Singhee Amith (40 results)
Language: English
Published by Springer, 2012
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Language: English
Published by Springer, 2010
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Paperback. Condition: Brand New. 2009 edition. 210 pages. 9.25x6.10x0.48 inches. In Stock.
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Taschenbuch. Condition: Neu. Novel Algorithms for Fast Statistical Analysis of Scaled Circuits | Amith Singhee (u. a.) | Taschenbuch | xv | Englisch | 2012 | Springer | EAN 9789400736870 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbi…eter: preigu.
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - As VLSI technology moves to the nanometer scale for transistor feature sizes, the impact of manufacturing imperfections result in large variations in the circuit performance. Traditional CAD tools are not well-equipped to handle this scenario, sinc…e they do not model this statistical nature of the circuit parameters and performances, or if they do, the existing techniques tend to be over-simplified or intractably slow. Novel Algorithms for Fast Statistical Analysis of Scaled Circuits draws upon ideas for attacking parallel problems in other technical fields, such as computational finance, machine learning and actuarial risk, and synthesizes them with innovative attacks for the problem domain of integrated circuits. The result is a set of novel solutions to problems of efficient statistical analysis of circuits in the nanometer regime.
Language: English
Published by Springer, 2012
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Language: English
Published by Springer, 2010
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Language: English
Published by Springer Us, 2010
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Condition: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | Extreme Statistics in Nanoscale Memory Design brings together some of the world's leading experts in statistical EDA, memory design, device variability modeling and reliability modeling, to compile theoretical and practical results in one c…omplete reference on statistical techniques for extreme statistics in nanoscale memories.The work covers a variety of techniques, including statistical, deterministic, model-based and non-parametric methods, along with relevant description of the sources of variations and their impact on devices and memory design. Specifically, the authors cover methods from extreme value theory, Monte Carlo simulation, reliability modeling, direct memory margin computation and hypervolume computation. Ideas are also presented both from the perspective of an EDA practitioner and a memory designer to provide a comprehensive understanding of the state-of -the-art in the area of extreme statistics estimation and statistical memory design.Extreme Statistics in Nanoscale Memory Design is a useful reference on statistical design of integrated circuits for researchers, engineers and professionals.
Language: English
Published by Springer, 2010
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Condition: New. pp. 258.
Language: English
Published by Springer, 2012
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More imagesLanguage: English
Published by Springer, 2012
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Taschenbuch. Condition: Neu. Extreme Statistics in Nanoscale Memory Design | Amith Singhee (u. a.) | Taschenbuch | Integrated Circuits and Systems | x | Englisch | 2012 | Springer | EAN 9781461426721 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[d…ot]com | Anbieter: preigu.
Language: English
Published by Springer US, Springer US, 2012
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Knowledge exists: you only have to nd it VLSI design has come to an important in ection point with the appearance of large manufacturing variations as semiconductor technology has moved to 45 nm feature sizes and below. If we ignore the random vari…ations in the manufacturing process, simulation-based design essentially becomes useless, since its predictions will be far from the reality of manufactured ICs. On the other hand, using design margins based on some traditional notion of worst-case scenarios can force us to sacri ce too much in terms of power consumption or manufacturing cost, to the extent of making the design goals even infeasible. We absolutely need to explicitly account for the statistics of this random variability, to have design margins that are accurate so that we can nd the optimum balance between yield loss and design cost. This discontinuity in design processes has led many researchers to develop effective methods of statistical design, where the designer can simulate not just the behavior of the nominal design, but the expected statistics of the behavior in manufactured ICs. Memory circuits tend to be the hardest hit by the problem of these random variations because of their high replication count on any single chip, which demands a very high statistical quality from the product. Requirements of 5-6s (0.
Language: English
Published by Springer Us, 2010
- Hardcover
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Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Knowledge exists: you only have to nd it VLSI design has come to an important in ection point with the appearance of large manufacturing variations as semiconductor technology has moved to 45 nm feature sizes and below. If we ignore the random variations…in the manufacturing process, simulation-based design essentially becomes useless, since its predictions will be far from the reality of manufactured ICs. On the other hand, using design margins based on some traditional notion of worst-case scenarios can force us to sacri ce too much in terms of power consumption or manufacturing cost, to the extent of making the design goals even infeasible. We absolutely need to explicitly account for the statistics of this random variability, to have design margins that are accurate so that we can nd the optimum balance between yield loss and design cost. This discontinuity in design processes has led many researchers to develop effective methods of statistical design, where the designer can simulate not just the behavior of the nominal design, but the expected statistics of the behavior in manufactured ICs. Memory circuits tend to be the hardest hit by the problem of these random variations because of their high replication count on any single chip, which demands a very high statistical quality from the product. Requirements of 5-6s (0.
Language: English
Published by Springer, 2012
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Language: English
Published by Springer Us, 2010
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Hardcover. Condition: gut. 2010. Extreme Statistics in Nanoscale Memory Design In englischer Sprache. pages.
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Language: English
Published by Springer, 2012
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Language: English
Published by Springer, 2010
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents flexible and general techniques for statistical analysis that can be applied to wide variety of circuit applicationsApplies theory from a wide variety of scientific fields (machine learning, computational fin…ance, number theory, actuarial.
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Gebunden. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents flexible and general techniques for statistical analysis that can be applied to wide variety of circuit applicationsApplies theory from a wide variety of scientific fields (machine learning, computa…tional finance, number theory, actuarial.
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Condition: New. Print on Demand pp. 212 52:B&W 6.14 x 9.21in or 234 x 156mm (Royal 8vo) Case Laminate on White w/Gloss Lam.
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Condition: New. Print on Demand pp. 212 49:B&W 6.14 x 9.21 in or 234 x 156 mm (Royal 8vo) Perfect Bound on White w/Gloss Lam.
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Condition: New. PRINT ON DEMAND pp. 212.
Language: English
Published by Springer US Nov 2012, 2012
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Knowledge exists: you only have to nd it VLSI design has come to an important in ection point with the appearance of large manufacturing variations as semiconductor technology has moved to 45 nm feature sizes and below. If we ignore… the random variations in the manufacturing process, simulation-based design essentially becomes useless, since its predictions will be far from the reality of manufactured ICs. On the other hand, using design margins based on some traditional notion of worst-case scenarios can force us to sacri ce too much in terms of power consumption or manufacturing cost, to the extent of making the design goals even infeasible. We absolutely need to explicitly account for the statistics of this random variability, to have design margins that are accurate so that we can nd the optimum balance between yield loss and design cost. This discontinuity in design processes has led many researchers to develop effective methods of statistical design, where the designer can simulate not just the behavior of the nominal design, but the expected statistics of the behavior in manufactured ICs. Memory circuits tend to be the hardest hit by the problem of these random variations because of their high replication count on any single chip, which demands a very high statistical quality from the product. Requirements of 5-6s (0. 256 pp. Englisch.
