Importance sampled circuit learning ensembles for robust analog IC design
Created by W.Langdon from
gp-bibliography.bib Revision:1.8051
- @InProceedings{Gao:2008:ICCAD,
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author = "Peng Gao and Trent McConaghy and Georges Gielen",
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title = "Importance sampled circuit learning ensembles for
robust analog IC design",
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booktitle = "IEEE/ACM International Conference on Computer-Aided
Design, ICCAD 2008",
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year = "2008",
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pages = "396--399",
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address = "San Jose, CA, USA",
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month = "10-13 " # nov,
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keywords = "genetic algorithms, genetic programming, EHW, analogue
integrated circuits, analogue-digital conversion,
importance sampling, integrated circuit design,
waveform generators, ISCLEs-specific library, Moore's
Law, analog IC design, block topology, boosting
algorithm, digital-sized circuits, flash A-D converter,
importance sampling, learning ensembles, multi-topology
sizing technique, sinusoidal function generator, Analog
integrated circuits, Assembly, Boosting, Circuit
topology, Design methodology, Monte Carlo methods,
Moore's Law, Robustness, Signal generators, Software
libraries",
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isbn13 = "978-1-4244-2819-9",
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URL = "http://trent.st/content/2008-ICCAD-iscles.pdf",
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DOI = "doi:10.1109/ICCAD.2008.4681604",
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size = "4 pages",
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abstract = "This paper presents ISCLEs, a novel and robust analog
design method that promises to scale with Moore's Law,
by doing boosting-style importance sampling on
digital-sized circuits to achieve the target analog
behaviour. ISCLEs consists of: (1) a boosting algorithm
developed specifically for circuit assembly; (2) an
ISCLEs-specific library of possible digital-sized
circuit blocks; and (3) a recently-developed
multi-topology sizing technique to automatically
determine each block's topology and device sizes.
ISCLEs is demonstrated on design of a sinusoidal
function generator and a flash A/D converter, showing
promise to robustly scale with shrinking process
geometries.",
-
notes = "also known as \cite{4681604}",
- }
Genetic Programming entries for
Peng Gao
Trent McConaghy
Georges G E Gielen
Citations