OpenMP applications executed on top of software distributed shared memory (SDSM) systems show peaks in network traffic. In these scenarios, synchronization points are used to maintain memory consistency and improve pe...
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Large-scale distributedcomputing systems (LDCSs) can be best characterized by their dynamic nature particularly in terms of availability and performance. Typically, these systems deal with various types of jobs in ma...
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Web service composition, i.e., WSC, has emergedas a promising way to integrate various distributedcomputing resources for complex application requirements. However, much computation time is needed to determine the op...
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Collaborative computing involves human actors and artificial agents interacting in a distributed system to resolve a global problem, often formed dynamically during the computation process Owing to the open nature of ...
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ISBN:
(纸本)9783642144028
Collaborative computing involves human actors and artificial agents interacting in a distributed system to resolve a global problem, often formed dynamically during the computation process Owing to the open nature of the system and non-cooperative settings, its computations are in general non-algorithmic i.e their outcome cannot be calculated in advance by any closed distributed system Authors advocate for a new processing model, based on exchange of documents implemented as autonomous and mobile agents, providing adaptive and self-aware content as interface units
CUDA(Compute Unified Device Architecture) acceleration of very large scale matrix-vector and matrix-matrix multiplication is presented in this paper. the intrinsic parallelism in the matrix computations are exploited ...
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the Union-Find algorithm is used for maintaining a number of non-overlapping sets from a finite universe of elements. the algorithm has applications in a number of areas including the computation of spanning trees, sp...
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ISBN:
(纸本)9783642143892
the Union-Find algorithm is used for maintaining a number of non-overlapping sets from a finite universe of elements. the algorithm has applications in a number of areas including the computation of spanning trees, sparse linear algebra, and in image processing. Although the algorithm is inherently sequential there has been some previous efforts at constructing parallel implementations. these have mainly focused on shared memory computers. In this paper we present the first scalable parallel implementation of the Union-Find algorithm suitable for distributed memory computers. Our new parallel algorithm is based on an observation of how the Find part of the sequential algorithm can be executed more efficiently. We show the efficiency of our implementation through a series of tests to compute spanning forests of very large graphs.
the advent of mobile computing devices and development of wireless and ad-hoc networking technologies has led to growth of infrastructure-less environments. Mostly, these environments lie at the edges of Internet i.e....
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Many applications demand distributing data with different contents efficiently in the network environment with unreliable links and a high node churn. Existing approaches mostly focus on optimizing either efficiency o...
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Many large-scale scientific applications feature distributedcomputing workflows of complex structures that must be executed and transferred in shared wide-area networks consisting of unreliable nodes and links. Mappi...
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Energy efficiency represents one of the main challenges in the engineering field. the benefit of the energy efficiency is twofold: the reduction of the cost owing to the energy consumption and the reduction in the ene...
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ISBN:
(纸本)9783642124327
Energy efficiency represents one of the main challenges in the engineering field. the benefit of the energy efficiency is twofold: the reduction of the cost owing to the energy consumption and the reduction in the energy consumption due to a better design minimising the energy losses. this is particularly true in real world processes in the industry or in business, where the elements involved may be considered as distributed agents. Moreover, in some fields like building management systems the data are full of noise and biases, and the emergence of new technologies -as the ambient intelligence can be- degrades the quality data introducing linguistic values. In this contribution we propose the use of the novel genetic fuzzy system approach to obtain classifiers and models able to manage low quality data to improve the enemy efficiency in intelligent distributed systems. We will introduce the problem and some of the challenging fields are to be detailed. Finally, a brief review of methods considering the low quality data is related.
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