Nowadays, more and more scientific applications are moving to cloud computing. The optimal deployment of scientific applications is critical for providing good services to users. Scientific applications are usually to...
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Nowadays, more and more scientific applications are moving to cloud computing. The optimal deployment of scientific applications is critical for providing good services to users. Scientific applications are usually topology-aware applications. Therefore, considering the topology of a scientific application during the development will benefit the performance of the application. However, it is challenging to automatically discover and make use of the communication pattern of a scientific application while deploying the application on cloud. To attack this challenge, in this paper, we propose a framework to discover the communication topology of a scientific application by pre-execution and multi-scale graph clustering, based on which the deployment can be optimized. Comprehensive experiments are conducted by employing a well-known MPI benchmark and comparing the performance of our method with those of other methods. The experimental results show the effectiveness of our topology-aware deployment method.
The availability of computers and communication networks allows us to gather and analyse data on a far larger scale than previously. At present, it is believed that statistics is a suitable method to analyse networks ...
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The availability of computers and communication networks allows us to gather and analyse data on a far larger scale than previously. At present, it is believed that statistics is a suitable method to analyse networks with millions, or more, of vertices. The MATLAB language, with its mass of statistical functions, is a good choice to rapidly realize an algorithm prototype of complex networks. The performance of the MATLAB codes can be further improved by using graphic processor units (GPU). This paper presents the strategies and performance of the GPU implementation of a complex networks package, and the Jacket toolbox of MATLAB is used. Compared with some commercially available CPU implementations, GPU can achieve a speedup of, on average, 11.3x. The experimental result proves that the GPU platform combined with the MATLAB language is a good combination for complex network research.
Many real-world networks are found to be scale-free. However, graph partition technology, as a technology capable of parallel computing, performs poorly when scale-free graphs are provided. The reason for this is that...
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Many real-world networks are found to be scale-free. However, graph partition technology, as a technology capable of parallel computing, performs poorly when scale-free graphs are provided. The reason for this is that traditional partitioning algorithms are designed for random networks and regular networks, rather than for scale-free networks. Multilevel graph-partitioning algorithms are currently considered to be the state of the art and are used extensively. In this paper, we analyse the reasons why traditional multilevel graph-partitioning algorithms perform poorly and present a new multilevel graph-partitioning paradigm, top down partitioning, which derives its name from the comparison with the traditional bottom-up partitioning. A new multilevel partitioning algorithm, named betweenness-based partitioning algorithm, is also presented as an implementation of top-down partitioning paradigm. An experimental evaluation of seven different real-world scale-free networks shows that the betweenness-based partitioning algorithm significantly outperforms the existing state-of-the-art approaches.
We consider the maximal vector problem on uncertain data, which has been recently posed by the study on processing skyline queries over a probabilistic data stream in the database context. Let D n be a set of n points...
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We consider the maximal vector problem on uncertain data, which has been recently posed by the study on processing skyline queries over a probabilistic data stream in the database context. Let D n be a set of n points in a d-dimensional space and q (0 < q 1) be a probability threshold; each point in D n has a probability to occur. Our problem is concerned with how to estimate the expected size of the probabilistic skyline, which consists of all the points that are not dominated by any other point in D n with a probability not less than q. We prove that the upper bound of the expected size is O(min{n, (- ln q)(ln n) d-1 }) under the assumptions that the value distribution on each dimension is independent and the values of the points along each dimension are distinct. The main idea of our proof is to find a recurrence about the expected size and solve it. Our results reveal the relationship between the probability threshold q and the expected size of the probabilistic skyline, and show that the upper bound is poly-logarithmic when q is not extremely small.
Multi-island single electron transistor is an important kind of the single electron transistor, which is convenient to realize the controllable room temperature operation. A novel semi-empirical compact model for the ...
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ISBN:
(纸本)9781424435449
Multi-island single electron transistor is an important kind of the single electron transistor, which is convenient to realize the controllable room temperature operation. A novel semi-empirical compact model for the Multi-island single electron transistor is proposed. The new approach combines the orthodox theory of the single electron tunneling through single coulomb island and a novel empirical analysis procedure for the chain of multi coulomb islands to solve the current of the whole multi-island single electron transistor. The tunneling rates are calculated based on the orthodox theory for the single electron tunneling. The tunneling currents representing the first splitted peaks in the coulomb oscillation curves are calculated according to the assumption that the currents through all the coulomb islands are equal to each other at the stable states, while the currents representing the other splitted peaks are constructed and merged together according to the empirical analysis. The model is verified by the traditional SET simulator SIMON and shows much faster calculation speed than SIMON. Therefore, the novel compact model is suitable for the large scale MISET circuit simulation.
The reliability issue of Exascale system is extremely serious. Traditional passive fault-tolerant methods, such as rollback-recovery, can not fully guarantee system reliability any more because of their large executin...
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Constant degree peer-to-peer (P2P) system is turning into the P2P domain's promising hotspot due to constant degree digraphs having good propertis. However, it is often hard to convert a stardard constant degree d...
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Constant degree peer-to-peer (P2P) system is turning into the P2P domain's promising hotspot due to constant degree digraphs having good propertis. However, it is often hard to convert a stardard constant degree digraph to a DHT schema. Thus, most researches focus on DHT's construction and maintenance, while leaving optimization and supporting to complex query behind. Underlying topology affects upper-layers' character a lot. For constant degree P2P topologies, their inherent property makes a constant degree P2P system built using classical technique be poor in the data locality, and unfit for efficient, low-cost complex queries. Aiming at this shortage, a general-purpose construction technique towards efficient complex queries is proposed, which adds an embedding transformation layer between data layer and DHT overlay. In this way, adjacent data are stored in overlay's adjacent peers and the data locality is improved, so that the number of peers referred in complex queries can be minimized with a limited time overhead. To validate this technology, the first constant degree P2P system based on Kautz digraph FissionE is reconstructed as a typical example, which includes re-allocating of resources, query algorithm and locality maintenance strategies. Experimental results show that this construction technique can ensure data locality, reduce query cost and lead to systems' efficiency without changing the underlying DHT layer.
The development of multi-core processor makes the parallelization of traditional sequential algorithms increasingly important. Meanwhile, transactional memory serves a good parallel programming model. This paper takes...
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A Cloud may be seen as a type of flexible computing infrastructure consisting of many compute nodes, where resizable computing capacities can be provided to different customers. To fully harness the power of the Cloud...
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When a large-scale distributed interactive simulation system is running on WAN, the sites usually disperse over a wide area in geography, which results in the simulation clock of each site is hardly to be accurately s...
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