In this paper we describe two types of complex server aggregations which can be used to model collections of components in certain types of parallel computersystems and give a case study showing how the aggregations ...
ISBN:
(纸本)9780897911849
In this paper we describe two types of complex server aggregations which can be used to model collections of components in certain types of parallel computersystems and give a case study showing how the aggregations may be applied in practice. Analytical models of such systems are becoming increasingly important as a means of guiding the often complex design processes, particularly since recent developments in VLSI technology now make it possible to fabricate many paper-designs hitherto impractical for reasons of cost. We argue that aggregations of the type described are essential in the modelling of parallel systems; using the proposed techniques, large numbers of components can be modelled as queue-length-dependent servers within a queueing network in which the number of servers is the same as the number of distinct types of processing element in the system being modelled. Because the number of severs in the model is fixed i.e. is independent of the number of processors, very large multiprocessor systems can be modelled efficiently with no explosion in the size of the state space.
In models of virtual memory computersystems, it is generally assumed that the time intervals between the page (or segment) faults, often called lifetimes, are independent from each other. Due to the phase-transition ...
ISBN:
(纸本)9780897911849
In models of virtual memory computersystems, it is generally assumed that the time intervals between the page (or segment) faults, often called lifetimes, are independent from each other. Due to the phase-transition behaviour in many real programs this is not always true, and strong correlations may exist between successive lifetimes. These correlations may have a notable effect on the system behaviour. This paper describes a series of experiments where autoregressive -moving average (ARMA) models are used to describe the correlation structure in sequences of lifetimes. It is shown that many real program executions can be described with models having four parameters only, i.e. with the ARMA(1,1) models. The models can be used as parts of simulation models for instance, and they also give us better understanding about the program behaviour in general.
This tutorial is an introduction to performance modeling in the design of integrated circuits (ICs). It assumes no background in either electrical engineering or VLSI design; all relevant concepts and terminology will...
ISBN:
(纸本)9780897911849
This tutorial is an introduction to performance modeling in the design of integrated circuits (ICs). It assumes no background in either electrical engineering or VLSI design; all relevant concepts and terminology will be introduced. The goal is to give an overview of the role of performance modeling in IC design, the current state of the art, central problems and research ***, the process of IC design will be reviewed. Every design progresses through a series of stages: concept, architecture, implementation and realization. Each level of design manipulates different abstractions and hence is concerned with different measures of design quality. Some principle measures are: speed, silicon area, power consumption and the number of input/output connections. There are several different major design paradigms such as gate array, standard cell and custom design. Each results in different tradeoffs between flexibility, ease of implementation and design quality. This has a fundamental impact on both the design process and the resulting *** considerations enter into IC design at a variety of levels: device, circuit, logic design and architecture. Each requires different performance models, and the designer must make tradeoffs that are qualitatively different at different levels. Circuit level design requires fast and accurate models of logic gate behavior. A circuit's speed, silicon area and power consumption must be accurately estimated. Each of these circuit characteristics can be traded off against the others, and the designer may adjust the tradeoff in order to tune the circuit to the needs of a particular application. Accurate and computationally fast models form the basis for the tools that assist the designer in circuit optimization. Tools exist that accurately predict circuit performance and that automatically optimize *** circuit design is a field still in its infancy. This, coupled with the fact that the underlying technol
Queueing models provide a useful tool for predicting the performance of many service systems including computersystems, telecommunication systems, computer/communication networks and flexible manufacturing systems. T...
ISBN:
(纸本)9780897911849
Queueing models provide a useful tool for predicting the performance of many service systems including computersystems, telecommunication systems, computer/communication networks and flexible manufacturing systems. Traditional queueing models predict system performance under the assumption that all service facilities provide failure-free service. It must, however, be acknowledged that service facilities do experience failures and that they get repaired. In recent years, it has been increasingly recognized that this separation of performance and reliability/availability models is no longer *** exact steady-state queueing analysis of such systems is considered by several authors and is carried out by means of generating functions, supplementary variables, imbedded Markov process and renewal theory, or probabilistic techniques [1,2,7,8]. Another approach is approximate, in which it is assumed that the time to reach the steady-state is much smaller than the times to failures/repairs. Therefore, it is reasonable to associate a performance measure (reward) with each state of the underlying Markov (or semi-Markov) model describing the failure/repair behavior of the system. Each of these performance measures is obtained from the steady-state queueing analysis of the system in the corresponding state [3,5].Earlier we have developed models to derive the distribution of job completion time in a failure-prone environment [3,4]. In these models, we need to consider a possible loss of work due to the occurrence of a failure, i.e., the interrupted job may be resumed or restarted upon service resumption. Note that the job completion time analysis includes the delays due to failures and repairs. The purpose of this paper [9] is to extend our earlier analysis so as to account for the queueing delays. In effect, we consider an exact queueing analysis of fault-tolerant systems in order to obtain the steady-state distribution and the mean of the number of jobs in the system. In
There are a number of views as to what software reliability is and how it should be quantified. Some people believe that this measure should be binary in nature so that an imperfect program would have zero reliability...
ISBN:
(纸本)9780897911849
There are a number of views as to what software reliability is and how it should be quantified. Some people believe that this measure should be binary in nature so that an imperfect program would have zero reliability while a perfect one would have a reliability value of one. This view parallels that of program proving whereby the program is either correct or incorrect. Others, however, feel that software reliability should be defined as the relative frequency of the times that the program works as intended by the user. This view is similar to that taken in testing where a percentage of the successful ewes is used as a measure of program quality. According to the latter viewpoint, software reliability is a probabilistic measure and can be defined as follows:Let F be a class of faults, defined arbitrarily, and T be a measure of relevant time, the units of which are dictated by the application at hand. Then the reliability of the software package with respect to the class of faults F and with respect to the metric T, is the probability that no fault of the class occurs during the execution of the program for a prespecified period of relevant time.A number of models have been proposed during the past fifteen years to estimate software reliability and several other performance measures. These are based mainly on the failure history of software and can be classified according to the nature of the failure process studied as indicated *** Between Failures Models: In this class of models the process under study is the time between failures. The most common approach is to assume that the time between, say, the (i-1)st and ith failures, follows a distribution whose parameters depend on the number of faults remaining in the program during this *** Count Models: The interest of this class of models is in the number of faults or failures in specified time intervals rather than in times between failures. The failure counts are assumed to follow a known stocha
The proceedings contain 20 papers. The topics discussed include: A comparison of receiver-initiated and sender-initiated adaptive load sharing;an adaptive communication protocol for network computers;RECAL - a new eff...
ISBN:
(纸本)0897911695
The proceedings contain 20 papers. The topics discussed include: A comparison of receiver-initiated and sender-initiated adaptive load sharing;an adaptive communication protocol for network computers;RECAL - a new efficient algorithm for the exact analysis of multiple-chain closed queuing networks;on the availability of a distributed computer system failing components;modeling priority schemes;non-exponential networks of queues: a maximum entropy analysis;sensitivity study of the clustering approach to workload modeling;empirical results on locality in database referencing;degradable computersystems with dependent subsystems;and the effect of system workload on error latency: an experimental study.
We develop Generalized Stochastic Petri Net models for several priority queueing disciplines. The building blocks of these models are explained and many variants are easily derivable from them. We then combine these b...
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When building a model for degradable computer syrtems, it ir not sufficient to merely quantify reliability and performance measures. There indicer must be mathematically sound if they we to be wed to design such syste...
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