60 research outputs found

    Grand Challenges of Advanced Computing for Energy Innovation Report from the Workshop Held July 31-August 2, 2012

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    On July 31-August 2 of 2012, the U.S. Department of Energy (DOE) held a workshop entitled Grand Challenges of Advanced Computing for Energy Innovation. This workshop built on three earlier workshops that clearly identified the potential for the Department and its national laboratories to enable energy innovation. The specific goal of the workshop was to identify the key challenges that the nation must overcome to apply the full benefit of taxpayer-funded advanced computing technologies to U.S. energy innovation in the ways that the country produces, moves, stores, and uses energy. Perhaps more importantly, the workshop also developed a set of recommendations to help the Department overcome those challenges. These recommendations provide an action plan for what the Department can do in the coming years to improve the nation’s energy future

    Dagstuhl News January - December 2000

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    "Dagstuhl News" is a publication edited especially for the members of the Foundation "Informatikzentrum Schloss Dagstuhl" to thank them for their support. The News give a summary of the scientific work being done in Dagstuhl. Each Dagstuhl Seminar is presented by a small abstract describing the contents and scientific highlights of the seminar as well as the perspectives or challenges of the research topic

    Stochastic modelling of spatial collective adaptive systems

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    Collective Adaptive Systems (CAS) are composed of individual agents with internal knowledge and rules which organize themselves into ensembles. These ensembles can often be observed to exhibit behaviour resembling that of a single entity with a clear goal and a consistent internal knowledge, even when the individual agents within the ensemble are not managed by any outside, globally-accessible entity. Because of their lack of a need for centralized control which results in high robustness, CAS are commonly observed in nature – and for similar reasons are often reflected in human engineered systems. Researching the patterns of operation observed in such systems provides meaningful insight into how to design and optimise stable multiagent systems capable of withstanding adverse conditions. Formal modelling provides valuable intellectual tools which can be applied to the problem of analysis of systems by means of modelling and simulation. In this thesis we explore the modelling of CAS in which space (topology and distances) plays a significant role. Working with CARMA (Collective Adaptive Resource-sharing Markovian Agents) a formal feature-rich language for modelling stochastic CAS, we investigate a number of spatial CAS scenarios from the realm of urban planning. When components operate in a spatial context, their behaviour can be affected by where they are located in that space. For example, their location can influence the speed at which they move, and their ability to communicate with other components. Components in CARMA have internal store, and behaviour expressed by Markov processes. They can communicate with each other through sending messages on state transitions in a unicast or broadcast fashion. Simulation with pseudo-random events can be used to obtain values of measures applied to CARMA models, providing a basis for analysis and optimisation. The CARMA models developed in the case studies are data-driven and the results of simulating these models are compared with real-world data. In particular, we explore two scenarios: crowd-routing and city transportation systems. Building on top of CARMA, we also introduce CGP (CARMA Graphical Plugin), a novel graphical software tool for graphically specifying spatial CAS systems with the feature of automatic translation into CARMA models. We also supply CARMA with additional syntax structures for expressing spatial constructs

    A Hybrid Parallel Algorithm for the 3-D Method of Characteristics Solution of the Boltzmann Transport Equation on High Performance Compute Clusters.

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    The focus of this thesis is on the development of a highly scalable parallel algorithm for solving the 3-D method of characteristics (MOC) form of the Boltzmann neutron transport equation. The derivation of the 3-D MOC method is presented first, along with the details of the discretization techniques, that utilize the concept of modular ray tracing. The implementation of these equations is then described, and then the approach to parallelizing the algorithm is discussed. Results are shown for a range of benchmark problems typically solved by 3-D neutron transport codes. The algorithm is parallelized in space, angle, and by characteristic rays, which is specific to the MOC solution method. Once the parallel algorithm is established, a performance model for the particular implementation is derived. This model contains detailed expressions for the number of floating point operations and execution time as a function of the problem size and fundamental computer hardware properties, such as the time per flop and cache access latency. The procedure for determining the hardware coefficients required by the performance model is then presented and validated using experimental results. The performance model is shown to agree well with experiment for both types of execution, and the model is therefore used for subsequent analyses that explore the algorithm's sensitivities to the computer and network hardware characteristics. The model is also analyzed to assess the scaling of the algorithm for a quarter core PWR. The optimization of the convergence of the parallel 3-D MOC algorithm through the use of the coarse mesh finite difference (CMFD) method is then developed. The CMFD accelerated parallel 3-D MOC algorithm is then used to compute solutions to several numerical benchmarks, that show good agreement with the reference results. Finally, the research performed in this thesis and its conclusions are summarized, and areas of future research are suggested.PHDNuclear Engineering & Radiological SciencesUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/100072/1/bkochuna_1.pd

    Fundamental Approaches to Software Engineering

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    This open access book constitutes the proceedings of the 25th International Conference on Fundamental Approaches to Software Engineering, FASE 2022, which was held during April 4-5, 2022, in Munich, Germany, as part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2022. The 17 regular papers presented in this volume were carefully reviewed and selected from 64 submissions. The proceedings also contain 3 contributions from the Test-Comp Competition. The papers deal with the foundations on which software engineering is built, including topics like software engineering as an engineering discipline, requirements engineering, software architectures, software quality, model-driven development, software processes, software evolution, AI-based software engineering, and the specification, design, and implementation of particular classes of systems, such as (self-)adaptive, collaborative, AI, embedded, distributed, mobile, pervasive, cyber-physical, or service-oriented applications

