Articoli di riviste: "Computational grids (Computer systems)"

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Jie, Wei, Tianyi Zang, Terence Hung, Stephen J. Turner e Wentong Cai. "Information Management for Computational Grids". International Journal of Web Services Research 2, n. 3 (luglio 2005): 69–82. http://dx.doi.org/10.4018/jwsr.2005070103.

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Xu, Lin, Yong-Hong Tang, Wei Pu e Yang Han. "Hybrid electromechanical-electromagnetic simulation to SVC controller based on ADPSS platform". Journal of Energy in Southern Africa 25, n. 4 (19 dicembre 2014): 112–22. http://dx.doi.org/10.17159/2413-3051/2014/v25i4a2244.

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To test the dynamic performance and damping features of a static var compensator (SVC) controller accurately in large-scale interconnected AC/DC hybrid power systems, it is of vital significance to build the detailed electromagnetic transient model. However, it is unrealistic and time-consuming to build the detailed models of all the devices in the actual large-scale power grid. Utilizing the hybrid simulation function in the advanced digital power system simulator (ADPSS) and by dividing the large-scale power grid into the electromagnetic transient sub-grids and electromechanical sub-grids, the computation speed of real-time simulation is remarkably enhanced by the parallel computational capabilities of digital simulator. The SVC controller and the nearby substation are modelled in the electromagnetic transient sub-grid, and the residue sub-networks are modelled in the electromechanical sub-grid. This paper focuses on the mechanism of the hybrid electromechanical and electromagnetic simulation, the detailed modelling and the ADPSS-based digital closed-loop test methodologies of the SVC controller. Eventually, the validity and effectiveness of the modelling and control methods are confirmed by the experimental results.

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PREVE, NIKOLAOS P., e EMMANUEL N. PROTONOTARIOS. "MONTE CARLO SIMULATION ON COMPUTATIONAL FINANCE FOR GRID COMPUTING". International Journal of Modeling, Simulation, and Scientific Computing 03, n. 03 (17 maggio 2012): 1250010. http://dx.doi.org/10.1142/s1793962312500109.

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Monte Carlo methods are a class of computational algorithms that rely on repeated random sampling to compute their results. Monte Carlo methods are often used in simulating complex systems. Because of their reliance on repeated computation of random or pseudo-random numbers, these methods are most suited to calculation by a computer and tend to be used when it is infeasible or impossible to compute an exact result with a deterministic algorithm. In finance, Monte Carlo simulation method is used to calculate the value of companies, to evaluate economic investments and financial derivatives. On the other hand, Grid Computing applies heterogeneous computer resources of many geographically disperse computers in a network in order to solve a single problem that requires a great number of computer processing cycles or access to large amounts of data. In this paper, we have developed a simulation based on Monte Carlo method which is applied on grid computing in order to predict through complex calculations the future trends in stock prices.

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ARNOLD, DORIAN C., SATHISH S. VAHDIYAR e JACK J. DONGARRA. "ON THE CONVERGENCE OF COMPUTATIONAL AND DATA GRIDS". Parallel Processing Letters 11, n. 02n03 (giugno 2001): 187–202. http://dx.doi.org/10.1142/s012962640100052x.

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Great advances in high-performance computing have given rise to scientific applications that place large demands on software and hardware infrastructures for both computational and data services. With these trends the necessity has emerged for distributed systems developers that once distinguished between these elements to acknowledge that indeed computational and data services are tightly coupled and need to be addressed simultaneously. In this article, we compile and discuss several strategies and techniques, like co-scheduling and co-allocation of computational and data services, dynamic storage capabilities, and quality-of-service, that can be used to help resolve some of the aforementioned issues. We present our interactions with a distributed computing system, NetSolve, and a Distributed Storage Infrastructure, IBP, as a case study of how some of these techniques can be effectively deployed and offer experimental evidence from early prototypes that validate our motivation and direction.

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Huang, Sili, Eric Aubanel e Virendrakumar C. Bhavsar. "PaGrid: A Mesh Partitioner for Computational Grids". Journal of Grid Computing 4, n. 1 (1 febbraio 2006): 71–88. http://dx.doi.org/10.1007/s10723-005-9018-0.

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Darwish, M., H. Diab e F. Moukalled. "An Educational Two-Dimensional Interactive Dynamic Grid Generator". International Journal of Mechanical Engineering Education 24, n. 4 (ottobre 1996): 279–90. http://dx.doi.org/10.1177/030641909602400406.

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This paper describes IDGG, an Interactive Dynamic Grid Generator, for use as an educational tool by students studying computational fluid dynamics. The package is a Windows applications and runs on IBM PC, or compatible, computers. It is written in Pascal and built using object-oriented programming. The computer program allows the user to generate boundary-fitted curvilinear grids in any two-dimensional domain. The procedure adopted requires the user to perform the transformation step by step allowing him/her to easily grasp the concept of boundary-fitted coordinate systems. In addition, IDGG may be used by CFD researchers to display results graphically in the form of vector fields, contours, and two- and three-dimensional plots. The examples provided show the effectiveness of the package as a teaching aid.

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Röhlig, Martin, Ruby Kala Prakasam, Jörg Stüwe, Christoph Schmidt, Oliver Stachs e Heidrun Schumann. "Enhanced Grid-Based Visual Analysis of Retinal Layer Thickness with Optical Coherence Tomography". Information 10, n. 9 (23 agosto 2019): 266. http://dx.doi.org/10.3390/info10090266.

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Optical coherence tomography enables high-resolution 3D imaging of retinal layers in the human eye. The thickness of the layers is commonly assessed to understand a variety of retinal and systemic disorders. Yet, the thickness data are complex and currently need to be considerably reduced prior to further processing and analysis. This leads to a loss of information on localized variations in thickness, which is important for early detection of certain retinal diseases. We propose an enhanced grid-based reduction and exploration of retinal thickness data. Alternative grids are computed, their representation quality is rated, and best fitting grids for given thickness data are suggested. Selected grids are then visualized, adapted, and compared at different levels of granularity. A visual analysis tool bundles all computational, visual, and interactive means in a flexible user interface. We demonstrate the utility of our tool in a complementary analysis procedure, which eases the evaluation of ophthalmic study data. Ophthalmologists successfully applied our solution to study localized variations in thickness of retinal layers in patients with diabetes mellitus.

