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A New Digital Repository for Remotely Sensed Hyperspectral Imagery on GPUs

A New Digital Repository for Remotely Sensed Hyperspectral I...

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15th international symposium on symbolic and numeric algorithms for scientific computing (SYNASC)

作者： Sevilla, Jorge Plaza, Antonio Univ Extremadura Hyperspectral Comp Lab Dept Technol Comp & Commun Caceres Spain

ISBN: (纸本)9781479930357

Hyperspectral imaging is a new technique in remote sensing in which an imaging spectrometer collects hundred of images (at different wavelength channels) for the same area on the surface of Earth. Over the last years, hyperspectral image data sets have been collected from a great amount of locations over the world using a variety of instruments for Earth observation. Only a small amount of them are available for public use and they are spread among different storage locations and exhibit significant heterogeneity regarding the storage format. therefore, the development of a standardized hyperspectral data repository is a highly desired goal in the remote sensing community. In this paper, we describe the development of a shared digital repository for remotely sensed hyperspectral data, which allows uploading new hyperspectral data sets along with meta-data, ground-truth and analysis results (spectral information). Such repository is presented as a web service for providing the management of images through a web interface, and it is available online from http://***/repository. Most importantly, the developed system includes a spectral unmixing-based content based image retrieval (CBIR) functionality which allows searching for images from the database using spectrally pure components or endmembers in the scene. A full spectral unmixing chain is implemented for spectral information extraction, which allows filtering images using the similarity of the spectral signature and abundance of a given ground-truth. In order to accelerate the process of obtaining the spectral information for new entries in the system, we resort to an efficient implementations of spectral unmixing algorithms of graphics processing units (GPUs).

关键词： Hyperspectral imaging repository content-based image retrieval (CBIR) spectral unmixing high performance computing GPUs distributed resources

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Register Caching for Stencil Computations on GPUs 16

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16th international symposium on symbolic and numeric algorithms for scientific computing (SYNASC)

作者： Falch, thomas L. Elster, Anne C. Norwegian Univ Sci & Technol Dept Comp & Informat Sci Trondheim Norway

ISBN: (纸本)9781479984480

For most applications, taking full advantage of the memory system is key to achieving good performance on GPUs. In this paper, we introduce register caching, a novel idea where registers of multiple threads are combined and used as a shared, last level, manually managed cache for the contributing threads. this method is enabled by the shuffle instruction recently introduced in Nvidia's Kepler GPU architecture, which allows threads in the same warp to exchange data directly, previously only possible by going through shared memory. We evaluate our proposal with a stencil computation benchmark, achieving speedups of up to 2.04, compared to using shared memory on a GTX680 GPU. Stencil computations form the core of many scientific applications, which can therefore benefit from our proposal. Furthermore, our method is not limited to stencil computations, but is applicable to any application with a predictable memory access pattern suitable for manual caching.

关键词： cache storage graphics processing units shared memory systems GTX680 GPU Nvidia Kepler GPU architecture data exchange graphics processing unit register caching shared memory system shuffle instruction stencil computation Benchmark testing Computer architecture Graphics processing units Indexes Instruction sets Manuals Registers CUDA Caching GPU GPU computing Register Caching Stencil Computations Graphics Processing Unit shared memory systems Registers Cache memory instruction sets Benchmark testing cache storage Computer Architecture data exchange GRAPPER PICK UP shared memory thREADS Cache Memory System

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ARTIST Methodology and Framework: A novel approach for the migration of legacy software on the Cloud

ARTIST Methodology and Framework: A novel approach for the m...

