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Dynamic run-time architecture techniques for enabling continuous optimization
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Source Conference On Computing Frontiers archive
Proceedings of the 2nd conference on Computing frontiers table of contents
Ischia, Italy
SESSION: Track 7: compilers and operating systems table of contents
Pages: 211 - 220  
Year of Publication: 2005
ISBN:1-59593-019-1
Authors
Tipp Moseley  University of Colorado, Boulder, CO
Alex Shye  University of Colorado, Boulder, CO
Vijay Janapa Reddi  University of Colorado, Boulder, CO
Matthew Iyer  University of Colorado, Boulder, CO
Dan Fay  University of Colorado, Boulder, CO
David Hodgdon  University of Colorado, Boulder, CO
Joshua L. Kihm  University of Colorado, Boulder, CO
Alex Settle  University of Colorado, Boulder, CO
Dirk Grunwald  University of Colorado, Boulder, CO
Daniel A. Connors  University of Colorado, Boulder, CO
Sponsor
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 8,   Downloads (12 Months): 38,   Citation Count: 2
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ABSTRACT

Future computer systems will integrate tens of multithreaded processor cores on a single chip die, resulting in hundreds of concurrent program threads sharing system resources. These designs will be the cornerstone of improving throughput in high-performance computing and server environments. However, to date, appropriate systems software (operating system, run-time system, and compiler) technologies for these emerging machines have not been adequately explored. Future processors will require sophisticated hardware monitoring units to continuously feed back resource utilization information to allow the operating system to make optimal thread co-scheduling decisions and also to software that continuously optimizes the program itselfNevertheless, in order to continually and automatically adapt systems resources to program behaviors and application needs, specific run-time information must be collected to adequately enable dynamic code optimization and operating system scheduling. Generally, run-time optimization is limited by the time required to collect profiles, the time required to perform optimization, and the inherent benefits of any optimization or decisions. Initial techniques for effectively utilizing run-time information for dynamic optimization and informed thread scheduling in future multithreaded architectures are presented


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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Collaborative Colleagues:
Tipp Moseley: colleagues
Alex Shye: colleagues
Vijay Janapa Reddi: colleagues
Matthew Iyer: colleagues
Dan Fay: colleagues
David Hodgdon: colleagues
Joshua L. Kihm: colleagues
Alex Settle: colleagues
Dirk Grunwald: colleagues
Daniel A. Connors: colleagues