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ITRE 2005 - 3rd International Conference on Information Technology: Research and Education

作者： Li, Kuan-Ching Yang, Chao-Tung Parallel and Distributed Processing Center Dept. of Computer Science and Information Management Providence University Shalu Taichung 43301 Taiwan High Performance Computing Laboratory Dept. of Computer Science and Information Engineering Tunghai University Taichung City Taichung 40704 Taiwan

ISBN: (纸本)0780389328

The computing power provided by high performance and low cost PC-based clusters and Grid computing platforms are attractive and they are equal or superior to supercomputers and mainframes. In parallel, discussions on how to obtain more computing power from these computing platforms become an interesting issue. The development of applications for these high-performance computing platforms is complicated for several reasons: The complexity of applications themselves, which combines aspects of supercomputing and distributed computing, and by the need to achieve higher performance. This paper describes the design rationale and implementation of a parallel programming web-based toolkit, to ease the parallel programming learning process, with the use of web-based interface. The toolkit has widely been used in MPI parallel programming courses (both in graduate and undergraduate levels) and industry trainings. © 2005 IEEE.

关键词： Computer programming

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Performance problems online detection in cloud computing systems via analyzing request execution paths

Performance problems online detection in cloud computing sys...

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International Conference on Dependable Systems and Networks Workshops (DSN-W)

作者： Haibo Mi Huaimin Wang Gang Yin Hua Cai Qi Zhou Tingtao Sun National Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha China Computing Platform Alibaba Cloud Computing Company Hangzhou China

It is quite a headache for developers to online detect performance problems in large-scale cloud computing systems. The behavior and the hidden connections among the huge amount of runtime request execution paths in cloud computing systems usually contain useful information for performance problem detection. In this paper, we propose an approach to rapidly diagnose the source of performance degradation in large-scale non-stop cloud computing systems. The approach first groups the user requests into categories with a fast clustering algorithm; then applies the principal components analysis to extract the primary methods; finally compares the normal and abnormal behaviors of the primary methods to localize the main cause of performance problems. We conduct extensive experiments over a real-world enterprise system providing services for the public. The results show that our approach can locate the prime causes of performance problems accurately and efficiently.

关键词： Cloud computing Principal component analysis Instruments Degradation Servers Data mining Accuracy

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Temporal Closing Path for PLM-based Temporal Knowledge Graph Completion

Temporal Closing Path for PLM-based Temporal Knowledge Graph...

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International Joint Conference on Neural Networks (IJCNN)

作者： Xin Zhou Yongxue Shan Zixuan Dong Haijiao Liu Xiaodong Wang National Key Laboratory of Parallel and Distributed Computing College of Computer Science and Technology National University of Denfense Technology Changsha China

ISBN: (数字)9798350359312

ISBN: (纸本)9798350359329

Temporal Knowledge Graph Completion (TKGC) aims to predict missing parts of quadruples, which is crucial for real-life knowledge graphs. Compared with methods that only use graph neural networks, the emergence of pre-trained model has introduced a trend of simultaneously leveraging text and graph structure information. However, most current methods based on pre-trained models struggle to effectively utilize both text and multi-hop graph structure information concurrently, resulting in insufficient association mining of relations. To address the challenge, we propose a novel model: Temporal Closing Path for Pre-trained Language Model-based TKGC (TCP-PLM). We obtain the temporal closing relation path of the target relation through sampling, and use the relation path as a bridge to simultaneously utilize text and multi-hop graph structure information. Moreover, the relation path serves as a tool for mining associations between relations. At the same time, due to the design of entity-independent relation paths, our model can also handle the inductive setting. Our experiments on three benchmarks, along with extensive analysis, demonstrate that our model not only achieves substantial performance enhancements across four metrics compared to other models but also adeptly handles inductive settings.

关键词： Training Measurement Knowledge engineering Bridges Analytical models Knowledge graphs Transforms

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On design of cluster and grid computing environment toolkit for bioinformatics applications∗ 6th

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6th International Workshop on distributed computing, IWDC 2004

作者： Yang, Chao-Tung Kuo, Yu-Lun Li, Kuan-Ching Gaudiot, Jean-Luc High Performance Computing Laboratory Dept. of Computer Science and Information Engineering Tunghai University Taichung40744 Taiwan Parallel and Distributed Processing Center Dept. of Computer Science and Information Management Providence University Taichung43301 Taiwan Parallel and Scalable Computer Architecture Laboratory Dept. of Electrical Engineering and Computer Science University of California – Irvine IrvineCA92697 United States