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15th international symposium on symbolic and numeric algorithms for scientific computing (SYNASC)

作者： Menychtas, Andreas Santzaridou, Christina Kousiouris, George Varvarigou, theodora Orue-Echevarria, Leire Alonso, Juncal Gorronogoitia, Jesus Bruneliere, Hugo Strauss, Oliver Senkova, Tatiana Pellens, Bram Stuer, Peter Natl Tech Univ Athens Athens Greece TECNALIA ICT European Software Inst Div Zamudio Spain ATOS Res & Innovat Serv Engn & IT Platforms Lab Madrid Spain Inria Mines Nantes AtlanMod Team Nantes France LINA Nantes France Fraunhofer Inst Ind Engn IAO Software Technol Team Stuttgart Germany Spikes NV Brussels Belgium

ISBN: (纸本)9781479930357

Nowadays Cloud computing is considered as the ideal environment for engineering, hosting and provisioning applications. A continuously increasing set of cloud-based solutions is available to application owners and developers to tailor their applications exploiting the advanced features of this paradigm for elasticity, high availability and performance. Although these offerings provide many benefits to new applications, they also incorporate constrains to the modernization and migration of legacy applications by obliging the use of specific technologies and explicit architectural design approaches. the modernization and adaptation of legacy applications to cloud environments is a great challenge for all involved stakeholders, not only from the technical perspective, but also in business level with the need to adapt the business processes and models of the modernized application that will be offered from now on, as a service. In this paper we present a novel model-driven approach for the migration of legacy applications in modern cloud environments which covers all aspects and phases of the migration process, as well as an integrated framework that supports all migration process.

关键词： Cloud computing Legacy Software Modelling Migration Modernization Methodology

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Using Models at Runtime to Support Adaptable Monitoring of Multi-Clouds Applications 16

Using Models at Runtime to Support Adaptable Monitoring of M...

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16th international symposium on symbolic and numeric algorithms for scientific computing (SYNASC)

作者： Cianciaruso, Lorenzo di Forenza, Francesco Di Nitto, Elisabetta Miglierina, Marco Ferry, Nicolas Solberg, Arnor Politecn Milan Dipartimento Elettron Informaz & Bioingn Politecn Milan Italy SINTEF Dept Networked Syst & Serv Oslo Norway

ISBN: (纸本)9781479984480

the ability to run and manage multi-clouds applications (i.e., applications that run on multiple clouds) allows exploiting the peculiarities of each cloud solution and hence improves non-functional aspects such as availability, cost, and scalability. Monitoring such multi-clouds applications is fundamental to track the health of the applications themselves and of their underlying infrastructures as well as to decide when and how to adapt their behaviour and deployment. It is clear that, not only the application but also the corresponding monitoring infrastructure should dynamically adapt in order to (i) be optimized to the application context (e.g., adapting the frequency of monitoring to reduce network load);(ii) to enable the co-evolution of the monitoring platform together with the cloud application (e.g., if a service migrates from one provider to another, the monitoring activities have to be adapted accordingly). In this paper, we present a model-based platform for the dynamic provisioning, deployment, and monitoring of multi-clouds applications whose monitoring activities can be automatically and dynamically adapted to best fit with the actual deployment of the application.

关键词： cloud computing adaptable multiclouds applications monitoring application context cloud application cloud solution dynamic provisioning model-based platform monitoring infrastructure nonfunctional aspects Adaptation models Cognition Computer architecture Engines Measurement Monitoring Observers adaptation cloud modaclouds models at runtime models@runtime monitoring multi-cloud multicloud Clouds Computer Architecture Engines CLOUDS Cloud computing Cognition Runtime Observers Adaptation models deployment

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Load scheduling in a cloud based massive video-storage environment 16

Load scheduling in a cloud based massive video-storage envir...

