For computations on large-scale graphs, one often resorts to parallel algorithms. However, parallel algorithms are difficult to write, debug and analyze. Worse still, it is difficult to make algorithms parallelly scal...
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For computations on large-scale graphs, one often resorts to parallel algorithms. However, parallel algorithms are difficult to write, debug and analyze. Worse still, it is difficult to make algorithms parallelly scalable, such that the more machines are used, the faster the algorithms run. Indeed, it is not yet known whether any PTIME computational problems admit parallelly scalable algorithms on shared-nothing *** it possible to parallelize sequential graph algorithms and guarantee convergence at the correct results as long as the sequential algorithms are correct? Moreover, does a PTIME parallelly scalable problem exist on shared-nothing systems? This position paper answers both questions in the affirmative.
Learning is a fundamental characteristic of living systems, enabling them to comprehend their environments and make informed decisions. These decision-making processes are inherently influenced by available informatio...
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Secure sum protocol is a significant secure multiparty computation protocol and it has various applications in privacy-preserving distributed multiparty computation. However, most existing secure sum protocols rarely ...
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Secure sum protocol is a significant secure multiparty computation protocol and it has various applications in privacy-preserving distributed multiparty computation. However, most existing secure sum protocols rarely considered how to resist underlying collusion which is a significant practical problem. Urabe et al. proposed a collusion-resistant secure sum protocol, but too much cost of communication and computation results in its low performance efficiency. In this paper, we propose security definitions to measure secure multiparty computation protocol's capability of resisting potential collusion. Then, we precisely analyze several previous secure sum protocols' capability of resisting collusion. In addition, considering realistic requirement to resist collusion and performance efficiency needs, we present a novel collusion-resisting secure sum protocol. Theoretical analysis and experimental results confirm that our secure sum protocol is efficient and has strong capability of resisting potential collusion such that it is much superior to previous ones. The communication overheads and computation complexity of our scheme both are linearity of the number of participants. Besides, our protocol's capability of resisting collusion is adjustable according to different security needs.
This paper is considering issues connected with parallelization of Direct Simulation Monte Carlo (later referred as DSMC). The method is applied to simulate gas flow in micro-channels. The general algorithm of DSMC ca...
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This paper focuses on the minimum delay broadcast problem in two-hop neighborhoods. We divide the process of broadcast into different time slots, and in each time slot we choose one or more nodes to forward. The objec...
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This paper focuses on the minimum delay broadcast problem in two-hop neighborhoods. We divide the process of broadcast into different time slots, and in each time slot we choose one or more nodes to forward. The objective is to minimize the number of time slots. We model it as the Minimum Time-Slot Forwarding (MTSF) problem, and prove that MTSF is NP-hard in general graph, so there is no polynomial time algorithm for MTSF, unless NP⊆P. Two heuristics saying algorithm1 and algorithm2 are proposed to solve MTSF, and theoretical analysis as well as the simulation results shows that the average time slot needed for broadcasting is a linear of In P , where P is the set of two hop neighbors of source node s. We also compare the performance of the heuristics proposed with that of flooding, and the simulation results show that both of them perform better than flooding, especially for algorithm2.
New words could benefit many NLP tasks such as sentence chunking and sentiment analysis. However, automatic new word extraction is a challenging task because new words usually have no fixed language pattern, and even ...
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New words could benefit many NLP tasks such as sentence chunking and sentiment analysis. However, automatic new word extraction is a challenging task because new words usually have no fixed language pattern, and even appear with the new meanings of existing words. To tackle these problems, this paper proposes a novel method to extract new words. It not only considers domain specificity, but also combines with multiple statistical language knowledge. First, we perform a filtering algorithm to obtain a candidate list of new words. Then, we employ the statistical language knowledge to extract the top ranked new words. Experimental results show that our proposed method is able to extract a large number of new words both in Chinese and English corpus, and notably outperforms the state-of-the-art methods. Moreover, we also demonstrate our method increases the accuracy of Chinese word segmentation by 10% on corpus containing new words.
We provide an overview of quantum photonic network on chip. We begin from the discussion of the pros and cons of several material platforms for engineering quantum photonic chips. Then we introduce and analyze the bas...
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We provide an overview of quantum photonic network on chip. We begin from the discussion of the pros and cons of several material platforms for engineering quantum photonic chips. Then we introduce and analyze the basic building blocks and functional units of quantum photonic integrated circuits. In the main part of this review, we focus on the generation and manipulation of quantum states of light on chip and are particularly interested in some applications of advanced integrated circuits with different functionalities for quantum information processing, including quantum communication, quantum computing, and quantum simulation. We emphasize that developing fully integrated quantum photonic chip which contains sources of quantum light, integrate circuits, modulators, quantum storage, and detectors are promising approaches for future quantum photonic technologies. Recent achievements in the large scale photonic chips for linear optical computing are also included. Finally, we illustrate the challenges toward highperformance quantum information processing devices and conclude with promising perspectives in this field.
Frequent itemset mining (FIM) plays an essential role in mining associations, correlations and many other important data mining tasks. Unfortunately, as the volume of dataset gets larger day by day, most of the FIM al...
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Heterogeneity in computing environments is becoming increasingly common. Some consider this a problem, while others (including ourselves) prefer to think of it as a benefit. By exploiting the different features and ca...
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An approximate method for solving the Riemann problem is needed to construct Godunov schemes for relativistic hydrodynamical equations. Such an approximate Riemann solver is presented in this paper which treats all wa...
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An approximate method for solving the Riemann problem is needed to construct Godunov schemes for relativistic hydrodynamical equations. Such an approximate Riemann solver is presented in this paper which treats all waves emanating from an initial discontinuity as themselves discontinuous. Therefore, jump conditions for shocks are approximately used for rarefaction waves. The solver is easy to implement in a Godunov scheme and converges rapidly for relativistic hydrodynamics. The fast convergence of the solver indicates the potential of a higher performance of a Godunov scheme in which the solver is used.
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