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Wei, Guiyi, Yun Ling, Athanasios V. Vasilakos, Bin Xiao e Yao Zheng. "PIVOT: An adaptive information discovery framework for computational grids". Information Sciences 180, n. 23 (dicembre 2010): 4543–56. http://dx.doi.org/10.1016/j.ins.2010.07.022.

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Jeong, Se-Min, e Chang-Yull Lee. "Weighted Moving Square-Based Solver for Unsteady Incompressible Laminar Flow Simulations". Applied Sciences 12, n. 7 (30 marzo 2022): 3519. http://dx.doi.org/10.3390/app12073519.

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For computational fluid dynamics simulations, grid systems are generally used in the Eulerian frame for both structured and unstructured grids and solvers designed for the chosen grid systems. In contrast to the grid-based method, in which the connection information with neighboring grids must be maintained, gridless methods do not require an underlying connectivity in the form of control volumes or elements. Hence, gridless methods are feasible and robust for the problems with moving boundary and/or complicated boundary shapes. In this study, a Eulerian gridless solver is proposed, and its application for simulating two-dimensional unsteady viscous flows in low Reynolds number regions is investigated. The solver utilizes the weighted moving square method to obtain the spatial derivatives of the governing equations and solve the pressure Poisson equation iteratively. Simple remedies to satisfy the boundary conditions in the finite difference method are applied. The fractional step method with the second-order Adams–Bashforth method is used for time integration. Some benchmark problems were solved using the developed solver, and the results were compared with those of other experimental and computational methods. Good agreement with the results of other methods confirmed the validity of the proposed solver.

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Rahman, Ashiqur Md, e Rashedur M. Rahman. "CAPM Indexed Hybrid E-Negotiation for Resource Allocation in Grid Computing". International Journal of Grid and High Performance Computing 5, n. 2 (aprile 2013): 72–91. http://dx.doi.org/10.4018/jghpc.2013040105.

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Computational Grids are a promising platform for executing large-scale resource intensive applications. This paper identifies challenges in managing resources in a Grid computing environment and proposes computational economy as a metaphor for effective management of resources and application scheduling. It identifies distributed resource management challenges and requirements of economy-based Grid systems, and proposes an economy based negotiation system protocol for cooperative and competitive trading of resources. Dynamic pricing for services and good level of Pareto optimality make auctions more attractive for resource allocation over other economic models. In a complex Grid environment, the communication demand can become a bottleneck; that is, a number of messages need to be exchanged for matching suitable service providers and consumers. The Fuzzy Trust integrated hybrid Capital Asset Pricing Model (CAPM) shows the higher user centric satisfaction and provides the equilibrium relationship between the expected return and risk on investments. This paper also presents an analysis on the communication requirements and the necessity of the CAPMAuction in Grid environment.

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Nurkanović, Armin, Amer Mešanović, Mario Sperl, Sebastian Albrecht, Ulrich Münz, Rolf Findeisen e Moritz Diehl. "Optimization-based primary and secondary control of microgrids". at - Automatisierungstechnik 68, n. 12 (18 novembre 2020): 1044–58. http://dx.doi.org/10.1515/auto-2020-0088.

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AbstractThis article discusses how to use optimization-based methods to efficiently operate microgrids with a large share of renewables. We discuss how to apply a frequency-based method to tune the droop parameters in order to stabilize the grid and improve oscillation damping after disturbances. Moreover, we propose a centralized real-time feasible nonlinear model predictive control (NMPC) scheme to achieve efficient frequency and voltage control while considering economic dispatch results. Centralized NMPC for secondary control is a computationaly challenging task. We demonstrate how to reduce the computational burden using the Advanced Step Real-Time Iteration with nonuniform discretization grids. This reduces the computational burden up to 60 % compared to a standard uniform approach, while having only a minor performance loss. All methods are validated on the example of a 9-bus microgrid, which is modeled with a complex differential algebraic equation.

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Gumen, Olena, Ganna Smakovska e Yuriy Maksуmenko. "THE USE OF NESTED ADAPTIVE GRIDS FOR MODELING HEAT TRANSFER PROCESSES IN INFORMATION AND CONTROL SYSTEMS OF COMPLEX EQUIPMENT SAMPLES". Collection of scientific works of Odesa Military Academy, n. 16 (11 febbraio 2022): 59–65. http://dx.doi.org/10.37129/2313-7509.2021.16.59-65.

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Modeling of processes on the use of adaptive grids for information and control systems of complex samples of equipment is offered. Application in the simulation of various natural phenomena and processes have obtained differential equations with partial derivatives. The principle of replacing the continuous domain of the unknown function by a discrete set of points (grid) is the basis of numerical methods for solving such equations. The complex solution of such problems is a definite scientific problem, the solution of which determines the accuracy of the numerical solution in areas where the gradient of the desired function reaches large values, significantly affects the accuracy of the solution throughout the region. The study considers the method of constructing nested adaptive difference grids for modeling heat transfer processes in information-control systems of complex samples of equipment, which are condensed in zones of rapid change of the desired function to solve two-dimensional nonstationary equation of thermal conductivity. Existing methods of constructing non-uniform grids before calculations, based on finding possible zones of high gradients are not effective in non-stationary problems, where these zones can change their position over time. The proposed algorithm for finding zones with significant gradients of the desired function in the process of the task analyzes the behavior of the function, controls the error and builds a time variable and a non-uniform difference grid. This significantly reduces the machine time required to solve problems with significant gradients in some areas of the computational domain. The solution of the problem for the main and nested grids can be performed in parallel, which will further reduce the time to solve when using multi-core systems. Keywords: computer model, finite difference method, difference mesh, nested mesh, modeling of heat transfer processes, information and control systems.

