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Grid architecture is a fast evolving distributed computing architecture.
CMS is actively involved in several grid-related projects to develop and deploy a fully distributed computing architecture.
To study how to explore valuable information among multimedia big data with low complexity, this paper proposes an object detection method of big data, which is in compressive measurement domain under a mobile distributed computing architecture.
Applying a distributed computing architecture to sample nearly 5000 complete tRNA folding events using a minimalist, atomistic model, we have characterized the role of native topology in tRNA folding dynamics: the simulated bulk folding behavior predicts well the experimentally observed folding mechanism.
Therefore, sequence alignment tools based on parallel and distributed computing architecture evolved as the best option for bioinformaticians.
In this paper, we propose a distributed computing architecture for running ICA across networked processors, depicted in Fig. 3.
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The proposed approach results in a modular control scheme which simplifies application to multibody systems with a large number of links, reduces the required computational burden, and allows efficient implementation on distributed computing architectures.
BLB is well suited to modern parallel and distributed computing architectures and furthermore retains the generic applicability and statistical efficiency of the bootstrap.
However the end of Moores law and the shift towards distributed computing architectures presents many new challenges for building and executing such applications in a scalable fashion.
In this paper we review the state-of-the-art in distributed particle filtering and propose a method that is applicable to distributed computing architectures.
Large-scale simulations of multidimensional unsteady reacting flows with detailed chemistry and transport can be computationally extremely intensive even on distributed computing architectures.
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