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Towards a Systematic, Pragmatic and Architecture-Aware Program Optimization Process for Complex Processors
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Source Conference on High Performance Networking and Computing archive
Proceedings of the 2004 ACM/IEEE conference on Supercomputing table of contents
Page: 15  
Year of Publication: 2004
ISBN:0-7695-2153-3
Authors
David Parello  HP France and HiPEAC network
Olivier Temam  INRIA Futurs, Paris Sud University and HiPEAC network
Albert Cohen  INRIA Futurs and HiPEAC network
Jean-Marie Verdun  HP France
Sponsor
SIGARCH: ACM Special Interest Group on Computer Architecture
Publisher
IEEE Computer Society  Washington, DC, USA
Bibliometrics
Downloads (6 Weeks): 1,   Downloads (12 Months): 15,   Citation Count: 5
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abstract   references   cited by   collaborative colleagues  

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DOI Bookmark: 10.1109/SC.2004.61

ABSTRACT

Because processor architectures are increasingly complex, it is increasingly difficult to embed accurate machine models within compilers. As a result, compiler efficiency tends to decrease. Currently, the trend is on top-down approaches: static compilers are progressively augmented with information from the architecture as in profile-based, iterative or dynamic compilation techniques. However, for the moment, fairly elementary architectural information is used. In this article, we adopt a bottom-up approach to the architecture complexity issue: we assume we know everything about the behavior of the program on the architecture. We present a manual but systematic process for optimizing a program on a complex processor architecture using extensive dynamic analysis, and we find that a small set of run-time information is sufficient to drive anefficient process. We have experimentally observed on an Alpha 21264 that this approach can yield significant performance improvement on Spec benchmarks, beyond peak Spec. We are currently using this approach for optimizing customer applications.


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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[1] C. Bastoul, A. Cohen, S. Girbal, S. Sharma, and O. Temam. Putting polyhedral loop transformation to work. In 10th International Workshop on Languages and Compilers for Parallel Computing (LCPC), October 2003.
 
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[4] G. Fursin, M. O'Boyle, and P. Knijnenburg. Evaluating iterative compilation. In 11th Workshop on Languages and Compilers for Parallel Computing, LNCS, Washington DC, July 2002. Springer-Verlag.
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[6] Intel Itanium2 processor reference manual for software development and optimization. http: //developer.intel.com/design/itatium2/manuals.
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[8] T. Kisuki, P. Knijnenburg, M. O'Boyle, and H. Wijshoff. Iterative compilation in program optimization. In Proc. CPC'10 (Compilers for Parallel Computers), pages 35-44, 2000.
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[10] Oprofile project. http://oprofile.sourceforge.net.
 
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[11] Open research compiler. http://ipf-orc.sourceforge.net.
 
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[14] Perfmon project. http://www.hpl.hp.com/research/linux/perfmon.
 
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[15] Standard performance evaluation corporation. http://www.spec.org.
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[17] Intel VTune performance analysers. http://www.intel.com/software/products/vtune.
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CITED BY  5
Collaborative Colleagues:
David Parello: colleagues
Olivier Temam: colleagues
Albert Cohen: colleagues
Jean-Marie Verdun: colleagues