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Ma, Tianlong, Lin Zhang, Fujun Cao e Yongbin Ge. "A Special Multigrid Strategy on Non-Uniform Grids for Solving 3D Convection–Diffusion Problems with Boundary/Interior Layers". Symmetry 13, n. 7 (24 giugno 2021): 1123. http://dx.doi.org/10.3390/sym13071123.

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Boundary or interior layer problems of high-dimensional convection–diffusion equations have distinct asymmetry. Consequently, computational grid distributions and linear algebraic systems arising from finite difference schemes for them are also asymmetric. Numerical solutions for these kinds of problems are more complicated than those symmetric problems. In this paper, we extended our previous work on the partial semi-coarsening multigrid method combined with the high-order compact (HOC) difference scheme for solving the two-dimensional (2D) convection–diffusion problems on non-uniform grids to the three-dimensional (3D) cases. The main merit of the present method is that the multigrid method on non-uniform grids can be performed with a different number of grids in different coordinate axes, which is more efficient than the multigrid method on non-uniform grids with the same number of grids in different coordinate axes. Numerical experiments are carried out to validate the accuracy and efficiency of the present method. It is shown that, without losing the high precision, the present method is very effective to reduce computing cost by cutting down the number of grids in the direction(s) which does/do not contain boundary or interior layer(s).

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Morozov, Alexander Yu, Andrey A. Zhuravlev e Dmitry L. Reviznikov. "Sparse Grid Adaptive Interpolation in Problems of Modeling Dynamic Systems with Interval Parameters". Mathematics 9, n. 4 (3 febbraio 2021): 298. http://dx.doi.org/10.3390/math9040298.

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The paper is concerned with the issues of modeling dynamic systems with interval parameters. In previous works, the authors proposed an adaptive interpolation algorithm for solving interval problems; the essence of the algorithm is the dynamic construction of a piecewise polynomial function that interpolates the solution of the problem with a given accuracy. The main problem of applying the algorithm is related to the curse of dimension, i.e., exponential complexity relative to the number of interval uncertainties in parameters. The main objective of this work is to apply the previously proposed adaptive interpolation algorithm to dynamic systems with a large number of interval parameters. In order to reduce the computational complexity of the algorithm, the authors propose using adaptive sparse grids. This article introduces a novelty approach of applying sparse grids to problems with interval uncertainties. The efficiency of the proposed approach has been demonstrated on representative interval problems of nonlinear dynamics and computational materials science.

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Savyanavar, Amit Sadanand, e Vijay Ram Ghorpade. "Application Checkpointing Technique for Self-Healing From Failures in Mobile Grid Computing". International Journal of Grid and High Performance Computing 11, n. 2 (aprile 2019): 50–62. http://dx.doi.org/10.4018/ijghpc.2019040103.

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A mobile grid (MG) consists of interconnected mobile devices which are used for high performance computing. Fault tolerance is an important property of mobile computational grid systems for achieving superior arrangement reliability and faster recovery from failures. Since the failure of the resources affects task execution fatally, fault tolerance service is essential to achieve QoS requirement in MG. The faults which occur in MG are link failure, node failure, task failure, limited bandwidth etc. Detecting these failures can help in better utilisation of the resources and timely notification to the user in a MG environment. These failures result in loss of computational results and data. Many algorithms or techniques were proposed for failure handling in traditional grids. The authors propose a checkpointing based failure handling technique which will improve arrangement reliability and failure recovery time for the MG network. Experimentation was conducted by creating a grid of ubiquitously available Android-based mobile phones.

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Ganzha, Victor G., e Evgenii V. Vorozhtsov. "Application of Computer Algebra Systems for Stability Analysis of Difference Schemes on Curvilinear Grids". Journal of Symbolic Computation 28, n. 3 (settembre 1999): 401–33. http://dx.doi.org/10.1006/jsco.1999.0289.

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José da Silva, Diego, Edmarcio Antonio Belati e Eduardo Werley Silva dos Angelos. "FPAES: A Hybrid Approach for the Optimal Placement and Sizing of Reactive Compensation in Distribution Grids". Energies 13, n. 23 (4 dicembre 2020): 6409. http://dx.doi.org/10.3390/en13236409.

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Reactive power compensation with Capacitor Banks (CBs) is one of the most successful approaches used in distribution systems, mainly due to their versatility, long-term acceptance in the power industry, and reduced costs. Most allocation methods, however, lack specific strategies to handle the limited discrete nature of CBs sizes seeking to improve the overall optimization and computational performance. We present an algorithm for the Optimal Placement of Capacitor Banks (OPCB) in distribution systems by means of a hybrid Flower Pollination Algorithm (FPA)–Exhaustive Search (ES) approach. The pollination process itself determines the sets of buses for placement, while CBs sizes and the final fitness values of each pollen are selected after a full-search is conducted in the sizing space. As the sizing phase works on the limited search space of predetermined discrete bank values, the computational effort to find the optimum CB capacity is greatly reduced. Tests were performed on distribution systems of 10, 34, and 85 buses with respect to the objective function, final losses, and voltage profile. The algorithm offers an excellent compromise between solution quality and computational effort, when compared to similar approaches.

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Zeng, Fancheng, Guanqiu Qi, Zhiqin Zhu, Jian Sun, Gang Hu e Matthew Haner. "Convex Neural Networks Based Reinforcement Learning for Load Frequency Control under Denial of Service Attacks". Algorithms 15, n. 2 (23 gennaio 2022): 34. http://dx.doi.org/10.3390/a15020034.

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With the increase in the complexity and informatization of power grids, new challenges, such as access to a large number of distributed energy sources and cyber attacks on power grid control systems, are brought to load-frequency control. As load-frequency control methods, both aggregated distributed energy sources (ADES) and artificial intelligence techniques provide flexible solution strategies to mitigate the frequency deviation of power grids. This paper proposes a load-frequency control strategy of ADES-based reinforcement learning under the consideration of reducing the impact of denial of service (DoS) attacks. Reinforcement learning is used to evaluate the pros and cons of the proposed frequency control strategy. The entire evaluation process is realized by the approximation of convex neural networks. Convex neural networks are used to convert the nonlinear optimization problems of reinforcement learning for long-term performance into the corresponding convex optimization problems. Thus, the local optimum is avoided, the optimization process of the strategy utility function is accelerated, and the response ability of controllers is improved. The stability of power grids and the convergence of convex neural networks under the proposed frequency control strategy are studied by constructing Lyapunov functions to obtain the sufficient conditions for the steady states of ADES and the weight convergence of actor–critic networks. The article uses the IEEE14, IEEE57, and IEEE118 bus testing systems to verify the proposed strategy. Our experimental results confirm that the proposed frequency control strategy can effectively reduce the frequency deviation of power grids under DoS attacks.