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16th international symposium on symbolic and numeric algorithms for scientific computing (SYNASC)

作者： Bayyapu, Karunakar Reddy Fischer, Paul Tech Univ Denmark Dept Appl Math & Comp Sci DK-2800 Lyngby Denmark

ISBN: (纸本)9781479984480

We propose an architecture for a storage system of surveillance videos. Such systems have to handle massive amounts of incoming video streams and relatively few requests for replay. In such a system load (i.e., write requests) scheduling is essential to guarantee performance. Large-scale data-storage system (LSDSS) is an emerging hosting facility for video-storage, which has a very high number of writes while most of the videos are never or rarely watched. We discuss the design and implementation of LSDSS and load scheduling in autonomous storage environments called datacenters in LSDSS. A datacenter (DC) is the basic concept in our LSDSS, which has the self-management system to store data efficiently. A LSDSS consists of many DCs organized in a hierarchy fashion, thereby decentralizing load scheduling tasks. Because DC has a simple design, load scheduling is particularly suited for implementation on a real-time video surveillance and allows to make scheduling decisions. We also discuss experimental results that clearly show the advantage of load scheduling over the widely known base load scheduling.

关键词： cloud computing computer centres scheduling video databases video surveillance DC LSDSS autonomous storage environments cloud based massive video-storage environment datacenters incoming video streams large-scale data-storage system real-time video surveillance scheduling decisions system load scheduling Bandwidth Computer architecture Scheduling Scheduling algorithms Servers Videos architecture cloud storage distributed storage load scheduling video storage load dispatching Cloud computing Videotapes video databases Scheduling algorithms Computer Architecture video monitoring Servers direct current Building construction ARCHITECTURE Bandwidth

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Optimal Capacity Allocation for executing MapReduce Jobs in Cloud Systems 16

Optimal Capacity Allocation for executing MapReduce Jobs in ...

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16th international symposium on symbolic and numeric algorithms for scientific computing (SYNASC)

作者： Malekimajd, M. Rizzi, A. M. Ardagna, D. Ciavotta, M. Passacantando, M. Movaghar, A. Sharif Univ Technol Dept Comp Engn Tehran Iran Politecn Milan Dipartimento Elettron Informaz & Bioingn I-20133 Milan Italy Univ Pisa Dipartimento Informat Pisa Italy

ISBN: (纸本)9781479984480

Nowadays, analyzing large amount of data is of paramount importance for many companies. Big data and business intelligence applications are facilitated by the MapReduce programming model while, at infrastructural layer, cloud computing provides flexible and cost effective solutions for allocating on demand large clusters. Capacity allocation in such systems is a key challenge to providing performance for MapReduce jobs and minimize cloud resource cost. the contribution of this paper is twofold: (i) we formulate a linear programming model able to minimize cloud resources cost and job rejection penalties for the execution of jobs of multiple classes with (soft) deadline guarantees, (ii) we provide new upper and lower bounds for MapReduce job execution time in shared Hadoop clusters. Moreover, our solutions are validated by a large set of experiments. We demonstrate that our method is able to determine the global optimal solution for systems including up to 1000 user classes in less than 0.5 seconds. Moreover, the execution time of MapReduce jobs are within 19% of our upper bounds on average.

关键词： Big Data cloud computing data analysis linear programming parallel programming pattern clustering resource allocation MapReduce job execution time MapReduce programming model big data applications business intelligence applications capacity allocation cloud resource cost minimization cloud systems infrastructural layer job rejection linear programming model optimal capacity allocation shared Hadoop clusters Bismuth Mathematical model Optimization Resource management Scalability Silicon Upper bound Capacity Allocation Cloud computing MapReduce Performance bounds Cloud computing big data linear programming models management of resources Upper bound jobs Parallel programming Data analysis Scalability bismuth Cluster Analysis linear programming Resource utilization Mathematical Model Big data applications

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Algorithmic experiences in Coxeter spectral study of P-critical edge-bipartite graphs and posets

Algorithmic experiences in Coxeter spectral study of P-criti...

