1,761 research outputs found

    Transient analysis of manufacturing system performance

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    Includes bibliographical references (p. 28-34).Supported by the INDO-US Science and Technology Fellowship Program.Y. Narahari, N. Viswanadham

    Rail transit fare collection: Policy and technology assessment

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    The impact of fare policies and fare structure on the selection of equipment was investigated, fare collection systems are described, hardware and technology related problems are documented, and the requirements of a fare collection simulation model are outlined. Major findings include: (1) a wide variation in the fare collection systems and equipment, caused primarily by historical precedence; (2) the reliability of AFC equipment used at BART and WMATA discouraged other properties from considering use of similar equipment; (3) existing equipment may not meet the fare collection needs of properties in the near future; (4) the cost of fare collection operation and maintenance is high; and (5) the relatively small market in fare collection equipment discourages new product development by suppliers. Recommendations for fare collection R&D programs include development of new hardware to meet rail transit needs, study of impacts of alternate fare policies increased communication among policymakers, and consensus on fare policy issues

    EARLY PERFORMANCE PREDICTION METHODOLOGY FOR MANY-CORES ON CHIP BASED APPLICATIONS

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    Modern high performance computing applications such as personal computing, gaming, numerical simulations require application-specific integrated circuits (ASICs) that comprises of many cores. Performance for these applications depends mainly on latency of interconnects which transfer data between cores that implement applications by distributing tasks. Time-to-market is a critical consideration while designing ASICs for these applications. Therefore, to reduce design cycle time, predicting system performance accurately at an early stage of design is essential. With process technology in nanometer era, physical phenomena such as crosstalk, reflection on the propagating signal have a direct impact on performance. Incorporating these effects provides a better performance estimate at an early stage. This work presents a methodology for better performance prediction at an early stage of design, achieved by mapping system specification to a circuit-level netlist description. At system-level, to simplify description and for efficient simulation, SystemVerilog descriptions are employed. For modeling system performance at this abstraction, queueing theory based bounded queue models are applied. At the circuit level, behavioral Input/Output Buffer Information Specification (IBIS) models can be used for analyzing effects of these physical phenomena on on-chip signal integrity and hence performance. For behavioral circuit-level performance simulation with IBIS models, a netlist must be described consisting of interacting cores and a communication link. Two new netlists, IBIS-ISS and IBIS-AMI-ISS are introduced for this purpose. The cores are represented by a macromodel automatically generated by a developed tool from IBIS models. The generated IBIS models are employed in the new netlists. Early performance prediction methodology maps a system specification to an instance of these netlists to provide a better performance estimate at an early stage of design. The methodology is scalable in nanometer process technology and can be reused in different designs

    Dynamical Modeling of Cloud Applications for Runtime Performance Management

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    Cloud computing has quickly grown to become an essential component in many modern-day software applications. It allows consumers, such as a provider of some web service, to quickly and on demand obtain the necessary computational resources to run their applications. It is desirable for these service providers to keep the running cost of their cloud application low while adhering to various performance constraints. This is made difficult due to the dynamics imposed by, e.g., resource contentions or changing arrival rate of users, and the fact that there exist multiple ways of influencing the performance of a running cloud application. To facilitate decision making in this environment, performance models can be introduced that relate the workload and different actions to important performance metrics.In this thesis, such performance models of cloud applications are studied. In particular, we focus on modeling using queueing theory and on the fluid model for approximating the often intractable dynamics of the queue lengths. First, existing results on how the fluid model can be obtained from the mean-field approximation of a closed queueing network are simplified and extended to allow for mixed networks. The queues are allowed to follow the processor sharing or delay disciplines, and can have multiple classes with phase-type service times. An improvement to this fluid model is then presented to increase accuracy when the \emph{system size}, i.e., number of servers, initial population, and arrival rate, is small. Furthermore, a closed-form approximation of the response time CDF is presented. The methods are tested in a series of simulation experiments and shown to be accurate. This mean-field fluid model is then used to derive a general fluid model for microservices with interservice delays. The model is shown to be completely extractable at runtime in a distributed fashion. It is further evaluated on a simple microservice application and found to accurately predict important performance metrics in most cases. Furthermore, a method is devised to reduce the cost of a running application by tuning load balancing parameters between replicas. The method is built on gradient stepping by applying automatic differentiation to the fluid model. This allows for arbitrarily defined cost functions and constraints, most notably including different response time percentiles. The method is tested on a simple application distributed over multiple computing clusters and is shown to reduce costs while adhering to percentile constraints. Finally, modeling of request cloning is studied using the novel concept of synchronized service. This allows certain forms of cloning over servers, each modeled with a single queue, to be equivalently expressed as one single queue. The concept is very general regarding the involved queueing discipline and distributions, but instead introduces new, less realistic assumptions. How the equivalent queue model is affected by relaxing these assumptions is studied considering the processor sharing discipline, and an extension to enable modeling of speculative execution is made. In a simulation campaign, it is shown that these relaxations only has a minor effect in certain cases