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Collignon, Tijmen, e Martin Van Gijzen. "Two implementations of the preconditioned conjugate gradient method on heterogeneous computing grids". International Journal of Applied Mathematics and Computer Science 20, n. 1 (1 marzo 2010): 109–21. http://dx.doi.org/10.2478/v10006-010-0008-4.

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Two implementations of the preconditioned conjugate gradient method on heterogeneous computing gridsEfficient iterative solution of large linear systems on grid computers is a complex problem. The induced heterogeneity and volatile nature of the aggregated computational resources present numerous algorithmic challenges. This paper describes a case study regarding iterative solution of large sparse linear systems on grid computers within the software constraints of the grid middleware GridSolve and within the algorithmic constraints of preconditioned Conjugate Gradient (CG) type methods. We identify the various bottlenecks induced by the middleware and the iterative algorithm. We consider the standard CG algorithm of Hestenes and Stiefel, and as an alternative the Chronopoulos/Gear variant, a formulation that is potentially better suited for grid computing since it requires only one synchronisation point per iteration, instead of two for standard CG. In addition, we improve the computation-to-communication ratio by maximising the work in the preconditioner. In addition to these algorithmic improvements, we also try to minimise the communication overhead within the communication model currently used by the GridSolve middleware. We present numerical experiments on 3D bubbly flow problems using heterogeneous computing hardware that show lower computing times and better speed-up for the Chronopoulos/Gear variant of conjugate gradients. Finally, we suggest extensions to both the iterative algorithm and the middleware for improving granularity.

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Kołodziej, Joanna, e Fatos Xhafa. "Modern approaches to modeling user requirements on resource and task allocation in hierarchical computational grids". International Journal of Applied Mathematics and Computer Science 21, n. 2 (1 giugno 2011): 243–57. http://dx.doi.org/10.2478/v10006-011-0018-x.

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Modern approaches to modeling user requirements on resource and task allocation in hierarchical computational grids Tasks scheduling and resource allocation are among crucial issues in any large scale distributed system, including Computational Grids (CGs). These issues are commonly investigated using traditional computational models and resolution methods that yield near-optimal scheduling strategies. One drawback of such approaches is that they cannot effectively tackle the complex nature of CGs. On the one hand, such systems account for many administrative domains with their own access policies, user privileges, etc. On the other, CGs have hierarchical nature and therefore any computational model should be able to effectively express the hierarchical architecture in the optimization model. Recently, researchers have been investigating the use of game theory for modeling user requirements regarding task and resource allocation in grid scheduling problems. In this paper we present two general non-cooperative game approaches, namely, the symmetric non-zero sum game and the asymmetric Stackelberg game for modeling grid user behavior defined as user requirements. In our game-theoretic approaches we are able to cast new requirements arising in allocation problems, such as asymmetric users relations, security and reliability restrictions in CGs. For solving the games, we designed and implemented GA-based hybrid schedulers for approximating the equilibrium points for both games. The proposed hybrid resolution methods are experimentally evaluated through the grid simulator under heterogeneity, and large-scale and dynamics conditions. The relative performance of the schedulers is measured in terms of the makespan and flowtime metrics. The experimental analysis showed high efficiency of meta-heuristics in solving the game-based models, especially in the case of an additional cost of secure task scheduling to be paid by the users.

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Wang, Lizhe, Dan Chen, Ze Deng e Fang Huang. "Large scale distributed visualization on computational Grids: A review". Computers & Electrical Engineering 37, n. 4 (luglio 2011): 403–16. http://dx.doi.org/10.1016/j.compeleceng.2011.05.010.

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Tafani, Daniele, Burak Kantarci, Hussein T. Mouftah, Conor McArdle e Liam P. Barry. "A distributed framework for energy-efficient lightpaths in computational grids". Journal of High Speed Networks 19, n. 1 (2013): 1–18. http://dx.doi.org/10.3233/jhs-130457.

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Chen, Uei-Ren, e Woei Lin. "Aligning block permutation methods for topology transformation on computational grids". Journal of Supercomputing 61, n. 3 (21 aprile 2011): 545–59. http://dx.doi.org/10.1007/s11227-011-0613-5.

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Aziz, Abdul, e Hesham El-Rewini. "Power efficient scheduling heuristics for energy conservation in computational grids". Journal of Supercomputing 57, n. 1 (3 febbraio 2011): 65–80. http://dx.doi.org/10.1007/s11227-011-0559-7.

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Nikitina, Alla, Alyona Filinа, Vladimir Litvinov e Asya Atayan. "Development of a specialized software complex for modeling the biogeochemical cycles in the Azov sea, including calculation modules of transformation of phosphorus, nitrogen, silicon, sulfur and dissolved oxygen forms, as well as the dynamics of phyto-and zooplatonkton". E3S Web of Conferences 363 (2022): 02023. http://dx.doi.org/10.1051/e3sconf/202236302023.

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The paper is devoted to the development of a software complex for predictive modeling of biogeochemical cycles in the Azov Sea on high-performance computer systems in a limited time. The complex development includes the creation of software modules of the computational structure to calculate the concentrations of phosphorus, nitrogen, silicon, sulfur, dissolved oxygen forms and describe in detail phyto- and zooplankton dynamics in the Azov Sea; the integration of various environmental databases, satellite monitoring. The complex is adapted to solve a wide class of predictive problems of water ecology and water resources management. It includes the implementation of developed 3D mathematical model of hydrophysics and biological kinetics on computational grids, consistent with the complex shape of the water coastline. Parallel algorithms have been developed for numerical implementation of water ecology problems, oriented to high-performance computer systems. To increase the calculation efficiency of computational grid fragments assigned to graphics accelerators, an algorithm and its software implementation were developed in the CUDA C language. Based on the developed specialized software tools focused on supercomputers, scenarios for the development of the environmental situation and sustainable development management at biological rehabilitation of the Azov Sea were developed, including forecasts of changes in harmful algae concentration; dynamics of spatial interaction processes between phyto- and zooplankton populations; evolution of biological kinetics processes on the example of plankton interaction.

