It is known that accelerator physics technology has made essential contributions to other branches of science and technology. Experiments realized on linear and circular accelerators have made remarkable discoveries a...
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ISBN:
(纸本)9783642152733
It is known that accelerator physics technology has made essential contributions to other branches of science and technology. Experiments realized on linear and circular accelerators have made remarkable discoveries about the basic nature of matter. In particular, there are now two accelerator projects. The first of them is already realized the Large Hadron Collider, the second the pilot project for future dedicated EDM machine. These and other similar projects (i. e., the project NICA JINR, Dubna) demand some special requirements for simulation methods and technologies. Indeed, the successful functioning of these accelerators requires essential advancement in theory and technology leading to new particle accelerators capabilities. The complexity of accelerator physics problems makes comprehensive use of modern analytical, numerical, and symbolic methods. Only if we integrate these approaches the corresponding computational technologies will be effective. In the present report, we discuss sonic problems of correlation between symbolic and numerical manipulation. The main approach for beam dynamics is based on Lie algebraic methods and corresponding matrix formalism as presentation tools. All suggested approaches are realized using symbolic algorithms, and the corresponding symbolic formulae are assumed as a basis of numerical algorithms. This approach allows to realize the necessary numerical modeling using parallel and distributed computational systems for some practical problems.
This report is devoted to discussion of numerical and symbolic computing ratio in beam physics. We tray to draw attention on basic conceptual and computational problems first of all. It is known that the main problem ...
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This report is devoted to discussion of numerical and symbolic computing ratio in beam physics. We tray to draw attention on basic conceptual and computational problems first of all. It is known that the main problem in modern computational beam physics connected with high performance computing realization. The most of used approaches are not appropriate for computing using multiprocessing systems. Here we give some possible solutions, which based on a matrix presentation of necessary information and modern information technologies.
Ensemble empirical-mode decomposition (EEMD) is a novel adaptive time-frequency analysis method, which is particularly suitable for extracting useful information from noisy non-linear or nonstationary data. Unfortunat...
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Ensemble empirical-mode decomposition (EEMD) is a novel adaptive time-frequency analysis method, which is particularly suitable for extracting useful information from noisy non-linear or nonstationary data. Unfortunately, since the EEMD is highly compute-intensive, the method does not apply in real-time applications on top of commercial-off-the-shelf computers. Aiming at this problem, a parallelized EEMD method has been developed using general-purpose computing on the graphics processing unit (GPGPU), namely, G-EEMD. A spectral entropy facilitated by G-EEMD was, therefore, proposed to analyze the EEG data for estimating the depth of anesthesia (DoA) in a real-time manner. In terms of EEG data analysis, G-EEMD has dramatically improved the run-time performance by more than 140 times compared to the original serial EEMD implementation. G-EEMD also performs far better than another parallelized implementation of EEMD bases on conventional CPU-based distributedcomputing technology despite the latter utilizes 16 high-end computing nodes for the same computing task. Furthermore, the results obtained from a pharmacokinetics/pharmacodynamic (PK/PD) model analysis indicate that the EEMD method is slightly more effective than its precedent alternative method (EMD) in estimating DoA, the coefficient of determination R(2) by EEMD is significantly higher than that by EMD(p < 0.05, paired t-test) and the prediction probability P(k) by EEMD is also slighter higher than that by EMD (p < 0.2, paired t-test).
This paper proposes a method for reducing the number of search nodes involved in the solution of queries arriving to a Web search engine. The method is applied by the query receptionist machine during situations of su...
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This paper proposes a method for reducing the number of search nodes involved in the solution of queries arriving to a Web search engine. The method is applied by the query receptionist machine during situations of sudden peaks in query trafic to reduce the load on the search nodes. The experimental evaluation based on actual traces from users of a major search engine, shows that the proposed method outperforms alternative strategies. This is more evident for systems composed of a large number of search nodes which indicates that the method is also more scalable than the alternative strategies.
Similarity search has been proved suitable for searching in large collections of unstructured data objects. A number of practical index data structures for this purpose have been proposed. All of them have been devise...
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Similarity search has been proved suitable for searching in large collections of unstructured data objects. A number of practical index data structures for this purpose have been proposed. All of them have been devised to process single queries sequentially. However, in large-scale systems such as Web Search Engines indexing multi-media content, it is critical to deal efficiently with streams of queries rather than with single queries. In this paper we show how to achieve efficient and scalable performance in this context. To this end we transform a sequential index based on clustering into a distributed one and devise algorithms and optimizations specially tailored to support high-performance parallel query processing. (C) 2008 Elsevier B. V. All rights reserved.
The use of supercomputing technology, parallel and distributed processing, and sophisticated algorithms is of major importance for computational scientists. Yet, the scientists’ goals are to solve their challenging s...
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The use of supercomputing technology, parallel and distributed processing, and sophisticated algorithms is of major importance for computational scientists. Yet, the scientists’ goals are to solve their challenging scientific problems, not the software engineering tasks associated with it. For that reason, computational science and engineering must be able to rely on dedicated support from program development and analysis tools. The primary intention of this workshop is to bring together developers of tools for scientific computing and their potential users. Tool developers present how their tools support scientists and engineers during program development and analysis. The users report their experiences employing such tools, especially highlighting the benefits and possible improvements.
The reliable and fault tolerant computers are key to the success to aerospace, and communication industries. Designing a reliable digital system, and detecting and repairing the faults are challenging tasks in order f...
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ISBN:
(纸本)9780769536422
The reliable and fault tolerant computers are key to the success to aerospace, and communication industries. Designing a reliable digital system, and detecting and repairing the faults are challenging tasks in order for the digital system to operate without failures for a given period of time. The paper presents a new and systematic software engineering approach of performing fault diagnosis parallel and distributed computing. The purpose of the paper would be to demonstrate a method to build a fault diagnosis for a parallel and distributed computing. The paper chooses a model posed a tremendous challenge to the user for fault analysis. The model is the classic PMC model that happens to be a parallel and distributed computing. The paper would also show a method for building an optimal inference engine by obtaining sub graphs that also preserve the necessary and sufficient conditions of the model. Coin words: parallel and distributed computing, Artificial Intelligence
This article describes problems of distributing a real-time, human-in-the-loop simulator. The simulator itself is a dynamics simulator solving the dynamics of Multi-Body Systems in real-time. Techniques used to distri...
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ISBN:
(纸本)9780769538686
This article describes problems of distributing a real-time, human-in-the-loop simulator. The simulator itself is a dynamics simulator solving the dynamics of Multi-Body Systems in real-time. Techniques used to distribute computation are presented and their suitability for general purpose interactive simulation are discussed.
Graphics Processing Units (GPUs) have evolved over the past few years from dedicated graphics rendering devices to powerful parallel processors, outperforming traditional Central Processing Units (CPUs) in many areas ...
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ISBN:
(纸本)9780769537887
Graphics Processing Units (GPUs) have evolved over the past few years from dedicated graphics rendering devices to powerful parallel processors, outperforming traditional Central Processing Units (CPUs) in many areas of scientific computing. The use of GPUs as processing elements was very limited until recently, when the concept of General-Purpose computing on Graphics Processing Units (GPGPU) was introduced. GPGPU made possible to exploit the processing power and the memory bandwidth of the GPUs with the use of APIs that hide the GPU hardware from programmers. This paper presents experimental results on the parallel processing for some well known on-line string matching algorithms using one such GPU abstraction API, the Compute Unified Device Architecture (CUDA).
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