    A Metamodel-Based Monte Carlo Simulation Approach for Responsive Production Planning of Manufacturing Systems

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    Production planning is concerned with finding a release plan of jobs into the manufacturing system so that its actual outputs over time match the customer demand with the least cost. The biggest challenge of production planning lies in the difficulty to quantify the performance of a release plan, which is the necessary basis for plan optimization. Triggered by an input plan over a time horizon, the system outputs, work in process (WIP) and job departures, are non-stationary bivariate time series that interact with customer demand (another time series), resulting in the fulfillment/non-fulfillment of demand and in the holding cost of both WIP and finished-goods inventory. The relationship between a release plan and its resulting performance metrics (typically, mean/variance of the total cost and the demand fulfill rate is far from being adequately quantified in the existing literature of production planning. In this dissertation, a metamodel-based Monte Carlo simulation (MCS) method is developed to accurately capture the dynamic and stochastic behavior of a manufacturing system, and to allow for real-time evaluation of a release plan in terms of its performance metrics. This evaluation capability is embedded in a multi-objective optimization framework to enable the quick search of good (or optimum) release plans. The developed method has been applied to a scaled-down semiconductor fabrication system to demonstrate the quality of the metamodel-based MCS evaluation and the plan optimization results

    On the distribution of throughput of transfer lines

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    Ankara : Department of Industrial Engineering and the Institute of Engineering and Sciences of Bilkent University, 1998.Thesis (Master's) -- Bilkent University, 1998.Includes bibliographical references leaves 86-107A transfer line corresponds to a manufacturing system consisting of a number of work stations in series integrated into one system by a common transfer mechanism and a control system. There is a vast literature on the transfer lines. However, little has been done on the transient analysis of these systems by making use of the higher order moments of their performance measures due to the difficulty in determining the evolution of the stochastic processes under consideration. This thesis examines the transient behavior of relatively short transfer lines and derives the distribution of the performance measures of interest. The proposed method based on the analytical derivation of the distribution of throughput is also applied to the systems with two-part types. An experiment is designed in order to compare the results of this study with the state-space representations and the simulation. They are also interpreted from the point of view of the line behavior and design issue. Furthermore, extensions are briefly discussed and directions for future research are suggested.Deler, BaharM.S

    Parallel algorithms for simulating continuous time Markov chains

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    We have previously shown that the mathematical technique of uniformization can serve as the basis of synchronization for the parallel simulation of continuous-time Markov chains. This paper reviews the basic method and compares five different methods based on uniformization, evaluating their strengths and weaknesses as a function of problem characteristics. The methods vary in their use of optimism, logical aggregation, communication management, and adaptivity. Performance evaluation is conducted on the Intel Touchstone Delta multiprocessor, using up to 256 processors
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