Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 23 for “"cluster computing"”.
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Performance analysis and improvement of InfiniBand networks. Modelling and effective Quality-of-Service mechanisms for interconnection networks in cluster computing systems.
… for constructing high-performance interconnected cluster computing systems. This architecture replaces the traditional bus-based interconnection with a switch-based network for the server Input-Output (I/O) and inter-processor communications. The efficient Quality-of-Service (QoS) mechanism is …
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Evaluating a Cluster of Low-Power ARM64 Single-Board Computers with MapReduce
… computations over large datasets residing on clusters of commodity hardware. MapReduce abstracts away the challenging low-level synchronization and scalability details which parallel and distributed computing often necessitate, reducing the concept burden on programmers and scientists who …
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Optimizing a parallel fast Fourier transform
Parallel computing, especially cluster computing has become more popular and more powerful in recent years. Star-P is a means of harnessing that power by eliminating the difficulties in parallelizing code and by providing the user with a familiar and intuitive interface. This paper presents methods …
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Routing and scheduling for cloud service data centers
… analyze and mine the vast amount of data. Cluster computing systems, like MapReduce and Hadoop, have provided an efficient platform for large scale computation. This research studies the data locality problem for cluster computing systems, which significantly affects system throughput and …
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A study into the abstraction and integration of hardware and software for accelerated product development in a broadcast environment
… (MXF), multimedia processing frameworks, grid computing, cluster computing, and software optimisation. The key outcomes of this research are implementations of some of the advanced features of MXF, a report into multimedia processing frameworks, a review of grid technologies, an architecture …
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Numerical modeling of borehole acoustics : parallel implementation of a loggin-while-drilling (LWD) model
… finite difference code showing the efficiency of cluster computing in a discretized space.
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Improving the Performance of Parallel SPARQL Query Processing on Apache Spark Using Bloom Filters
… RDF query processing techniques utilizing cluster computing. Among the different platforms for cluster computing, Apache Spark has emerged as the industry leader with a huge development community. In this thesis, we extend our previous work on parallel SPARQL query processing using Apache …
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Design and implementation of evolutionary computation algorithms for volunteer compute networks
… and deployed the system onto Boinc, a volunteer computing network (VCN). Evolutionary computation is computationally expensive and VCN allows more cost-effective cluster computing since resources are donated. In addition, we believe that the design similarities between EGS and our chosen VCN …
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Parallel SPARQL Query Execution using Apache Spark
… techniques that can leverage the power of cluster computing. Big data ecosystems like Apache Spark provide new opportunities for designing scalable RDF indexing and query processing techniques. In this thesis, we present new ideas on storing, indexing, and query processing of RDF datasets …
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Distributed timing analysis
… timer OpenTimer. We investigated into existing cluster computing frameworks from big data community and demonstrated DTA is a difficult fit here in terms of computation patterns and performance concern. Our specialized DTA framework supports (1) general design partitions (logical, physical, …
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Shade : a differentially private wrapper around Apache Spark
… and scalable framework for Apache Spark, a cluster computing framework, that provides strong privacy guarantees for users even in the presence of an informed adversary, while still providing high utility for analysts in an interactive wrapper. The framework, titled Shade, includes two …
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Metamori: A library for Incremental File Checkpointing
The advent of cluster computing has resulted in a thrust towards providing software mechanisms for reliability on clusters. The prevalent model for such mechanisms is to take a snapshot of the state of an application, called a checkpoint and commit it to stable storage. This checkpoint has …
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Analytical and Numerical Analysis of Static Coulomb Formations
… algorithm could be extended to take advantage of cluster computing.
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Exploration of fault tolerance in Apache Spark
… of these approaches. Apache Spark is a cluster computing system comprised of three main components: the driver program, the cluster manager, and the worker nodes. Spark already tolerates the loss of worker nodes, and other external tools already provide fault tolerance solutions for the …
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Design and Implementation of a Distributed Lattice Boltzmann-based Fluid Flow Simulation Tool
… in a distributed way (for example, using cluster computing) can decrease the execution time and reduces the memory requirements for each computer. Dynamic Heterogeneous Clusters (DHC) is a class of clusters involving computers inter-connected by a local area network; these computers are …
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Proton Computed Tomography: Matrix Data Generation Through General Purpose Graphics Processing Unit Reconstruction
… algorithms to be implemented across some sort of cluster computing architecture. The prototypical algorithm to solve the pCT system is the algebraic reconstruction technique (ART) that has been modified into parallel versions called block-iterative-projection (BIP) methods and …
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High Performance Data Mining Techniques For Intrusion Detection
… will show that how high performance and parallel computing can be used to scale the data mining algorithms to handle large datasets, allowing the data mining component to search a much larger set of patterns and models than traditional computational platforms and algorithms would allow. We develop …
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Transforming Point Data into Proximity Graphs
… evolutionary biology, computer vision, cluster analysis, and visualization. The emergence of big data has created a need for scalable algorithms to generate proximity graphs for massive datasets. In this thesis, we propose a novel approach for creating DT, GG, and RNG by leveraging the …
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Heterogeneous Cloud Systems Based on Broadband Embedded Computing
Computing systems continue to evolve from homogeneous systems of commodity-based servers within a single data-center towards modern Cloud systems that consist of numerous data-center clusters virtualized at the infrastructure and application layers to provide scalable, cost-effective and elastic …
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