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Mo, Tiexiang, e Guodong Li. "Parallel Accelerated Fifth-Order WENO Scheme-Based Pipeline Transient Flow Solution Model". Applied Sciences 12, n. 14 (21 luglio 2022): 7350. http://dx.doi.org/10.3390/app12147350.

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The water hammer phenomenon is the main problem in long-distance pipeline networks. The MOC (Method of characteristics) and finite difference methods lead to severe constraints on the mesh and Courant number, while the finite volume method of the second-order Godunov scheme has limited intermittent capture capability. These methods will produce severe numerical dissipation, affecting the computational efficiency at low Courant numbers. Based on the lax-Friedrichs flux splitting method, combined with the upstream and downstream virtual grid boundary conditions, this paper uses the high-precision fifth-order WENO scheme to reconstruct the interface flux and establishes a finite volume numerical model for solving the transient flow in the pipeline. The model adopts the GPU parallel acceleration technology to improve the program’s computational efficiency. The results show that the model maintains the excellent performance of intermittent excitation capture without spurious oscillations even at a low Courant number. Simultaneously, the model has a high degree of flexibility in meshing due to the high insensitivity to the Courant number. The number of grids in the model can be significantly reduced and higher computational efficiency can be obtained compared with MOC and the second-order Godunov scheme. Furthermore, this paper analyzes the acceleration effect in different grids. Accordingly, the acceleration effect of the GPU technique increases significantly with the increase in the number of computational grids. This model can support efficient and accurate fast simulation and prediction of non-constant transient processes in long-distance water pipeline systems.

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Pierce, Marlon E. "Special Issue Editorial Introduction: Grids and Geospatial Information Systems". Concurrency and Computation: Practice and Experience 20, n. 14 (25 settembre 2008): 1611–15. http://dx.doi.org/10.1002/cpe.1381.

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Gundy-Burlet, K. L., M. M. Rai, R. C. Stauter e R. P. Dring. "Temporally and Spatially Resolved Flow in a Two-Stage Axial Compressor: Part 2—Computational Assessment". Journal of Turbomachinery 113, n. 2 (1 aprile 1991): 227–32. http://dx.doi.org/10.1115/1.2929090.

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Fluid dynamics of turbomachines are complicated because of aerodynamic interactions between rotors and stators. It is necessary to understand the aerodynamics associated with these interactions in order to design turbomachines that are both light and compact as well as reliable and efficient. The current study uses an unsteady, thin-layer Navier–Stokes zonal approach to investigate the unsteady aerodynamics of a multistage compressor. Relative motion between rotors and stators is made possible by the use of systems of patched and overlaid grids. Results have been computed for a 2 1/2-stage compressor configuration. The numerical data compare well with experimental data for surface pressures and wakes. In addition, the effect of grid refinement on the solution is studied.

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Chmaj, Grzegorz, Krzysztof Walkowiak, Michał Tarnawski e Michał Kucharzak. "Heuristic algorithms for optimization of task allocation and result distribution in peer-to-peer computing systems". International Journal of Applied Mathematics and Computer Science 22, n. 3 (1 settembre 2012): 733–48. http://dx.doi.org/10.2478/v10006-012-0055-0.

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Abstract Recently, distributed computing system have been gaining much attention due to a growing demand for various kinds of effective computations in both industry and academia. In this paper, we focus on Peer-to-Peer (P2P) computing systems, also called public-resource computing systems or global computing systems. P2P computing systems, contrary to grids, use personal computers and other relatively simple electronic equipment (e.g., the PlayStation console) to process sophisticated computational projects. A significant example of the P2P computing idea is the BOINC (Berkeley Open Infrastructure for Network Computing) project. To improve the performance of the computing system, we propose to use the P2P approach to distribute results of computational projects, i.e., results are transmitted in the system like in P2P file sharing systems (e.g., BitTorrent). In this work, we concentrate on offline optimization of the P2P computing system including two elements: scheduling of computations and data distribution. The objective is to minimize the system OPEX cost related to data processing and data transmission. We formulate an Integer Linear Problem (ILP) to model the system and apply this formulation to obtain optimal results using the CPLEX solver. Next, we propose two heuristic algorithms that provide results very

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Deese, Anthony S., e Chika O. Nwankpa. "Utilization of FPAA Technology for Emulation of Multiscale Power System Dynamics in Smart Grids". IEEE Transactions on Smart Grid 2, n. 2 (dicembre 2011): 606–14. http://dx.doi.org/10.1109/tsg.2011.2161782.

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In this paper, the authors address computational issues associated with implementation of VLSI technologies-specifically, the utilization of field programmable analog array (FPAA) technology to analyze the steady-state as well dynamic behavior of nonlinear, multiscale power systems. Emphasis is placed on the following issues: adaptation of FPAA hardware for power flow analyses, design and construction of physical prototype, optimal hardware scaling, and application of emulation to transient fault analyses.

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Ciller, Pedro, Sara Lumbreras e Andrés González-García. "Network Cost Estimation for Mini-Grids in Large-Scale Rural Electrification Planning". Energies 14, n. 21 (5 novembre 2021): 7382. http://dx.doi.org/10.3390/en14217382.

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Universal access to electricity is a crucial challenge in many developing countries. Establishing the electrification agenda of an underserved region is a complicated task where computer models play a critical role in calculating geospatial plans that efficiently allocate resources. Such plans should include—among other things—reasonable estimations of the designs and economic costs of standalone systems, mini-grids, and grid extensions. This implies that computer models need to estimate the network cost for many potential mini-grids. To that end, most planning tools apply quick rules of thumb or geometric methods that ignore power flows and electric constraints, which play a significant role in network designs. This paper presents a methodology that rapidly estimates any low-voltage mini-grid network cost without neglecting the impact of electrical feasibility in such cost. We present a case study where we evaluate our method in terms of accuracy and computation time. We also compare our method with a quick estimation similar to the ones most regional planning tools apply, showing the effectiveness of our method.

