Increasingly, feedback of measured run-time information is being used in the optimization of computation execution. This paper introduces a model relating the static view of a computation to its run-time variance that...
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Increasingly, feedback of measured run-time information is being used in the optimization of computation execution. This paper introduces a model relating the static view of a computation to its run-time variance that is useful in this context. A notion of uncertainty is then used to provide bounds on key scheduling parameters of the run-time computation. To illustrate the relationship between fidelity in measured information and minimum schedulable, grain size, we apply the bounds to three existing parallel architectures for the case of run-time variance caused by monitoring intrusion. We also outline a hybrid static-dynamic scheduling paradigm-SEDIA-that uses the model of uncertainty to optimize computation for execution in the presence of run-time variance from sources other than monitoring intrusion.
With the continuous development of quantum technology, entangled signal has been used in more and more fields. Due to the unique temporal-spatial correlation characteristics of entangled signal, it provides promising ...
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In this paper, a robust target localization method based on iterative reweight least squares (IRWLS) is presented to against outliers in distributed MIMO radars. Unlike conventional weight least squares model which de...
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SIMD (single-instruction-stream, multiple-data-stream) architectures require mechanisms that efficiently enable and disable mask processors to support flexible programming. Most current SIMD architectures use local ma...
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SIMD (single-instruction-stream, multiple-data-stream) architectures require mechanisms that efficiently enable and disable mask processors to support flexible programming. Most current SIMD architectures use local masking. Global processor masks, specified by the control unit, are more efficient for tasks where the masking is data independent. An efficient hybrid masking technique that supports global masking, as well as local masking, for SIMD architectures constructed from standard microprocessors is proposed. A design for the hybrid mechanism is described, and its experimental performance using the existing PASM prototype is examined. It is shown that the hybrid masking technique can increase the utilization of PEs and thus increase performance, the degree of improvement being algorithm dependent.< >
By amassing 'wisdom of the crowd', social tagging systems draw more and more academic attention in interpreting Internet folk knowledge. In order to uncover their hidden semantics, several researches have atte...
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Modern power systems are evolving into sociotechnical systems with massive complexity, whose real-time operation and dispatch go beyond human capability. Thus,the need for developing and applying new intelligent power...
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Modern power systems are evolving into sociotechnical systems with massive complexity, whose real-time operation and dispatch go beyond human capability. Thus,the need for developing and applying new intelligent power system dispatch tools are of great practical significance. In this paper, we introduce the overall business model of power system dispatch, the top level design approach of an intelligent dispatch system, and the parallel intelligent technology with its dispatch applications. We expect that a new dispatch paradigm,namely the parallel dispatch, can be established by incorporating various intelligent technologies, especially the parallel intelligent technology, to enable secure operation of complex power grids,extend system operators' capabilities, suggest optimal dispatch strategies, and to provide decision-making recommendations according to power system operational goals.
In this poster, we present an approach to contex-tualized semantic image annotation as an optimization problem. Ontologies are used to capture general and contextual knowledge of the domain considered, and a genetic a...
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In this poster, we present an approach to contex-tualized semantic image annotation as an optimization problem. Ontologies are used to capture general and contextual knowledge of the domain considered, and a genetic algorithm is applied to realize the final annotation. Experiments with images from the beach vacation domain demonstrate the performance of the proposed approach and illustrate the added value of utilizing contextual information.
A framework for estimating the relative execution time of a data-parallel algorithm in an environment capable of the SIMD and SPMD (Single Program - Multiple Data) modes of computation is presented. Given a data-paral...
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