ISBN: (纸本)9783540240761

In this paper, we present BioGrid, a novel computing resource that combines advantages of grid computing technology with bioinformatics parallel applications. The grid environment permits the sharing of a large amount of idle computing resources and data. The investigation of bioinformatics demands orders of magnitude of computing resources and in parallel, the biological data are growing in such a high speed. By using BioGrid, we plan to integrate and share resources and biological data using the grid computing technology. Still in this paper, the well-known FASTA application is performed as matter of testing and analysis in our grid computing platform, as goal to show the improved efficiency and reduced computation time. © Springer-Verlag Berlin Heidelberg 2004.

关键词： Bioinformatics

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The anatomy of a course in cluster and grid computing

The anatomy of a course in cluster and grid computing

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ITRE 2005 - 3rd International Conference on Information Technology: Research and Education

作者： Yang, Chao-Tung Li, Kuan-Ching High Performance Computing Laboratory Dept. of Computer Science and Information Engineering Tunghai University Taichung City Taichung 40704 Taiwan Parallel and Distributed Processing Center Dept. of Computer Science and Information Management Providence University Shalu Taichung 43301 Taiwan

ISBN: (纸本)0780389328

Cluster and grid computing is a relatively new interdisciplinary field, where computer science, engineering and computational biology as its core supporting disciplines. The rise of cluster and grid computing discipline brings to computer science faculty members new opportunities and challenges, both in education and in research. In this paper, we will explore issues in teaching Cluster and Grid computing, the developing of curricula, and thoughts to foster student to work on research projects in Cluster and Grid computing. © 2005 IEEE.

关键词： Education

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Density estimation with adaptive sparse grids for large data sets 14

Density estimation with adaptive sparse grids for large data...

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14th SIAM International Conference on Data Mining, SDM 2014

作者： Peherstorfer, Benjamin Pflüger, Dirk Bungartz, Hans-Joachim Aerospace Computational Design Laboratory AeroAstro Massachusetts Institute of Technology United States Simulation of Large Systems Group Institute for Parallel and Distributed Systems University of Stuttgart Germany Scientific Computing Group Department of Computer Science Technische Universität München Germany

ISBN: (纸本)9781510811515

Nonparametric density estimation is a fundamental problem of statistics and data mining. Even though kernel density estimation is the most widely used method, its performance highly depends on the choice of the kernel bandwidth, and it can become computationally expensive for large data sets. WTe present an adaptive sparse-grid-based density estimation method which discretizes the estimated density function on basis functions centered at grid points rather than on kernels centered at the data points. Thus, the costs of evaluating the estimated density function are independent from the number of data points. We give details on how to estimate density functions on sparse grids and develop a cross validation technique for the parameter selection. We show numerical results to confirm that our sparse-grid-based method is well-suited for large data sets, and, finally, employ our method for the classification of astronomical objects to demonstrate that it is competitive to current kernel-based density estimation approaches with respect to classification accuracy and runtime. Copyright © SIAM.

关键词： Data mining

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Ruan Jian Xue Bao/Journal of Software 2011年第1期22卷 132-148页

作者： Li, Hui-Ba Tian, Tian Peng, Yu-Xing Li, Dong-Sheng Lu, Xi-Cheng National Laboratory for Parallel and Distributed Computing Computer School National University of Defense Technology Changsha 410073 China Institute of Software Computer School National University of Defense Technology Changsha 410073 China

The Internet has become a vital information infrastructure for modern society. However, the concurrent nature of network introduces a wide-range of difficulties in traditional programming methodology in developing high-quality network programs that significantly reduce productivity. The influence of concurrency on the complexity of software development is comparable to the "concurrency crisis" of software brought by multi-core processors, but it receives much less attention here than what it deserves. There is no universal approach to cope with this issue, and there are even disagreements between different approaches. In this paper, the basic concurrency models and their implementations are introduced, and then the paper surveys the inherent complexities of these approaches, comparing their advantages and disadvantages. Finally, this paper offers an opinion on the possibilities for future research on this topic. © Copyright 2011, Institute of Software, the Chinese Academy of Sciences. All rights reserved.

关键词： Complex networks

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Efficient distributed parallel Aligning Reads and Reference Genome with Many Repetitive Subsequences Using Compact de Bruijn Graph

Efficient Distributed Parallel Aligning Reads and Reference ...