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De Sarkar, Ajanta, Sarbani Roy, Dibyajyoti Ghosh, Rupam Mukhopadhyay e Nandini Mukherjee. "An Adaptive Execution Scheme for Achieving Guaranteed Performance in Computational Grids". Journal of Grid Computing 8, n. 1 (28 maggio 2009): 109–31. http://dx.doi.org/10.1007/s10723-009-9120-9.

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Shen, Zhanfeng, Jiancheng Luo, Chenghu Zhou, Guangyu Huang, Weifeng Ma e Dongping Ming. "System design and implementation of digital-image processing using computational grids". Computers & Geosciences 31, n. 5 (giugno 2005): 619–30. http://dx.doi.org/10.1016/j.cageo.2004.11.014.

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Altameem, T., e M. Amoon. "An agent-based approach for dynamic adjustment of scheduled jobs in computational grids". Journal of Computer and Systems Sciences International 49, n. 5 (ottobre 2010): 765–72. http://dx.doi.org/10.1134/s1064230710050114.

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Hu, Chunqiang, Hang Liu, Liran Ma, Yan Huo, Arwa Alrawais, Xiuhua Li, Hong Li e Qingyu Xiong. "A Secure and Scalable Data Communication Scheme in Smart Grids". Wireless Communications and Mobile Computing 2018 (2018): 1–17. http://dx.doi.org/10.1155/2018/5816765.

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The concept of smart grid gained tremendous attention among researchers and utility providers in recent years. How to establish a secure communication among smart meters, utility companies, and the service providers is a challenging issue. In this paper, we present a communication architecture for smart grids and propose a scheme to guarantee the security and privacy of data communications among smart meters, utility companies, and data repositories by employing decentralized attribute based encryption. The architecture is highly scalable, which employs an access control Linear Secret Sharing Scheme (LSSS) matrix to achieve a role-based access control. The security analysis demonstrated that the scheme ensures security and privacy. The performance analysis shows that the scheme is efficient in terms of computational cost.

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Sarhan, Amany, Ahmed I. Saleh e Amr M. Hamed. "A reliable-adaptive scheduler for computational grids with failure recovery and rescheduling mechanisms". International Journal of Grid and Utility Computing 2, n. 1 (2011): 59. http://dx.doi.org/10.1504/ijguc.2011.039981.

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DU, LIU-GE, KANG LI, FAN-MIN KONG e YUAN HU. "PARALLEL 3D FINITE-DIFFERENCE TIME-DOMAIN METHOD ON MULTI-GPU SYSTEMS". International Journal of Modern Physics C 22, n. 02 (febbraio 2011): 107–21. http://dx.doi.org/10.1142/s012918311101618x.

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Finite-difference time-domain (FDTD) is a popular but computational intensive method to solve Maxwell's equations for electrical and optical devices simulation. This paper presents implementations of three-dimensional FDTD with convolutional perfect match layer (CPML) absorbing boundary conditions on graphics processing unit (GPU). Electromagnetic fields in Yee cells are calculated in parallel millions of threads arranged as a grid of blocks with compute unified device architecture (CUDA) programming model and considerable speedup factors are obtained versus sequential CPU code. We extend the parallel algorithm to multiple GPUs in order to solve electrically large structures. Asynchronous memory copy scheme is used in data exchange procedure to improve the computation efficiency. We successfully use this technique to simulate pointwise source radiation and validate the result by comparison to high precision computation, which shows favorable agreements. With four commodity GTX295 graphics cards on a single personal computer, more than 4000 million Yee cells can be updated in one second, which is hundreds of times faster than traditional CPU computation.

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Shah, Sayed Chhattan, e Myong Soon Park. "An Energy-Efficient Resource Allocation Scheme for Mobile Ad Hoc Computational Grids". Journal of Grid Computing 9, n. 3 (16 aprile 2011): 303–23. http://dx.doi.org/10.1007/s10723-011-9188-x.

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Liang, Feng, Yunzhen Liu, Hai Liu, Shilong Ma e Bettina Schnor. "A Parallel Job Execution Time Estimation Approach Based on User Submission Patterns within Computational Grids". International Journal of Parallel Programming 43, n. 3 (12 novembre 2013): 440–54. http://dx.doi.org/10.1007/s10766-013-0294-1.

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Bhushan, Shanti, Pablo Carrica, Jianming Yang e Frederick Stern. "Scalability studies and large grid computations for surface combatant using CFDShip-Iowa". International Journal of High Performance Computing Applications 25, n. 4 (22 febbraio 2011): 466–87. http://dx.doi.org/10.1177/1094342010394887.

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Scalability studies and computations using the largest grids to date for free-surface flows are performed using message-passing interface (MPI)-based CFDShip-Iowa toolbox curvilinear (V4) and Cartesian (V6) grid solvers on Navy high-performance computing systems. Both solvers show good strong scalability up to 2048 processors, with V6 showing somewhat better performance than V4. V6 also outperforms V4 in terms of the memory requirements and central processing unit (CPU) time per time-step per grid point. The explicit solvers show better scalability than the implicit solvers, but the latter allows larger time-step sizes, resulting in a lower total CPU time. The multi-grid HYPRE solver shows better scalability than the portable, extensible toolkit for scientific computation solver. The main scalability bottleneck is identified to be the pressure Poisson solver. The memory bandwidth test suggests that further scalability improvements could be obtained by using hybrid MPI/open multi-processing (OpenMP) parallelization. V4-detached eddy simulation (DES) on a 300 M grid for the surface combatant model DTMB 5415 in the straight-ahead condition provides a plausible description of the vortical structures and mean flow patterns observed in the experiments. However, the vortex strengths are over predicted and the turbulence is not resolved. V4-DESs on up to 250 M grids for DTMB 5415 at 20° static drift angle significantly improve the forces and moment predictions compared to the coarse grid unsteady Reynolds averaged Navier–Stokes, due to the improved resolved turbulence predictions. The simulations provide detailed resolution of the free-surface and breaking pattern and vortical and turbulent structures, which will guide planned experiments. V6 simulations on up to 276 M grids for DTMB 5415 in the straight-ahead condition predict diffused vortical structures due to poor wall-layer predictions. This could be due to the limitations of the wall-function implementation for the immersed boundary method.