    Fundamental Approaches to Software Engineering

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    This open access book constitutes the proceedings of the 25th International Conference on Fundamental Approaches to Software Engineering, FASE 2022, which was held during April 4-5, 2022, in Munich, Germany, as part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2022. The 17 regular papers presented in this volume were carefully reviewed and selected from 64 submissions. The proceedings also contain 3 contributions from the Test-Comp Competition. The papers deal with the foundations on which software engineering is built, including topics like software engineering as an engineering discipline, requirements engineering, software architectures, software quality, model-driven development, software processes, software evolution, AI-based software engineering, and the specification, design, and implementation of particular classes of systems, such as (self-)adaptive, collaborative, AI, embedded, distributed, mobile, pervasive, cyber-physical, or service-oriented applications

    Evaluation of railway system performance under changing levels of automation using a simulation framework

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    Modern mainline railways are under constant pressure to meet the demands of higher capacity and to improve their punctuality. Railway system designers and operators are increasingly looking to use automation as tool to enable proactive strategies to optimise the timetable, improve the reliability of the infrastructure & rolling stock, to allow for a more dynamic command & control system which can respond to passenger demand and overall to linearize the response behaviour of the system under duress. In the first part of this thesis, I, the author, will discuss the development of automation over the years and the techniques that have been developed to analyse automation changes in a system. Further to this, I outline the various changes to the railway technology over the last century in brief. In the second part, I apply the techniques described earlier to design an automation framework to develop a grade of automation for the railway system to meet the demands of improved capacity and performance. Further to this, I develop parallel testable levels of automation using existing railway technology to demonstrate the effectiveness of a framework developed using the methodology discussed before. These levels are then tested on a network topology using micro-simulation to verify if they produce improved capacity and performance. In the final part, A case study is developed for the network from Kings Cross station to Welwyn Garden on the East Coast Main Line with the traffic dense branch line from Hertford north joining this line. The network is simulated under similar conditions to that adopted for the theoretical network and the results are compared with the previous outcomes. Results from the above studies have several significant outcomes. Firstly, the methodology developed over the course of this thesis can produce automation levels that are distinct from each other. Secondly, these simulation results show that there is a step change in the performance of the systems when organised into distinct levels of automation. Thirdly, and perhaps the most important conclusion from the studies, I show that automation of a single railway sub-system does not yield beneficial results unless there are complementary solutions produced for the surrounding sub-systems. In the theoretical phase of the study, the journey time calculations were repeated for 5000 iterations using a Quasi Monte Carlo framework. The results indicate a clear separation between each of the level and stages of automation proposed within the framework. The results from the simulation show that the reduction in journey times between the various levels can be as much as 5%. In the case study, the results were not as distinct but the overall trendlines indicate a reduction in journey times for both intercity and suburban services. Publications produced during the research period: • Venkateswaran, K., Nicholson, G., Chen, L. & Pelligrini, P. 2017. D3.3.2 Analysis of European best practices and levels of automation for traffic management under large disruptions In: IFFSTAR (ed.) Capacity for Rail. UIC. • Venkateswaran, K. G., Nicholson, G. L., Roberts, C. & Stone, R. Impact of Automation on the Capacity of a Mainline Railway: A Preliminary Hypothesis and Methodology. 2015 IEEE 18th International Conference on Intelligent Transportation Systems, pages 2097-2102

    Bibliography of Lewis Research Center technical publications announced in 1992

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    This compilation of abstracts describes and indexes the technical reporting that resulted from the scientific and engineering work performed and managed by the Lewis Research Center in 1992. All the publications were announced in the 1992 issues of STAR (Scientific and Technical Aerospace Reports) and/or IAA (International Aerospace Abstracts). Included are research reports, journal articles, conference presentations, patents and patent applications, and theses

    Performance and power management for multi-core processors

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    This dissertation addresses the problem of power and performance management for various computing systems, from single voltage island multicore processors to power constrained extreme scale cloud systems. Balancing power and performance in modern computing systems is a complex optimization problem. This challenge is addressed by the statement of this thesis: Improving performance and power consumption in modern computing systems will require new techniques, and the body of control theories can provide the basis for such solutions. This thesis developed dynamic models for throughput and power that adjust well to workload variations. Those models are general and can be applied to various kinds of computing frameworks. Based on those models, we use feedback controllers for throughput regulation and power regulation. The controllers are based on integrators for variable gain designed for stabilizing the closed-loop system as well as for rapidly responding to changing workload in short time frames. The feedback control is robust with respect to model uncertainties and computing errors in the loop, and they exhibit fast convergence despite such errors. This thesis addresses the performance and power management through three main contributions: 1. Effective and efficient power & performance management techniques in a single voltage island multi-core processor. 2. Maximizing power efficiency under a power cap in a multi-core processor that is composed of several voltage islands. 3. A hierarchical power management technique to improve performance and energy efficiency under power budgets in a cloud system.Ph.D
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