http://hdl.handle.net/2117/3646 Tue, 21 May 2013 16:21:13 GMT 2013-05-21T16:21:13Z webmaster.bupc@upc.edu Universitat Politècnica de Catalunya. Servei de Biblioteques i Documentació no http://hdl.handle.net/2117/15667 Title: Process variability in sub-16nm bulk CMOS technology Authors: Rubio Sola, Jose Antonio; Figueras Pàmies, Joan; Vatajelu, Elena Ioana; Canal Corretger, Ramon Abstract: The document is part of deliverable D3.6 of the TRAMS Project (EU FP7 248789), of public nature, and shows and justifies the levels of variability used in the research project for sub-18nm bulk CMOS technologies. Mon, 26 Mar 2012 18:45:53 GMT http://hdl.handle.net/2117/15667 2012-03-26T18:45:53Z Rubio Sola, Jose Antonio; Figueras Pàmies, Joan; Vatajelu, Elena Ioana; Canal Corretger, Ramon no The document is part of deliverable D3.6 of the TRAMS Project (EU FP7 248789), of public nature, and shows and justifies the levels of variability used in the research project for sub-18nm bulk CMOS technologies. http://hdl.handle.net/2117/7846 Title: A Failure-Distance Based Method to Bound the Reliability of Non-Repairable Fault-Tolerant Systems without the Knowledge of Minimal Cuts Authors: Suñé Socías, Víctor Manuel; Carrasco López, Juan Antonio Abstract: CTMC (continuous-time Markov chains) are a commonly used formalism for modeling fault-tolerant systems. One of the major drawbacks of CTMC is the well-known state-space explosion problem. This work develops and analyzes a method (SC-BM) to compute bounds for the reliability of non-repairable fault-tolerant systems in which only a portion of the state space of the CTMC is generated. SC-BM uses the failure distance concept as the method described in [1] but, unlike that method, which is based on the computation of exact failure distances, SC-BM uses lower bounds for failure distances, which are computed on the system fault tree, avoiding the computation and holding of all minimal cuts as required in [1]. This is important since computation of all minimal cuts is NP-hard and the number of minimal cuts can be very large. In some cases SCBM gives exactly the same bounds as the method described in [1]; in other cases it gives less tighter bounds. SC-BM computes tight bounds for the reliability of quite complex systems with an affordable number of generated states for short to quite large mission times. The analysis of several examples seems to show that the bounds obtained by SC-BM appreciably outperform those obtained by simpler methods, eg [2], and, when they are not equal, are only slightly worse than the bounds obtained by the method in [1]. In addition, the overhead in CPU time due to computing lower bounds for failure distances seems to be reasonable. Fri, 25 Jun 2010 15:21:51 GMT http://hdl.handle.net/2117/7846 2010-06-25T15:21:51Z Suñé Socías, Víctor Manuel; Carrasco López, Juan Antonio no CTMC (continuous-time Markov chains) are a commonly used formalism for modeling fault-tolerant systems. One of the major drawbacks of CTMC is the well-known state-space explosion problem. This work develops and analyzes a method (SC-BM) to compute bounds for the reliability of non-repairable fault-tolerant systems in which only a portion of the state space of the CTMC is generated. SC-BM uses the failure distance concept as the method described in [1] but, unlike that method, which is based on the computation of exact failure distances, SC-BM uses lower bounds for failure distances, which are computed on the system fault tree, avoiding the computation and holding of all minimal cuts as required in [1]. This is important since computation of all minimal cuts is NP-hard and the number of minimal cuts can be very large. In some cases SCBM gives exactly the same bounds as the method described in [1]; in other cases it gives less tighter bounds. SC-BM computes tight bounds for the reliability of quite complex systems with an affordable number of generated states for short to quite large mission times. The analysis of several examples seems to show that the bounds obtained by SC-BM appreciably outperform those obtained by simpler methods, eg [2], and, when they are not equal, are only slightly worse than the bounds obtained by the method in [1]. In addition, the overhead in CPU time due to computing lower bounds for failure distances seems to be reasonable. http://hdl.handle.net/2117/7845 Title: Transient Analysis of Large Markov Models with Absorbing States using Regenerative Randomization Authors: Carrasco López, Juan Antonio Abstract: In this paper, we develop a new method, called regenerative randomization, for the transient analysis of continuous time Markov models with absorbing states. The method has the same good properties as standard randomization: numerical stability, well-controlled computation error, and ability to specify the computation error in advance. Themethod has a benign behavior for large t and is significantly less costly than standard randomization for large enough models and large enough t. For a class of models, class C, including typical failure/repair reliability models with exponential failure and repair time distributions and repair in every state with failed components, stronger theoretical results are available assessing the efficiency of the method in terms of “visible” model characteristics. A large example belonging to that class is used to illustrate the performance of the method and to show that it