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Venetis, Ioannis E., Vasso Saltogianni, Stathis Stiros e Efstratios Gallopoulos. "Multivariable inversion using exhaustive grid search and high-performance GPU processing: a new perspective". Geophysical Journal International 221, n. 2 (23 gennaio 2020): 905–27. http://dx.doi.org/10.1093/gji/ggaa042.

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SUMMARY Exhaustive searches in regular grids is a traditional and effective method for inversion, that is numerical solution of systems of non-linear equations which cannot be solved using formal algebraic techniques. However, this technique is effective for very few (3–4) variables and is slow. Recently, the first limitation was to a major degree overpassed with the new TOPological INVersion (TOPINV) algorithm which was used for inversion of systems with up to 18, or even more unknown variables. The novelty of this algorithm is that it is not based on the principle of the mean minimum misfit (cost function) between observations and model predictions, used by most inversion techniques. The new algorithm investigates for each gridpoint whether misfits of each observation are within specified uncertainty intervals, and stores clusters of ‘successful’ gridpoints in matrix form. These clusters (ensembles, sets) of gridpoints are tested whether they satisfy certain criteria and are then used to compute one or more optimal statistical solutions. The new algorithm is efficient for highly non-linear problems with high measurement uncertainties (low signal-to-noise ratio, SNR) and poor distribution of observations, that is problems leading to complicated 3-D mean misfit surfaces without dominant peaks, but it is slow when running in common computers. To overcome this limitation, we used GPUs which permit parallel processing in common computers, but faced another computational problem: GPU parallel processing supports only up to three dimensions. To solve this problem, we used CUDA programming and optimized the distribution of the computational load to all GPU cores. This leads up to 100x speedup relative to common CPU processing, as is derived from comparative tests with synthetic data for two typical inversion geophysical problems with up to 18 unknown variables, Mogi magma source modeling and elastic dislocation modeling of seismic faults. This impressive speedup makes the GPU/CUDA implementation of TOPINV practical even for low-latency solution of certain geophysical problems. This speedup in calculations also permitted to investigate the performance of the new algorithm in relation to the density of the adopted grids. We focused on a typical problem of elastic dislocation in unfavorable conditions (poor observations geometry, data with low SNR) and on synthetic observations with noise, so that the difference of each solution from the ‘true’/reference value was known (accuracy-based approach). Application of the algorithm revealed stable, accurate and precise solutions, with quality increasing with the grid density. Solution defects (bias), mainly produced by very coarse grids, can be identified through specific diagnostic criteria, dictating finer search grids.

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Zhang, Y., M. Li e G. R. Liu. "A Fourier Transform Analysis of Convergence Properties of Multigrid V-Cycle Algorithm". International Journal of Computational Methods 16, n. 04 (13 maggio 2019): 1844010. http://dx.doi.org/10.1142/s0219876218440103.

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This paper aims to provide an insight on the mechanism for the fast convergence of multigrid (MG) V-cycle algorithms. With this goal, the Fourier transform analysis is implemented to compute quantitatively the frequency spectrum of components of the residual resulted from the MG iterations. MG method has been extensively employed to solve large-scale systems of algebraic equations. Hence, one needs to understand its fast convergence property and scalability mechanism before applying MG method to a system equation, which affects the computational efficiency directly. In a first step, a number of novel features of the MG algorithm are studied, including the relationships among the iteration numbers needed for converged solutions, condition number of the system matrix and the grid-spacing in this paper. In a second step, the complexity of the MG method is researched, and various numerical experiments have been conducted in solving algebraic equations of models in finite element method for both heat transfer problems and solid mechanics problems. It is found that if the number of iterations in different grids is fixed, the optimal iteration mode is determined according to the attenuation of the high-frequency and low-frequency components of the residual. Our results also show that the complexity of the MG method is close to [Formula: see text], meaning that it is a close-to-linear scalable solver, which echoes the findings given by other literature. This study has revealed an important insight that the linear scalability is achieved by mitigating the negative effects (stagnation in convergence) of the large condition number of the system matrix created on the finest grid, using a sequence of coarser grids with smaller and smaller condition numbers.

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Puzyrkov, Dmitry, Sergey Polyakov, Viktoriia Podryga e Sergey Markizov. "Concept of a Cloud Service for Data Preparation and Computational Control on Custom HPC Systems in Application to Molecular Dynamics". EPJ Web of Conferences 173 (2018): 05014. http://dx.doi.org/10.1051/epjconf/201817305014.

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At the present stage of computer technology development it is possible to study the properties and processes in complex systems at molecular and even atomic levels, for example, by means of molecular dynamics methods. The most interesting are problems related with the study of complex processes under real physical conditions. Solving such problems requires the use of high performance computing systems of various types, for example, GRID systems and HPC clusters. Considering the time consuming computational tasks, the need arises of software for automatic and unified monitoring of such computations. A complex computational task can be performed over different HPC systems. It requires output data synchronization between the storage chosen by a scientist and the HPC system used for computations. The design of the computational domain is also quite a problem. It requires complex software tools and algorithms for proper atomistic data generation on HPC systems. The paper describes the prototype of a cloud service, intended for design of atomistic systems of large volume for further detailed molecular dynamic calculations and computational management for this calculations, and presents the part of its concept aimed at initial data generation on the HPC systems.

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Møyner, Olav, e Hamdi A. Tchelepi. "A Mass-Conservative Sequential Implicit Multiscale Method for Isothermal Equation-of-State Compositional Problems". SPE Journal 23, n. 06 (10 settembre 2018): 2376–93. http://dx.doi.org/10.2118/182679-pa.

