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Towards formal probabilistic power-performance design space exploration
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Source Great Lakes Symposium on VLSI archive
Proceedings of the 16th ACM Great Lakes symposium on VLSI table of contents
Philadelphia, PA, USA
SESSION: Timing optimization table of contents
Pages: 229 - 234  
Year of Publication: 2006
ISBN:1-59593-347-6
Authors
Joonsoo Kim  The University of Texas at Austin
Michael Orshansky  The University of Texas at Austin
Sponsors
ACM: Association for Computing Machinery
SIGDA: ACM Special Interest Group on Design Automation
Publisher
ACM  New York, NY, USA
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ABSTRACT

We describe a formal probabilistic power-performance design space exploration technique. The technique aims at enabling hierarchical design space exploration based on a fully probabilistic description of power-performance tradeoffs. Probabilistic Pareto sets in power-performance space are proposed as canonical encodings of the power and delay tradeoffs in designs under any source of uncertainty. An algorithm to compute a composite probabilistic power-performance Pareto set for series or parallel connections of circuit blocks is also developed and validated. The algorithm is based on numerical convolution and is suitable for micro-architecture pipeline design exploration in the presence of process variability.


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:
Joonsoo Kim: colleagues
Michael Orshansky: colleagues