can indeed be much faster than standard randomization. Fri, 25 Jun 2010 15:14:30 GMT http://hdl.handle.net/2117/7845 2010-06-25T15:14:30Z Carrasco López, Juan Antonio no In this paper, we develop a new method, called regenerative randomization, for the transient analysis of continuous time Markov models with absorbing states. The method has the same good properties as standard randomization: numerical stability, well-controlled computation error, and ability to specify the computation error in advance. Themethod has a benign behavior for large t and is significantly less costly than standard randomization for large enough models and large enough t. For a class of models, class C, including typical failure/repair reliability models with exponential failure and repair time distributions and repair in every state with failed components, stronger theoretical results are available assessing the efficiency of the method in terms of “visible” model characteristics. A large example belonging to that class is used to illustrate the performance of the method and to show that it can indeed be much faster than standard randomization. http://hdl.handle.net/2117/7844 Title: A Generalized Method for the Transient Analysis of Markov Models of Fault-Tolerant Systems with Deferred Repair Authors: Temsamani, Jamal; Carrasco López, Juan Antonio Abstract: Randomization is an attractive alternative for the transient analysis of continuous timeMarkov models. The main advantages of the method are numerical stability, well-controlled computation error and ability to specify the computation error in advance. However, the fact that the method can be computationally expensive limits its applicability. Recently, a variant of the (standard) randomization method, called split regenerative randomization has been proposed for the efficient analysis of reliability-like models of fault-tolerant systems with deferred repair. In this paper, we generalize that method so that it covers more general reward measures: the expected transient reward rate and the expected averaged reward rate. The generalized method has the same good properties as the standard randomization method and, for large models and large values of the time t at which the measure has to be computed, can be significantly less expensive. The method requires the selection of a subset of states and a regenerative state satisfying some conditions. For a class of continuous time Markov models, class C 2, including typical failure/repair reliability models with exponential failure and repair time distributions and deferred repair, natural selections for the subset of states and the regenerative state exist and results are available assessing approximately the computational cost of the method in terms of “visible” model characteristics. Using a large model class C 2 example, we illustrate the performance of the method and show that it can be significantly faster than previously proposed randomization-based methods. Fri, 25 Jun 2010 15:09:25 GMT http://hdl.handle.net/2117/7844 2010-06-25T15:09:25Z Temsamani, Jamal; Carrasco López, Juan Antonio no Randomization is an attractive alternative for the transient analysis of continuous timeMarkov models. The main advantages of the method are numerical stability, well-controlled computation error and ability to specify the computation error in advance. However, the fact that the method can be computationally expensive limits its applicability. Recently, a variant of the (standard) randomization method, called split regenerative randomization has been proposed for the efficient analysis of reliability-like models of fault-tolerant systems with deferred repair. In this paper, we generalize that method so that it covers more general reward measures: the expected transient reward rate and the expected averaged reward rate. The generalized method has the same good properties as the standard randomization method and, for large models and large values of the time t at which the measure has to be computed, can be significantly less expensive. The method requires the selection of a subset of states and a regenerative state satisfying some conditions. For a class of continuous time Markov models, class C 2, including typical failure/repair reliability models with exponential failure and repair time distributions and deferred repair, natural selections for the subset of states and the regenerative state exist and results are available assessing approximately the computational cost of the method in terms of “visible” model characteristics. Using a large model class C 2 example, we illustrate the performance of the method and show that it can be significantly faster than previously proposed randomization-based methods. http://hdl.handle.net/2117/7843 Title: An Efficient and Numerically Stable Method for Computing Interval Availability Distribution Bounds Authors: Carrasco López, Juan Antonio Abstract: The paper develops a method, called bounding regenerative transformation, for the computation with numerical stability and well-controlled error of bounds for the interval availability distribution of systems modeled by finite (homogeneous) continuous-time Markov chain models with a particular structure. The method requires the selection of a regenerative state and is targeted at a class of models, class C 1, with a “natural” selection for the regenerative state. For class C 1 models, bounds tightness