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Grant: Discovery Grants Program - Individual

Carleton University

$70,000.00

Simulation and Performance Optimization of Large-Scale Systems in the Presence of Uncertainties

EF 2020-21

Résumé
The rapid evolution of the global electronic industry is unceasingly introducing new products operating at ever higher frequencies and bitrates. At such high data rates, high-frequency effects become the dominant factor limiting the overall performance of microelectronic systems. In addition, the fast rising demand for multifunction and miniature products warrants integration of heterogeneous circuit modules. As a result, the traditional boundaries between different design domains are fast vanishing. Moreover, variability of the geometrical and physical parameters and its effect on the system performance is adding another major concern. This uncertainty becomes inevitable at all levels of the design hierarchy. For example, manufacturing uncertainties can significantly influence the performance of on-chip interconnects, leading to timing variations that can propagate to the circuit or board level with negative impact on the whole system performance and yield. The research proposal calls for a paradigm shift in the development of the underlying design algorithms and methodologies by promoting “Design for Uncertainties” as a major ingredient in the design process. As a step towards this goal, several of the planned research activities are focused on the development of specialized stochastic algorithms to model and simulate the underlying statistical information at different levels of the design hierarchy. In addition, systematic methods will be developed to incorporate these algorithms in the design cycle to achieve optimal design centering. The planned research addresses generic strategic issues common to high-speed applications and will advance the state-of-art in a broad spectrum of interrelated topics. The success of the proposed research will provide designers with the ability to efficiently plan and design large-scale systems that are not currently feasible; resulting in superior and more reliable multi-function electronic and communication products. In addition, the benefits of the proposed research are not limited to the design of high-speed electronic systems since large-scale and uncertainty quantification challenges are common issues in several other fields within engineering and science.
Programme
Discovery Grants Program - Individual
Bénéficiaire
Emplacement
Ontario, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data

Tel que publié

Application id
RGPIN-2017-06368
Name nom
Nakhla, Michel
Department département
Electronics
Organization id
23
Institution établissement
Carleton University
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2020
Competition year année de concours
2017
Award amount
70000
Program id
RGPIN
Program name en
Discovery Grants Program - Individual
Program name fr
Programme de subventions à la découverte - individuelles
Group en
Discovery grants programs
Group fr
Programmes de subventions à la découverte
Committee code
1510
Committee name en
Electrical and Computer Engineering
Committee name fr
Génie électrique et informatique
Area of application code
1207
Area of application group en
Advancement of knowledge
Area of application group fr
Avancement des connaissances
Area of application en
Information, computer and communication technologies
Area of application fr
Technologie de l'information, des ordinateurs et des réseaux de communications
Research subject code
2519
Research subject group en
Electrical and electronic engineering
Research subject group fr
Génie électrique et électronique
Research subject en
Microelectronics
Research subject fr
Microélectronique
Installment
inst:4-5
Partie
2
Nb partie
5
Application title
Simulation and Performance Optimization of Large-Scale Systems in the Presence of Uncertainties
Keyword
NSERC
Application summary
The rapid evolution of the global electronic industry is unceasingly introducing new products operating at ever higher frequencies and bitrates. At such high data rates, high-frequency effects become the dominant factor limiting the overall performance of microelectronic systems. In addition, the fast rising demand for multifunction and miniature products warrants integration of heterogeneous circuit modules. As a result, the traditional boundaries between different design domains are fast vanishing. Moreover, variability of the geometrical and physical parameters and its effect on the system performance is adding another major concern. This uncertainty becomes inevitable at all levels of the design hierarchy. For example, manufacturing uncertainties can significantly influence the performance of on-chip interconnects, leading to timing variations that can propagate to the circuit or board level with negative impact on the whole system performance and yield. The research proposal calls for a paradigm shift in the development of the underlying design algorithms and methodologies by promoting “Design for Uncertainties” as a major ingredient in the design process. As a step towards this goal, several of the planned research activities are focused on the development of specialized stochastic algorithms to model and simulate the underlying statistical information at different levels of the design hierarchy. In addition, systematic methods will be developed to incorporate these algorithms in the design cycle to achieve optimal design centering. The planned research addresses generic strategic issues common to high-speed applications and will advance the state-of-art in a broad spectrum of interrelated topics. The success of the proposed research will provide designers with the ability to efficiently plan and design large-scale systems that are not currently feasible; resulting in superior and more reliable multi-function electronic and communication products. In addition, the benefits of the proposed research are not limited to the design of high-speed electronic systems since large-scale and uncertainty quantification challenges are common issues in several other fields within engineering and science.