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Using annotations to reduce dynamic optimization time
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Source Conference on Programming Language Design and Implementation archive
Proceedings of the ACM SIGPLAN 2001 conference on Programming language design and implementation table of contents
Snowbird, Utah, United States
Pages: 156 - 167  
Year of Publication: 2001
ISBN:1-58113-414-2
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Authors
Chandra Krintz  University of California, San Diego, Department of Computer Science and Engineering, La Jolla, CA
Brad Calder  University of California, San Diego, Department of Computer Science and Engineering, La Jolla, CA
Sponsor
SIGPLAN: ACM Special Interest Group on Programming Languages
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 9,   Downloads (12 Months): 46,   Citation Count: 19
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ABSTRACT

Dynamic compilation and optimization are widely used in heterogenous computing environments, in which an intermediate form of the code is compiled to native code during execution. An important trade off exists between the amount of time spent dynamically optimizing the program and the running time of the program. The time to perform dynamic optimizations can cause significant delays during execution and also prohibit performance gains that result from more complex optimization.

In this research, we present an annotation framework that substantially reduces compilation overhead of Java programs. Annotations consist of analysis information collected off-line and are incorporated into Java programs. The annotations are then used by dynamic compilers to guide optimization. The annotations we present reduce compilation overhead incurred at all stages of compilation and optimization as well as enable complex optimizations to be performed dynamically. On average, our annotation optimizations reduce optimized compilation overhead by 78% and enable speedups of 7% on average for the programs examined.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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CITED BY  19
 
 
 
 
 
 
 

Collaborative Colleagues:
Chandra Krintz: colleagues
Brad Calder: colleagues

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