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15th international symposium on symbolic and numeric algorithms for scientific computing (SYNASC)

作者： Polak, Agnieszka Simson, Daniel Nicolaus Copernicus Univ Fac Math & Comp Sci Torun Poland

ISBN: (纸本)9781479930357

We study P-critical edge-bipartite graphs (bigraphs for short) Delta with n >= 2 vertices, by means of the nonsymmetric Gram matrix G(Delta) is an element of M-n (Z), the Coxeter matrix Cox(Delta)(t) := G(Delta) center dot G(Delta)(-tr) M-n(Z), its Coxeter polynomial cox(Delta (t)) = det(t center dot E + G(Delta)(-tr)) and its Coxeter spectrum specc(Delta). We recall that Delta is positive if the symmetric matrix G(Delta) := G(Delta) + G(Delta)(-tr) is positive definite;and Delta is P-critical if it is not positive and each of its proper full subbigraphs is positive. It is easy to see that if two bigraphs Delta, Delta' are Z-bilinear equivalent Delta approximate to(Z) Delta' (i.e., there exists a matrix B is an element of Gl(n,Z) such that G Delta - B-tr center dot G(Delta') center dot B) then their Coxeter spectra specc(Delta) and specc(Delta') coincide;but the converse implication does not hold in general. One of the main questions of the Coxeter spectral analysis of connected P-critical bigraphs Delta, Delta' is whether the congruence Delta approximate to (Z)Delta' holds if and only if specc(Delta) = specc(Delta') In this note we discuss the problem in case when n < 10 and Delta and Delta' are P-critical loop-free bigraphs such that their Euclidean types D Delta, D Delta' is an element of {A(n), n >= 1, D-m, m >= 4, <(E)over tilde>(6), (E) over tilde (7), (E) over tilde (8)} coincide. In particular, we get an affirmative answer to the stated question, for a large class of P-critical bigraphs and Tits P-critical finite posets. By applying symbolic and numerical algorithms in Maple and C# we compute the set of Coxeter polynomials cox(Delta) (t) for P-critical loop-free bigraphs Delta, with at most 10 vertices.

关键词： Coxeter-Gram polynomial Euclidean diagram Gram matrix P-critical edge-bipartite graph algorithm edge-bipartite graph orthogonal group sincere root unit quadratic form loop-free Bipartite graph algorithms Positive definite Poset mathematics computing symbolic algebra Acer vertex head If and only if Polynomial matrices

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On corank two edge-bipartite graphs and simply extended Euclidean diagrams 16

On corank two edge-bipartite graphs and simply extended Eucl...

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16th international symposium on symbolic and numeric algorithms for scientific computing (SYNASC)

作者： Gasiorek, Marcin Simson, Daniel Zajac, Katarzyna Nicholas Copernicus Univ Fac Math & Comp Sci Torun Poland

ISBN: (纸本)9781479984480

We continue the Coxeter spectral study of finite connected loop- free edge- bipartite graphs Delta, with m + 2 >= 3 vertices (a class of signed graphs), started in [SIAM J. Discrete Math., 27(2013), 827- 854] by means of the complex Coxeter spectrum specc(Delta) subset of C and presented in our talks given in SYNASC12 and SYNASC13. Here, we study non- negative edge- bipartite graphs of corank two, in the sense that the symmetric Gram matrix G Delta is an element of Mm+2(Z) of Delta is positive semi- definite of rank m >= 1. Extending each of the simply laced Euclidean diagrams (A) over tilde (m), m >= 1, D-m, m >= 4, (E) over tilde (6), (E) over tilde (7), (E) over tilde (8) by one vertex, we construct a family of loop-free corank two diagrams (A) over tilde (2)(m), (D) over tilde (2)(m), (E) over tilde (2)(6), (E) over tilde (2)(7), (E) over tilde (2)(8) (called simply extended Euclidean diagrams) such that they classify all connected corank two loop- free edge- bipartite graphs Delta, with m + 2 >= 3 vertices, up to Z-congruence Delta similar to(Z) Delta'. Here Delta similar to(Z) Delta' means that G(Delta') = B-tr.G(Delta).B, for some B is an element of Mm+2(Z) such that det B = +/- 1. We present algorithms that generate all such edge- bipartite graphs of a given size m + 2 >= 3, together with their Coxeter polynomials, and the reduced Coxeter numbers, using symbolic and numeric computer calculations in Python. Moreover, we prove that for any corank two connected loop- free edge- bipartite graph Delta, with m + 2 >= 3 vertices, there exists a simply extended Euclidean diagram D such that Delta similar to(Z) D.

