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international symposium on parallel architectures, algorithms and programming (PAAP)

作者： Yeh-Cheng Chen Shyhtsun Felix Wu Department of Computer Science University of Califonia Davis Davis California

ISBN: (纸本)9781538694046;9781538694039

Online social network is playing an important role in modern society. It not only significantly changed the way people communicate, but also provided a new way of potential attack, such as identity theft, false information, etc. Recently, fake accounts in online social networks (OSNs) have made several problems throughout online social network. With the massive creation of fake account, OSNs providers are suffered by overflooded advertisement, false information spread, etc. Traditional method such as cannot distinguish between real and fake account efficiently. Some previous work has studied the structure and composition of fake account that distribute spam messages, however the fast improvement of fake account creation made these previous works outdated or getting ineffective. We then target on new model of fake account that may not only automatically post or comment, but also spam with advertisement or spread false information. In this research, we proposed an innovative method to detect fake account in OSNs. This method based on user activity pattern through Facebook activities, and we leverage machine learning to predict if an account is controlled by fake user. We also provide an analysis of those account activity from the prediction result. This research may bring up to a whole new level in fake accounts detection.

关键词： parallel architectures programming

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NCIC's research and development in parallel processing

NCIC's research and development in parallel processing

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international symposium on parallel architectures, algorithms and Networks (ISPAN)

作者： Guo-Jie Li National Research Center of Intelligent Computer Systems China

ISBN: (纸本)0818665076

National Research Center for Intelligent Computing Systems (NCIC) is the unique national hi-tech R/D center for advanced computing technology in China. We introduce China's Hi- Tech R&D Programme (863 programmes) and NCIC, and we report on the state of the art of parallel processing at NCIC. The article discusses the key technologies being exploited by the representative Chinese R & D teams and the wide applications of parallel computers in China. The key technologies in parallel processing we are attacking are reported and include wormhole routing and other efficient switching techniques, the Easter series, MPP systems, the Dawning series symmetric and multi-thread multiprocessor, parallel operating systems and parallel file systems, parallel compilers and efficient programming tools. Future research directions at NCIC are also mentioned.< >

关键词： Research and development parallel processing Intelligent systems Application software Computer applications Concurrent computing Routing Operating systems File systems Program processors

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Java internet computing environment with effective configuration method

Proceedings of the International Symposium on Parallel Archi...

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Proceedings of the international symposium on parallel architectures, algorithms and Networks, I-SPAN 1999年 42-47页

作者： Chung, Chun-Mok Shin, Pil-Sup Kim, Shin-Dug LG Information & Communications Ltd Seoul Korea Republic of

For an effective Internet-based distributed parallel computing platform, Java-Internet Computing Environment (JICE) is designed and implemented with multithreading and remote method invocation mechanisms provided in Java. Specifically, JICE supports a shared memory system model for communication between any two nodes. Under the JICE, communication time is a major candidate of performance bottleneck. To reduce this communication overhead, a method of grouping is designed based on the optimal communication time. Communication performance given by grouping is evaluated through the analysis of execution time and verified via experiments. The results show that communication time can be reduced about 80% from executing some Java benchmarks on JICE.

关键词： Java programming language

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Multi-selection Attention for Multimodal Aspect-level Sentiment Classification

Multi-selection Attention for Multimodal Aspect-level Sentim...

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international symposium on parallel architectures, algorithms and programming (PAAP)

作者： Yuqing Miao Ronghai Luo Tonglai Liu Wanzhen Zhang Guoyong Cai Ming Zhou School of Computer Science and Information Security Guilin University of Electronic Technology Guilin China College of Information Science and Technology Zhongkai University of Agriculture and Engineering Guangzhou China Guilin Hivision Technology Company Guilin China

ISBN: (纸本)9781665452199

Multimodal aspect-level sentiment classification aims to utilize images to recognize the sentiment polarity of target aspects in text. To address the issues of low utilization of inter-modal complementary information and vanishing gradients, a multimodal aspect-level sentiment based on multi-selection attention mechanism is proposed. Multi-selection attention mechanism explicitly considers the contribution of different modalities to aspects and utilizes shared features and private features of image modality to enhance sentiment expression of target aspects. On this basis, inspired by residual connections in ResNet and encoder-decoders in U-Net, a simple and effective residual encoder-decoder is proposed to mine deep information and avoid vanishing gradients. The experimental results on two public sentiment datasets show that the proposed model can better utilize images to supplement textual modality and improve the accuracy of sentiment classification.

