The physics goals of the next Large Hadron Collider run include high precision tests of the Standard Model and searches for new physics. These goals require detailed comparison of data with computational models simula...
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The physics goals of the next Large Hadron Collider run include high precision tests of the Standard Model and searches for new physics. These goals require detailed comparison of data with computational models simulating the expected data behavior. To highlight the role which modeling and simulation plays in future scientific discovery, we report on use cases and experience with a unified system built to process both real and simulated data of growing volume and variety.
The near-Earth space surveillance requires accurate and fast orbit predictions for the multitude of objects that are present around our planet. This prediction is performed by means of orbit propagators which offer so...
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ISBN:
(纸本)9781479984817
The near-Earth space surveillance requires accurate and fast orbit predictions for the multitude of objects that are present around our planet. This prediction is performed by means of orbit propagators which offer solutions to the satellite equations of motion. Based on the method of computation those propagators are split into three categories: analytical, numerical and semi-analytical, each with its own advantages and disadvantages. Today a large number of propagators are implemented in the form of software libraries, some proprietary and some freeware or even open-source. In this paper we have taken a semi-analytical propagator from an open-source Java library and used it in a distributed environment in order to compute the position of a satellite during a large time interval.
Scientific workloads often require scalable computing resources. The traditional HPC paradigm provides large scale computing resources but requires IT specialists to buy and maintain large computer infrastructure in t...
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ISBN:
(纸本)9781467372879
Scientific workloads often require scalable computing resources. The traditional HPC paradigm provides large scale computing resources but requires IT specialists to buy and maintain large computer infrastructure in their organization. With the emergence of cloud computing, more and more scientists and engineers are moving their computing workloads from local clusters to public cloud. However, such a migration often requires experience both in understanding cloud architecture and cloud development skills, which can impede the efficiency and success of migration. This paper presents a cloud-based parallel and distributed computing platform to support scientific computing. With the Simulation Runner, scientists only need to submit their embarrassingly parallel scientific applications with appropriate arguments or parameters. There is no need to rebuild migrate cloud applications or purchase large computer infrastructures by themselves. The system also uses a file caching mechanism to improve performance and reduce the costs of data-intensive computing tasks. A 44X speedup was resulted from using 128 computing instances compared with premise high performance desktop computers. A comparison study on the performance of file cache is given at the end of the paper.
Generally, image rendering requires high computing capacity. It is really time consuming to render a movie on a single machine. The use of multiple machines to render a move requires much effort to control the workflo...
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ISBN:
(纸本)9781479989379
Generally, image rendering requires high computing capacity. It is really time consuming to render a movie on a single machine. The use of multiple machines to render a move requires much effort to control the workflow and data. With the emergence of cloud computing, more and more scientists and engineers are moving their tasks from laboratories to public clouds. This migration requires some sort experience on both the cloud architecture and coding in the cloud. This paper proposes a simple service to render movies on Microsoft Azure that accelerates movie rendering. This service, called AzureRender, also introduces task parallelism and cache management to improve performance and reduce cost. A comparative study on image rendering performance and cost between Microsoft Azure and desktop machines is given at the end of the paper.
This paper presents a parallel particle swarm optimization (PSO) technique for reactive power and voltage control (Volt/Var Control: VVC) investigating dependability. High penetration of renewable energies and deregul...
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ISBN:
(纸本)9781509001910
This paper presents a parallel particle swarm optimization (PSO) technique for reactive power and voltage control (Volt/Var Control: VVC) investigating dependability. High penetration of renewable energies and deregulation of power systems force power flow to change suddenly and operators in control centers have to control voltage in wider power systems. Therefore, VVC is required to shorten the control interval and handle larger-scale power systems. One of the solutions for the problem is applications of parallel and distributed computing. Since power system is one of the infrastructures of social community, sustainable voltage control is crucial and dependability is strongly required for VVC. This paper investigates not only fast computation by parallel computation but also dependability of parallel PSO for VVC with IEEE 14, 30, 57, and 118 bus systems.
The work deals with the construction of strategy for finding optimal control of systems for spatially distributed systems on an example of problems in physics beams. The suggested approach is based on use of exact and...
