwedel

Erschienen in: Worst-Case Execution Time Aware Compilation Techniques for Real-Time Systems

Verlag: Springer Netherlands

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Abstract

The development of high-performance optimizing compilers is an inherently hard problem for many reasons. Besides the complex task of generating efficient compiler heuristics, optimizations that are performed in a sequence may exhibit non-trivial interactions with other optimizations as well as with the underlying hardware. For modern systems, the situation becomes even worse. In addition to the challenges of finding promising optimization sequences, modern systems have to meet different requirements. In case of embedded real-time systems, not only the WCET but also the average-case execution time or the code size are critical. This chapter provides a complementary solution for the construction of high-performance compilers. It begins with a discussion of the general structure of an adaptive compiler and shows how the WCC is accordingly extended. To cope with the huge search space of compiler optimizations, an automatic approach for compiler optimization sequence exploration based on evolutionary multi-objective search algorithms is presented. The effectiveness of this approach is demonstrated on real-life benchmarks.

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Vorheriges Kapitel Machine Learning Techniques in Compiler Design
Nächstes Kapitel Summary and Future Work
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Metadaten
Titel
Multi-objective Optimizations
verfasst von
Paul Lokuciejewski
Peter Marwedel
Copyright-Jahr
2011
Verlag
Springer Netherlands
Buch
Worst-Case Execution Time Aware Compilation Techniques for Real-Time Systems

Print ISBN: 978-90-481-9928-0

Electronic ISBN: 978-90-481-9929-7

Copyright-Jahr: 2011

DOI
https://doi.org/10.1007/978-90-481-9929-7_7

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