关键词： Deep learning Image recognition Text recognition Target recognition Bit error rate programming parallel architectures

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Energy-aware Preprocessing for Distributed Training in D2D Edge Network with Non-iid Data

Energy-aware Preprocessing for Distributed Training in D2D E...

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international symposium on parallel architectures, algorithms and programming (PAAP)

作者： Jiaxin Wu Jigang Wu Long Chen Yifei Sun School of Computer Science and Technology Guangdong University of Technology Guangzhou China

ISBN: (纸本)9781665496407

Inherent non-iid characteristic of heterogeneous devices' local dataset slows down the model training process and decreases the training accuracy. To tackle this problem, we propose a dataset reconstruction scheme to transform training device's non-iid dataset into iid dataset via data exchange among trusted devices. Two data exchange modes are proposed to serve the scheme. Considering the transmission overhead, we formulate an optimization problem named NORS to minimize the total energy consumption of devices. We then design an approximation algorithm named X-GTR to obtain a near-optimal auxiliary devices set for dataset reconstruction, while meeting the variance constraint of NORS. For comparison, we propose a baseline algorithm that randomly selects auxiliary devices for dataset reconstruction. Numerical results show that, with the total number of devices increasing, our proposed algorithm outperforms baseline algorithm on reducing energy consumption.

关键词： Training Energy consumption Simulation Distributed databases Transforms programming Approximation algorithms

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Optimal loop scheduling with register constraints using flow graphs

Optimal loop scheduling with register constraints using flow...

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international symposium on parallel architectures, algorithms and Networks (ISPAN)

作者： J. Muller D. Fimmel R. Merker Department of Electrical Engineering Dresden University of Technology Dresden Germany

We present a novel loop scheduling approach using a generalized flow graph model of the resource constraints. From this model we derive a new flow graph to incorporate register constraints. Our linear programming implementation produces an optimum loop schedule, respecting the constraints on functional units and registers in a single optimization problem. Moreover, the iteration interval is treated as a rational number, and the approach supports heterogeneous processor architectures and pipelined functional units. Compared to earlier approaches, the solution can reduce the problem complexity and solution time, and provide faster loop schedules.

关键词： Flow graphs Registers Resource management Intelligent networks parallel architectures Digital filters Delay Adders Writing Pipelines

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An Efficient Ambient Noise Cross-Correlation Algorithm on Heterogeneous CPU-GPU Cluster

An Efficient Ambient Noise Cross-Correlation Algorithm on He...

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international symposium on parallel architectures, algorithms and programming (PAAP)

作者： Chao Wu Xing Tan Huikun Li Guangzhong Sun Network and Information Center Supercomputing Center University of Science and Technology of China Hefei China School of Earth and Space Sciences University of Science and Technology of China Hefei China School of Software Engineering University of Science and Technology of China Hefei China School of Computer Science and Technology University of Science and Technology of China Hefei China

ISBN: (纸本)9781665452199

Calculation of noise cross-correlation functions (NCF) plays a vital role in ambient noise seismology. However high computation and storage requirements of NCF become huge obstacles in development of ambient noise seismology. Nowadays heterogeneous clusters show great impact in scientific computing. In this paper, we propose a parallel NCF algorithm based on heterogeneous cluster. Firstly, input SAC files are partitioned by dimension of dates and distributed to different nodes of heterogeneous cluster. Secondly, during NCF computation in each node, workloads are divided by station pairs, and calculated in different graphics processing units (GPUs) embedded in computing node. Finally, all NCF results of different dates are gathered to one computing node and stacked using all central processing units (CPUs) of that node. Experimental results demonstrate that the parallel NCF computing can be accomplished within much less time than that of the CPU counterpart, and the speedup remains almost linear when increasing number of computing nodes.

关键词： Correlation Scientific computing Seismology Clustering algorithms Graphics processing units programming parallel processing

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parallel Accelerating Ultra-Long Read Alignment by Vertical Partitioning Data

Parallel Accelerating Ultra-Long Read Alignment by Vertical ...