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International Symposium on parallel Architectures, Algorithms and Programming (PAAP)

作者： Yao Li Cheng Zhong Danyang Chen Jinxiong Zhang Mengxiao Yin Key Laboratory of Parallel School of Computer Electronics and Information Distributed Computing Technology in Guangxi Universities Guangxi University Nanning China

ISBN: (纸本)9781665496407

A large number of reads generated by the next generation sequencing platform will contain many repetitive subsequences. Effective localizing and identifying genomic regions containing repetitive subsequences will contribute to the subsequent genomic data analysis. To accelerate the alignment between large-scale short reads and reference genome with many repetitive subsequences, this paper develops a compact de Bruijn graph based short-read alignment algorithm on distributed parallel computing platform. The algorithm uses resilient distributed data sets (RDDS) to perform calculations in memory, and executes the broadcast method to distribute short reads and reference genome to the computing nodes to reduce the data communication time on the cluster system, and the number of RDD partitions is set to optimize the performance of parallel aligning algorithm. Experimental results on real datasets show that compared with the compact de Bruijn graph based sequential short-read alignment algorithm, our implemented distributed parallel alignment algorithm achieves good acceleration on the premise of obtaining the same correct alignment percentage as a whole, and compared with existing distributed parallel alignment algorithms, the implemented parallel algorithm can more quickly complete the alignment between large-scale short reads and reference genome with highly repetitive subsequences.

关键词： Sequential analysis Genomics Clustering algorithms distributed databases Programming Partitioning algorithms parallel architectures

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Identifying faults in large-scale distributed systems by filtering noisy error logs

Identifying faults in large-scale distributed systems by fil...

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International Conference on Dependable Systems and Networks Workshops (DSN-W)

作者： Xiang Rao Huaimin Wang Dianxi Shi Zhenbang Chen Hua Cai Qi Zhou Tingtao Sun National Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha China Computing Platform Alibaba Cloud Computing Corporation Hangzhou China

Extracting fault features with the error logs of fault injection tests has been widely studied in the area of large scale distributed systems for decades. However, the process of extracting features is severely affected by a large amount of noisy logs. While the existing work tries to solve the problem by compressing logs in temporal and spatial views or removing the semantic redundancy between logs, they fail to consider the co-existence of other noisy faults that generate error logs instead of injected faults, for example, random hardware faults, unexpected bugs of softwares, system configuration faults or the error rank of a log severity. During a fault feature extraction process, those noisy faults generate error logs that are not related to a target fault, and will strongly mislead the resulted fault features. We call an error log that is not related to a target fault a noisy error log. To filter out noisy error logs, we present a similarity-based error log filtering method SBF, which consists of three integrated steps: (1) model error logs into time series and use haar wavelet transform to get the approximate time series; (2) divide the approximate time series into sub time series by valleys; (3) identify noisy error logs by comparing the similarity between the sub time series of target error logs and the template of noisy error logs. We apply our log filtering method in an enterprise cloud system and show its effectiveness. Compared with the existing work, we successfully filter out noisy error logs and increase the precision and the recall rate of fault feature extraction.

关键词： Time series analysis Noise measurement Feature extraction Wavelet transforms Computer crashes Complexity theory Approximation methods

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An efficient local address generation for the block-cyclic distribution 3

An efficient local address generation for the block-cyclic d...

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3rd International Conference on Algorithms and Architectures for parallel Processing, ICA3PP 1997

作者： Kwon, Oh-Young Kim, Tae-Geun Han, Tack-Don Yang, Sung-Bong Kim, Shin-Dug Distributed Computing Lab. Systems Engineering Research Institute 1 Ueun-dong Yusong-gu Taejon305-333 Korea Republic of Parallel Processing System Laboratory Dept. of Computer Science Yonsei University Seoul120-749 Korea Republic of

ISBN: (纸本)0780342291

In order to generate local addresses for an array section A(l:h:s) with block-cyclic distribution, an efficient compiling method is required. In this paper, two local address generation methods for the block-cyclic distribution are presented. One is a simple local address generation method that is modified from the virtual-block scheme. The other is a linear-time ΔM table construction method. The array elements of A(l:h:s) to be accessed at run-time build up a family of lines. By using the equation of the lines, a ΔM table can be generated in O(k) time. Experimental results show that a simple local address generation method has poor performance but a linear-time ΔM table generation method is faster than other algorithms in ΔM table generation time and access time for 10,000 array elements. © 1997 IEEE.

关键词： Virtual addresses

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