As feature size keeps scaling down, process variations can dramatically reduce the accuracy in the estimation of interconnect performance. This paper proposes a statistical Elmore delay model for RC interconnect tree ...As feature size keeps scaling down, process variations can dramatically reduce the accuracy in the estimation of interconnect performance. This paper proposes a statistical Elmore delay model for RC interconnect tree in the presence of process variations. The suggested method translates the process variations into parasitic parameter extraction and statistical Elmore delay evaluation. Analytical expressions of mean and standard deviation of interconnect delay can be obtained in a given t^uctuation range of interconnect geometric parameters. Experimental results demonstrate that the approach matches well with Monte Carlo simulations. The errors of proposed mean and standard deviation are less than 1% and 7%, respectively. Simulations prove that our model is efficient and accurate.展开更多
As the feature size of the CMOS integrated circuit continues to shrink, process variations have become a key factor affecting the interconnect performance. Based on the equivalent Elmore model and the use of the polyn...As the feature size of the CMOS integrated circuit continues to shrink, process variations have become a key factor affecting the interconnect performance. Based on the equivalent Elmore model and the use of the polynomial chaos theory and the Galerkin method, we propose a linear statistical RCL interconnect delay model, taking into account process variations by successive application of the linear approximation method. Based on a variety of nano-CMOS process parameters, HSPICE simulation results show that the maximum error of the proposed model is less than 3.5%. The proposed model is simple, of high precision, and can be used in the analysis and design of nanometer integrated circuit interconnect systems.展开更多
In this paper, some issues related to design and analysis of real networked control systems （NCS） under the focus of the most likely region of stability are addressed. Such a system is cumbersome due to its inherent...In this paper, some issues related to design and analysis of real networked control systems （NCS） under the focus of the most likely region of stability are addressed. Such a system is cumbersome due to its inherent variable time delays, ranging from microseconds to hours. To show the influence of such huge variations in the control performance, a laboratory-scale luminosity system has been setup using the Internet as part of the control loop with dominant time constant in the order of milliseconds. Proportional and integral （PI） control strategies with and without explicit compensation for the time-delay variations were implemented using an event-driven controller. Using the well-known Monte Carlo method and subsequent analyses of time responses, it has been possible to identify the most likely region of stability. Some experimental results show the influence of the statistical parameters of the delays on the determination of the most likely regions of stability of the NCS and how these can be used in assessment and redesign of the control system. The experiments show that much larger delays than one sample period can be supported by real NCSs without becoming unstable.展开更多
基金Project supported by the National Natural Science Foundation of China (Grant No. 60606006)the National Science Fund forDistinguished Young Scholars of China (Grant No. 60725415)the Basic Science Research Fund in Xidian University,China
文摘As feature size keeps scaling down, process variations can dramatically reduce the accuracy in the estimation of interconnect performance. This paper proposes a statistical Elmore delay model for RC interconnect tree in the presence of process variations. The suggested method translates the process variations into parasitic parameter extraction and statistical Elmore delay evaluation. Analytical expressions of mean and standard deviation of interconnect delay can be obtained in a given t^uctuation range of interconnect geometric parameters. Experimental results demonstrate that the approach matches well with Monte Carlo simulations. The errors of proposed mean and standard deviation are less than 1% and 7%, respectively. Simulations prove that our model is efficient and accurate.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.60725415 and 60971066)the National Science&Technology Important Project of China(Grant No.2009ZX01034-002-001-005)The National Key Laboratory Foundation(Grant No.ZHD200904)
文摘As the feature size of the CMOS integrated circuit continues to shrink, process variations have become a key factor affecting the interconnect performance. Based on the equivalent Elmore model and the use of the polynomial chaos theory and the Galerkin method, we propose a linear statistical RCL interconnect delay model, taking into account process variations by successive application of the linear approximation method. Based on a variety of nano-CMOS process parameters, HSPICE simulation results show that the maximum error of the proposed model is less than 3.5%. The proposed model is simple, of high precision, and can be used in the analysis and design of nanometer integrated circuit interconnect systems.
基金supported by the Energy Utility Company of Minas Gerais(CEMIG)
文摘In this paper, some issues related to design and analysis of real networked control systems （NCS） under the focus of the most likely region of stability are addressed. Such a system is cumbersome due to its inherent variable time delays, ranging from microseconds to hours. To show the influence of such huge variations in the control performance, a laboratory-scale luminosity system has been setup using the Internet as part of the control loop with dominant time constant in the order of milliseconds. Proportional and integral （PI） control strategies with and without explicit compensation for the time-delay variations were implemented using an event-driven controller. Using the well-known Monte Carlo method and subsequent analyses of time responses, it has been possible to identify the most likely region of stability. Some experimental results show the influence of the statistical parameters of the delays on the determination of the most likely regions of stability of the NCS and how these can be used in assessment and redesign of the control system. The experiments show that much larger delays than one sample period can be supported by real NCSs without becoming unstable.