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international symposium on parallel architectures, algorithms and programming (PAAP)

作者： Deng Pan Cheng Zhong Danyang Chen Jinxiong Zhang Feng Yang School of Computer Electronics and Information Key Laboratory of Parallel Distributed Computing Technology in Guangxi Universities Guangxi University Nanning Guangxi China School of Computer Electronics and Information Key Laboratory of Parallel Distributed Computing Guangxi University Nanning Guangxi China

ISBN: (纸本)9781665452199

The alignment between sequencing reads and genome is a basic work in biological big data analysis. Each read of the third generation sequencing data is getting longer, and the data size is getting larger. To effectively solve the ultra-long read alignment problem with high requirements for computing and memory capacity, a strategy for vertical partitioning ultra-long reads on hybrid CPU/GPU cluster is proposed, and a heap data structure is used to filter the local aligned results in all computing nodes of the parallel cluster system according to the alignment score to reduce the data transmission size. The methods for early termination and parallel merging-splicing are used to accelerate splicing local aligned results. The local aligned results among all computing nodes are collected and extended to obtain the final alignment results. The experimental results on datasets of simulated and real ultra-long reads show that the proposed parallel alignment algorithm can obtain high alignment accuracy, sensitivity and base-level sensitivity as a whole, and accelerate completing alignment between ultra-long reads and reference genome.

关键词： Sequential analysis Sensitivity Splicing Merging Memory management Genomics programming

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A Heuristic SAT Problems Solving Method based on LSTM Network

A Heuristic SAT Problems Solving Method based on LSTM Networ...

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international symposium on parallel architectures, algorithms and programming (PAAP)

作者： Yichuan Wang Xiaolong Liang Xinhong Hei Lei Zhu Wenjiang Ji College of Computer Science and Engineering Xi'an University of Technology Xi'an China

ISBN: (纸本)9781665496407

Boolean Satisfiability Problem(SAT) is a well known determination Problem. *** proved in 1971 that SAT Problem is the first NP-Complete (NPC) Problem in the world, namely, any non-deterministic Polynomial (NP) Problem can be specified with the SAT Problem for solving in Polynomial time. Therefore, Boolean satisfiability problem (SAT) can be extended to many practical applications, such as integrated circuit design optimization, biological genes, artificial intelligence, Internet, etc. And there are a lot of NP problems in cryptography. Therefore, the study of SAT Problem is of great significance to cryptography. In this paper, we design a heuristic SAT solving algorithm based on LSTM (Long Short-Term Memory) recurrent neural networks. First of all, based on LSTM, we train the model as an end-to-end SAT Solver, which can output 0 or 1 to represent the satisfiability of each SAT problem. Then we extract the high-dimensional output of the LSTM network and carry out k-means clustering analysis. Finally, we assign the obtained results as the initial value of the variables of the SAT problem, and inspire two types of classical algorithms (complete algorithm and incomplete algorithm) to solve the SAT problem respectively, so as to accelerate the solving process. In the experiment, we demonstrated the test results of SAT problems with different sizes, and The results show that the LSTM-WalkSAT and LSTM-DPLL based heuristic SAT solving methods can significantly improve the solving efficiency of the original complete or incomplete SAT solving algorithms.

关键词： Integrated circuit synthesis Recurrent neural networks Heuristic algorithms Clustering algorithms programming parallel architectures Internet

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Explicit parallel structuring for rule-based programming

Explicit parallel structuring for rule-based programming

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international symposium on parallel Processing

作者： S. Wu J.C. Browne Department of Computer Sciences University of Texas Austin Austin TX USA

This paper presents semantically-based explicit parallel structuring for rule-based programming systems. Explicit parallel structuring appears to be necessary since compile-time dependency analysis of sequential programs has not yielded large scale parallelism and run-time analysis for parallelism is restricted by the execution cost of the analysis. Simple language extensions specifying semantics of rules are used to define parallel execution behavior at the rule level. Type definitions for working memory elements are extended to include relationships within and among objects which define the parallelism allowed on instances of object types. The first result presented is that the algorithms implemented by commonly used benchmark rule-based programs contain scalable parallelism. The second result is that much of that parallelism can be captured by simple and modest extensions of rule-based languages which are analogies of models and constructs used for specification of parallel structures in imperative programming languages. A sketch is given for a comprehensive language system which exploits specification of semantics defining parallel structures in both object-definition and executable segments of rule-based programs.< >

关键词： parallel programming parallel processing Large-scale systems Partitioning algorithms Algorithm design and analysis Computational modeling Runtime Costs Concurrent computing Production systems

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