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ISBN:
(纸本)9780735412873
The work deals with the construction of strategy for finding optimal control of systems for spatially distributed systems on an example of problems in physics beams. The suggested approach is based on use of exact and approximate invariants as a controlling mechanism for control of modelling process of beam lines. The classical problem of optimal control of similar systems as an optimal control problem is formulated in a functional space. This approach is based on algebraic methods Lie and the corresponding matrix formalism that allows you to build not only the formal procedures for finding optimal solutions, but also provide the necessary constructive computational procedures.
This paper presents a parallel particle swarm optimization (PSO) for reactive power and voltage control (Volt/Var Control: VVC) in electric power systems verifying dependability of the control. Considering high penetr...
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ISBN:
(纸本)9781479974924
This paper presents a parallel particle swarm optimization (PSO) for reactive power and voltage control (Volt/Var Control: VVC) in electric power systems verifying dependability of the control. Considering high penetration of renewable energies and deregulation of power systems, electric power flows can change suddenly and operators in control centers have to control voltage in wider power systems. Therefore, VVC is required to shorten the control interval and handle larger-scale power systems. One of the solutions for this problem is applications of parallel and distributed computing. Since electric power systems is one of the infrastructures of social community, sustainable voltage control is crucial and dependability is strongly required for VVC. This paper investigates not only fast computation by parallel computation but also dependability of parallel PSO for VVC. The results are meaningful for practical parallel computation by PSO in actual VVC operations.
The particle flow filters, proposed by Daum & Hwang, provide a powerful means for density-based nonlinear filtering but their computation is intense and may be prohibitive for real-time applications. This paper pr...
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ISBN:
(纸本)9781628417623
The particle flow filters, proposed by Daum & Hwang, provide a powerful means for density-based nonlinear filtering but their computation is intense and may be prohibitive for real-time applications. This paper proposes a design for superfast implementation of the exact particle flow filter using a field-programmable gate array (FPGA) as a parallel environment to speedup computation. Simulation results from a nonlinear filtering example are presented to demonstrate that using FPGA can dramatically accelerate particle flow filters through parallelization at the expense of a tolerable loss in accuracy as compared to nonparallel implementation.
Nearest neighbor search is a key technique used in hierarchical clustering. The time complexity of standard agglomerative hierarchical clustering is O(n(3)), while the time complexity of more advanced hierarchical clu...
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ISBN:
(纸本)9781479979356
Nearest neighbor search is a key technique used in hierarchical clustering. The time complexity of standard agglomerative hierarchical clustering is O(n(3)), while the time complexity of more advanced hierarchical clustering algorithms (such as nearest neighbor chain) is O(n(2)). This paper presents a new nearest neighbor search method called nearest neighbor boundary(NNB), which first divides a large dataset into independent subsets and then finds nearest neighbor of each point in the subsets. When NNB is used, the time complexity of hierarchical clustering can be reduced to O(n log(2) n). Based on NNB, we propose a fast hierarchical clustering algorithm called nearest-neighbor boundary clustering(NBC), and the proposed algorithm can also be adapted to the parallel and distributed computing frameworks. The experimental results demonstrate that our proposal algorithm is practical for large datasets.
The aim of this paper is to present a distributed implementation of the Type-2 Fuzzy Logic (T2FL) algorithm in a mobile agent based distributedcomputing platform. The proposed algorithm is assigned to be implemented ...
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ISBN:
(纸本)9781467387491
The aim of this paper is to present a distributed implementation of the Type-2 Fuzzy Logic (T2FL) algorithm in a mobile agent based distributedcomputing platform. The proposed algorithm is assigned to be implemented on an SPMD (Single Program Multiple Data) architecture which is based on a cooperative mobile agent model. It is constituted by a set of mobile agents as AVPEs (Agent Virtual Processing Elements) in order to improve the processing resources needed for performing the big data image segmentation. In this work we focused on the application of this algorithm to process the big data MRI (Magnetic Resonance Images) image. The input image is splitted into elementary images by the Mobile Team leader Agent and encapsulated one per AVPE. Each AVPE perform and exchange the segmentation results and maintain asynchronous communication with their Team leader agent until the convergence of this algorithm. The obtained experimental results in terms of accuracy and efficiency analysis of the proposed distributed implementation are achieved thanks to the mobile agents several interesting skills introduced in this distributed computational model.
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