关键词： graph theory mathematics computing matrix algebra polynomials Coxeter polynomials Python complex Coxeter spectrum corank two edge-bipartite graphs extended Euclidean diagrams finite connected loop-free edge-bipartite graphs nonnegative edge-bipartite graphs numeric computer calculations reduced Coxeter numbers signed graphs symbolic computer calculations symmetric Gram matrix Bipartite graph Kernel Labeling Polynomials Symmetric matrices Vectors Zinc Coxeter spectral analysis Euclidean diagrams Z-congruence inflation algorithm non-negative bigraphs of corank two quadratic form Bipartite graph Polynomial mathematics computing Symmetric matrix Pythonidae Quadratic form matrix algebra Graph theory loop-free Euclidean Python zinc Kernel

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A Distributed-memory Parallelization of a Shared-memory Parallel Ensemble Kalman Filter 16

A Distributed-memory Parallelization of a Shared-memory Para...

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16th international symposium on symbolic and numeric algorithms for scientific computing (SYNASC)

作者： Rostami, M. Ali Buecker, H. Martin Vogt, Christian Seidler, Ralf Neuhaeuser, David Rath, Volker Univ Jena Inst Comp Sci D-07743 Jena Germany Rhein Westfal TH Aachen Inst Appl Geophys & Geothermal Energy EON Energy Res Ctr D-52056 Aachen Germany Dublin Inst Adv Studies Sch Cosm Phys Dublin 4 Ireland Univ Complutense Madrid Dept Fis Tierra Astron & Astrofis 2 Madrid Spain

ISBN: (纸本)9781479984480

Inverse problems arise in various areas of science and engineering. these problems are not only difficult to solve numerically, but they also require a large amount of computer resources both in time and memory. It is therefore not surprising that inverse problems are often solved using techniques from high-performance computing. We consider the parallelization of an inverse problem in the field of geothermal reservoir engineering. In this particular scientific application, the underlying software package is already parallelized using the shared-memory programming paradigm OpenMP. Here, we present an extension of this parallelization to distributed memory enabling a hybrid OpenMP/MPI parallelization. the situation is different from the standard way of hybrid parallel programming because the data structures of the OpenMP-parallelized code differ from those in the serial implementation. We exploit this transformation of the data structures in our distributed-memory strategy for parallelizing an ensemble Kalman filter, a particular method for the solution of inverse problems. We describe this novel parallelization strategy, introduce a performance model, and present timing results on a compute cluster using nodes with 2 sockets, each equipped with Intel Xeon X5675 Westmere EP processors with 6 cores. All timing results are obtained with a pure MPI parallelization without using any OpenMP threads.

关键词： Kalman filters message passing parallel programming shared memory systems Intel Xeon X5675 Westmere EP processors computer resource data structures distributed-memory parallelization geothermal reservoir engineering hybrid Open MP-MPI parallelization hybrid parallel programming message passing interface parallelization strategy shared-memory parallel ensemble Kalman filter shared-memory programming paradigm Algorithm design and analysis Arrays Computational modeling Inverse problems Mathematical model Standards Inverse method message passing Kalman filters parallelization Algorithm design and analysis shared memory systems Parallel programming Data structures Reservoir engineering distributed memory Computational modeling Mathematical Model

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Proceedings - 13th international symposium on symbolic and numeric algorithms for scientific computing, SYNASC 2011: Preface

Proceedings - 13th International Symposium on Symbolic and N...

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Proceedings - 13th international symposium on symbolic and numeric algorithms for scientific computing, SYNASC 2011 2012年 x-xi页

作者： Wang, Dongming Negru, Viorel Ida, Tetsuo Jebelean, Tudor Petcu, Dana Watt, Stephen M. Zaharie, Daniela

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