can be traded-off with computational cost through a control parameter DC, with the option DC = 1 yielding the smallest computational cost. For large class C 1 models and the selection DC = 1, the method will often have a small computational cost relative to the model size and, with additional conditions, seems to yield tight bounds for any time interval or not small time intervals, depending on the initial probability distribution of the model. Class C 1 models with those additional conditions include both exact and bounding failure/repair models of coherent fault-tolerant systems with exponential failure and repair time distributions and repair in every state with failed components with failure rates much smaller than repair rates. Fri, 25 Jun 2010 15:01:16 GMT http://hdl.handle.net/2117/7843 2010-06-25T15:01:16Z Carrasco López, Juan Antonio no The paper develops a method, called bounding regenerative transformation, for the computation with numerical stability and well-controlled error of bounds for the interval availability distribution of systems modeled by finite (homogeneous) continuous-time Markov chain models with a particular structure. The method requires the selection of a regenerative state and is targeted at a class of models, class C 1, with a “natural” selection for the regenerative state. For class C 1 models, bounds tightness can be traded-off with computational cost through a control parameter DC, with the option DC = 1 yielding the smallest computational cost. For large class C 1 models and the selection DC = 1, the method will often have a small computational cost relative to the model size and, with additional conditions, seems to yield tight bounds for any time interval or not small time intervals, depending on the initial probability distribution of the model. Class C 1 models with those additional conditions include both exact and bounding failure/repair models of coherent fault-tolerant systems with exponential failure and repair time distributions and repair in every state with failed components with failure rates much smaller than repair rates. http://hdl.handle.net/2117/7842 Title: Simulation of Steady-state Availability Models of Fault-Tolerant Systems with Deferred Repair Authors: Carrasco López, Juan Antonio Abstract: This paper targets the simulation of continuous-timeMarkov chain models of fault-tolerant systems with deferred repair. We start by stating sufficient conditions for a given importance sampling scheme to satisfy the bounded relative error property. Using those sufficient conditions, it is noted that many previously proposed importance sampling schemes such as failure biasing and balanced failure biasing satisfy that property. Then, we adapt the importance sampling schemes failure transition distance biasing and balanced failure transition distance biasing so as to develop new importance sampling schemes which can be implemented with moderate effort and at the same time can be proved to be more efficient for balanced systems than the simpler failure biasing and balanced failure biasing schemes. The increased efficiency for balanced and unbalanced systems of the new adapted importance sampling schemes is illustrated using examples. Fri, 25 Jun 2010 14:52:31 GMT http://hdl.handle.net/2117/7842 2010-06-25T14:52:31Z Carrasco López, Juan Antonio no This paper targets the simulation of continuous-timeMarkov chain models of fault-tolerant systems with deferred repair. We start by stating sufficient conditions for a given importance sampling scheme to satisfy the bounded relative error property. Using those sufficient conditions, it is noted that many previously proposed importance sampling schemes such as failure biasing and balanced failure biasing satisfy that property. Then, we adapt the importance sampling schemes failure transition distance biasing and balanced failure transition distance biasing so as to develop new importance sampling schemes which can be implemented with moderate effort and at the same time can be proved to be more efficient for balanced systems than the simpler failure biasing and balanced failure biasing schemes. The increased efficiency for balanced and unbalanced systems of the new adapted importance sampling schemes is illustrated using examples. http://hdl.handle.net/2117/1232 Title: Energy macro-model for on chip interconnection buses Authors: Mendoza Vázquez, Raymundo; Pons Solé, Marc; Moll Echeto, Francisco de Borja; Figueras, Joan Abstract: This report presents a fast method of evaluating the power consumption of a bus. Given an on-chip bus driver-interconnection-receiver design of N parallel lines,the objective is to develop its energy consumption macro-model. With this model we are be able to evaluate the energy metrics for the bus under a certain traffic and information coding. Fri, 05 Oct 2007 08:09:54 GMT http://hdl.handle.net/2117/1232 2007-10-05T08:09:54Z Mendoza Vázquez, Raymundo; Pons Solé, Marc; Moll Echeto, Francisco de Borja; Figueras, Joan no digital integrated circuits, crosstalk, power consumption, leakage current This report presents a fast method of evaluating the power consumption of a bus. Given an on-chip bus driver-interconnection-receiver design of N parallel lines,the objective is to develop its energy consumption macro-model. With this model we are be able to evaluate the energy metrics for the bus under a certain traffic and information coding.