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Summary Compositional simulation is necessary for a wide variety of reservoir-simulation applications, and it is especially valuable for accurate modeling of near-miscible gas injection for enhanced oil recovery. Because the nonlinear behavior of gas injection is sensitive to the resolution of the simulation grid used, it is important to use a fine grid to accurately resolve the compositional and saturation gradients. Compositional simulation of highly detailed reservoir models entails the use of small timesteps and large, poorly conditioned linear systems. The high computational cost of solving such systems renders field-scale simulations practically unfeasible. The coupling of the flow and transport to the phase-equilibrium calculations adds to the challenge. This is especially the case for near-miscible gas injection, in which the phase state and the phase compositions are very strong functions of space and time. We present a multiscale solver for compositional displacements with three-phase fluid flow. The thermodynamic phase behavior is described by general nonlinear cubic equations of state (EOS). The fully implicit (FI) natural-variables formulation is used as the basis to derive a sequential implicit (SI) solution strategy, whereby the pressure field is decoupled from the multicomponent transport. The SI scheme is mass conservative without the need to iterate between the pressure and transport equations during the timestep. This conservation property allows the errors caused by fixing the total-velocity field between the pressure- and transport-updating steps to be represented as a volume error. The method computes approximate pressure solutions—within a prescribed residual tolerance—that yield conservative fluxes on the computational grid of interest (fine, coarse, or intermediate). We use basis functions computed using restricted smoothing to allow for generally unstructured grids. The new method is verified against existing research and commercial compositional simulators using a simple conceptual test case and also using more-complex cases represented on both unstructured and corner-point grids with strong heterogeneity, faults, and pinched-out and eroded cells. The SI method and the implementation described here represent the first demonstrated multiscale method applicable to general compositional problems with complexity relevant for industrial-reservoir simulation.

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Hegde, Sujay N., H. K. Krishnappa, M. A. Rajan e Srinivas D B. "An efficient greedy task scheduling algorithm for heterogeneous inter-dependent tasks on computational grids". International Journal of Grid and Utility Computing 1, n. 1 (2020): 1. http://dx.doi.org/10.1504/ijguc.2020.10026377.

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Srinivas, D. B., Sujay N. Hegde, M. A. Rajan e H. K. Krishnappa. "An efficient greedy task scheduling algorithm for heterogeneous inter-dependent tasks on computational grids". International Journal of Grid and Utility Computing 11, n. 5 (2020): 587. http://dx.doi.org/10.1504/ijguc.2020.110059.

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PANCAKE, CHERRI M. "USABILITY ISSUES IN DEVELOPING TOOLS FOR THE GRID — AND HOW VISUAL REPRESENTATIONS CAN HELP". Parallel Processing Letters 13, n. 02 (giugno 2003): 189–206. http://dx.doi.org/10.1142/s0129626403001239.

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Initial tools developed for grid administrators and users have built on the technology and representational techniques of large parallel systems. Like their predecessors, grid tools must cope with extreme variations in scale, rapidly evolving hardware and software environments, and the competing demands of operating systems and middleware. Computational grids present several unique challenges, however, that go well beyond the lessons we have learned from parallel and distributed tools: the volatile nature of grid resources, their extreme heterogeneity, and the lack of coordinated management. Because they define a new and unfamiliar computing environment, there is a significant human challenge as well. Grid users will be extremely diverse, including resource providers, resource managers, users of data and derived data products, etc., as well as application developers. The future usability of the grid will depend on how well grid tools can capture information on grid resources and synthesize a higher-level perspective that helps users make sense of this complex new environment. This article identifies the tool requirements that will have most impact on the usability. It then explores recent advances in information visualization, demonstrating that many of the techniques grid tools will need already exist in preliminary form. A series of examples illustrates how those techniques can be applied to portray grid landscapes (graphical representations of grid resources, activities, behavior, costs, etc.) in useful and meaningful ways.

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Li, Xiaodong, e Zheng Xu. "Enhanced Efficient EMT-Type Model of the MMCs Based on Arm Equivalence". Applied Sciences 10, n. 23 (26 novembre 2020): 8421. http://dx.doi.org/10.3390/app10238421.

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The large number of switching elements in modular multilevel converters (MMCs) contribute a tremendous computational burden for electromagnetic transient (EMT) simulation programs. Detailed equivalent models (DEMs) and average value model (AVMs) are currently two major types of accurate and efficient model. However, the DEMs are still computationally inefficient for the simulation scenarios in large-scale MMC based high-voltage direct current (MMC-HVDC) grids, as the models represent all submodule (SMs) switching events, and memorize all individual capacitor voltages. Though the AVMs provide a faster simulation speed by using a single equivalent capacitor on the DC side, they have a relatively low simulation accuracy compared to DEMs, especially under blocked mode. This paper proposes an enhanced computationally efficient model based on arm equivalence (AEM), which can accurately represent the dynamic behaviors in both de-blocked and blocked modes. Compared to the DEMs, the proposed AEM is more efficient, with no loss of accuracy, and the simulation speed is irrespective of the SM number. The accuracy and computational efficiency of the proposed model were validated against the DEM and AVM through several simulation scenarios in a two-terminal MMC-HVDC system on the power systems computer aided design/ electromagnetic transient in DC system (PSCAD/EMTDC) program.

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Caron, Eddy, Frédéric Desprez e Cédric Tedeschi. "Enhancing Computational Grids with Peer-to-Peer Technology for Large Scale Service Discovery". Journal of Grid Computing 5, n. 3 (22 dicembre 2006): 337–60. http://dx.doi.org/10.1007/s10723-006-9058-0.

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Hupfeld, Felix, Toni Cortes, Björn Kolbeck, Jan Stender, Erich Focht, Matthias Hess, Jesus Malo, Jonathan Marti e Eugenio Cesario. "The XtreemFS architecture-a case for object-based file systems in Grids". Concurrency and Computation: Practice and Experience 20, n. 17 (10 dicembre 2008): 2049–60. http://dx.doi.org/10.1002/cpe.1304.

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