This paper describes a constructive approach of distributedparallelcomputing using by hybrid union of MAPREDUCE and MPI technologies for solving oil extracting problems. We extend a common architecture of MAPREDUCE ...
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ISBN:
(纸本)9783642399572;9783642399589
This paper describes a constructive approach of distributedparallelcomputing using by hybrid union of MAPREDUCE and MPI technologies for solving oil extracting problems. We extend a common architecture of MAPREDUCE model by organizing decomposition of computational domain at different stages of MAPREDUCE process. We describes Model Driven Architecture (MDA) models for developing formal views of high-performance computing technologies using MAPREDUCE. We made computing experiments and show on specific HPC infrastructure. All implementations of programs is realize on Java platform. This approach will possible one of the ways to do cloud computing on high performance heterogeneous systems.
gridcomputing is the group of computer resources from numerous sites to achieve a common aspiration. The grid can be consideration of as a distributed system with non-interactive workloads that engross a great amount...
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ISBN:
(纸本)9781509037704
gridcomputing is the group of computer resources from numerous sites to achieve a common aspiration. The grid can be consideration of as a distributed system with non-interactive workloads that engross a great amount of files. In gridcomputing, fault tolerance is a major predicament and of the metric which believe being most imperative since the resource failure affects job finishing, throughput, response time and recital of system and network. Fault tolerance in load balancing is individual of the major confront in gridcomputing, which is necessary to dispense the workload uniformly diagonally all the nodes, perceive the fault and eliminate fault from the network and share workload to all the nodes to enlarge the recital of grid network. The load is a quantity of work that computation systems carry out, which can be classified as network load, storage capacity, memory capacity and CPU load. It is essential to build a new proposal for computational grids which hold computational and data intensive applications. The foremost endeavor of this paper is to diminish the implementation time of applications in computational grid. The proposed Load Balanced Fault tolerant (LBFT) architecture using SOA focus on a new dynamic load complementary algorithm beside among fault tolerant scheduling approach through which successful load balancing and fault tolerance have been accomplished.
We propose a MapReduce-based solution approach to solve a large-scale mixed-integer program which optimizes the layout of visual elements on a power transmission display map. We conduct extensive computational studies...
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ISBN:
(纸本)9781728131016
We propose a MapReduce-based solution approach to solve a large-scale mixed-integer program which optimizes the layout of visual elements on a power transmission display map. We conduct extensive computational studies based on a real-world power grid in the U.S. and compare our results with the (traditional) sequential approach, in terms of both accuracy and speed.
In this paper we present a distributed, autonomous network calibration algorithm, which enables visual sensor networks to gather knowledge about the network topology. A calibrated sensor network provides the basis for...
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ISBN:
(纸本)9781538639917
In this paper we present a distributed, autonomous network calibration algorithm, which enables visual sensor networks to gather knowledge about the network topology. A calibrated sensor network provides the basis for more robust applications, since nodes are aware of their spatial neighbors. In our approach, sensor nodes estimate relative positions and orientations of nodes with overlapping fields of view based on jointly detected objects and geometric relations. Distance and angle measurements are the only information required to be exchanged between nodes. The process works iteratively, first calibrating camera neighbors in a pairwise manner and then spreading the calibration information through the network. Further, each node operates within its local coordinate system avoiding the need for any global coordinates. While existing methods mostly exploit computer vision algorithms to relate nodes to each other based on their images, we solely rely on geometric constraints.
In this paper, we present a scalable parallel framework, which employs gridcomputing technologies, for solving computationally expensive and intractable design problems. Using an aerodynamic airfoil design optimizati...
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Performance-to-energy tradeoffs in distributedcomputing are discussed. Performance models are examined. Energy optimization can be reached under use of the advanced technologies like IoT.
ISBN:
(纸本)9786176078067
Performance-to-energy tradeoffs in distributedcomputing are discussed. Performance models are examined. Energy optimization can be reached under use of the advanced technologies like IoT.
Java has in-built support for distributedcomputing. As the first language designed from the bottom up with networking and distributedcomputing in mind, Java makes it easy for computers to cooperate. Students of dist...
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ISBN:
(纸本)1932415262
Java has in-built support for distributedcomputing. As the first language designed from the bottom up with networking and distributedcomputing in mind, Java makes it easy for computers to cooperate. Students of distributedcomputing need adequate exposure to this technology and in order to meet this need the author has put together a course on distributedcomputing which uses Java's support for object-oriented programming, clientserver applications, multithreaded servers, security, and distributed objects. This paper describes this course and the programming projects developed and used in the course. Students developed programming projects using open source, Java based middleware technologies that built on the lectures. The focus of the course and projects was providing students with a clear understanding of the trade-offs involved with the different Java based middleware technologies as they design and implement distributed applications.
Adaptive mesh refinement and iterative traversals of unknowns on such adaptive grids are fundamental building blocks for PDE solvers. We discuss a respective integrated approach for grid refinement and processing of u...
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ISBN:
(纸本)9783642281440;9783642281457
Adaptive mesh refinement and iterative traversals of unknowns on such adaptive grids are fundamental building blocks for PDE solvers. We discuss a respective integrated approach for grid refinement and processing of unknowns that is based on recursively structured triangular grids and space-filling element orders. In earlier work, the approach was demonstrated to be highly memory-and cache-efficient. In this paper, we analyse the cache efficiency of the traversal algorithms using the I/O model. Further, we discuss how the nested recursive traversal algorithms can be efficiently implemented. For that purpose, we compare the memory throughput of respective implementations with simple stream benchmarks, and study the dependence of memory throughput and floating point performance from the computational load per element.
In this paper, we propose real-time depth-image-based rendering (DIBR) on GPU for 1280x720 resolution. We utilize depth adaptive preprocessing and super-resolution to achieve high-quality DIBR. Moreover, we employ GPU...
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ISBN:
(纸本)9781467392006
In this paper, we propose real-time depth-image-based rendering (DIBR) on GPU for 1280x720 resolution. We utilize depth adaptive preprocessing and super-resolution to achieve high-quality DIBR. Moreover, we employ GPU-based parallelcomputing to achieve real-time DIBR. Experimental results demonstrate that the proposed method achieves superior performance in comparison with the existing methods with respect to rendering quality and computing time.
Pattern recognition applications such as natural phenomena detection and structural health monitoring have been widely applied using wireless sensor networks. These applications involve large amount of data to be anal...
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ISBN:
(纸本)9780769534435
Pattern recognition applications such as natural phenomena detection and structural health monitoring have been widely applied using wireless sensor networks. These applications involve large amount of data to be analysed, and thus incur high computational time and complexity In this paper we present a parallel associative memory-based pattern recognition algorithm known as distributed Hierarchical Graph Neuron (DHGN). It is a single-cycle learning algorithm with in-network processing capability;able to reduce computational loads by efficiently disseminates recognition processes throughout the network. Hence, suitable to be deployed in wireless sensor networks. The results of the accuracy and scalability tests show that our system performs with high accuracy and remains scalable for increases in pattern size and the number of stored patterns. The response time for pattern recognition remains within milliseconds irrespective of the size of the network.
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