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International Joint Conference on Neural Networks

作者： Long Lan Naiyang Guan Xiang Zhang Dacheng Tao Zhigang Luo Science and Technology on Parallel and Distributed Processing Laboratory School of Computer Science National University of Defense Technology Centre for Quantum Computation & Intelligent Systems and the Faculty of Engineering and Information Technology University of Technology

ISBN: (纸本)9781479914821

Semi-supervised clustering aims at boosting the clustering performance on unlabeled samples by using labels from a few labeled samples. Constrained NMF (CNMF) is one of the most significant semi-supervised clustering methods, and it factorizes the whole dataset by NMF and constrains those labeled samples from the same class to have identical encodings. In this paper, we propose a novel soft-constrained NMF (SCNMF) method by softening the hard constraint in CNMF. Particularly, SCNMF factorizes the whole dataset into two lower-dimensional factor matrices by using multiplicative update rule (MUR). To utilize the labels of labeled samples, SCNMF iteratively normalizes both factor matrices after updating them with MURs to make encodings of labeled samples close to their label vectors. It is therefore reasonable to believe that encodings of unlabeled samples are also close to their corresponding label vectors. Such strategy significantly boosts the clustering performance even when the labeled samples are rather limited, e.g., each class owns only a single labeled sample. Since the normalization procedure never increases the computational complexity of MUR, SCNMF is quite efficient and effective in practices. Experimental results on face image datasets illustrate both efficiency and effectiveness of SCNMF compared with both NMF and CNMF.

关键词： Matrix decomposition Encoding Vectors Clustering methods Clustering algorithms Time complexity Face

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Box-constrained Projective Nonnegative Matrix Factorization via Augmented Lagrangian Method

Box-constrained Projective Nonnegative Matrix Factorization ...

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International Joint Conference on Neural Networks

作者： Xiang Zhang Naiyang Guan Long Lan Dacheng Tao Zhigang Luo Science and Technology on Parallel and Distributed Processing Laboratory School of Computer Science National University of Defense Technology Centre for Quantum Computation & Intelligent Systems and the Faculty of Engineering and Information Technology University of Technology

ISBN: (纸本)9781479914821

Projective non-negative matrix factorization (PNMF) projects a set of examples onto a subspace spanned by a non-negative basis whose transpose is regarded as the projection matrix. Since PNMF learns a natural parts-based representation, it has been successfully used in text mining and pattern recognition. However, it is non-trivial to analyze the convergence of the optimization algorithms for PNMF because its objective function is non-convex. In this paper, we propose a Box-constrained PNMF (BPNMF) method to overcome this deficiency of PNMF. In particular, BPNMF introduces an auxiliary variable, i.e., the coefficients of examples, and incorporates the following two types of constraints: 1) each entry of the basis is non-negative and upper-bounded, i.e., box-constrained, and 2) the coefficients equal to the projected points of the examples. The first box constraint makes the basis to be bound and the second equality constraint keeps its equivalence to PNMF. Similar to PNMF, BPNMF is difficult because the objective function is non-convex. To solve BPNMF, we developed an efficient algorithm in the frame of augmented Lagrangian multiplier (ALM) method and proved that the ALM-based algorithm converges to local minima. Experimental results on two face image datasets demonstrate the effectiveness of BPNMF compared with the representative methods.

关键词： Accuracy Linear programming Training Convergence Optimization Face Educational institutions

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distributed computing and modeling & simulation: Speeding up simulations and creating large models 11

Distributed computing and modeling & simulation: Speeding up...

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Simulation Winter Conference

作者： Simon J. E. Taylor Mohammadmersad Ghorbani Navonil Mustafee Stephen J. Turner Tamas Kiss Daniel Farkas Shane Kite Steffen Straßburger ICT Innovation Group School of Information Systems Computing and Mathematics Brunei University Uxbridge UK Centre for Parallel Computing University of Westminster London UK School of Business and Economics Swansea University Swansea UK Upper Courtyard Saker Solutions Alcester UK Parallel & Distributed Computing Centre School of Computer Engineering Nanyang Technological University Singapore Singapore School of Economic Sciences Ilmenau University of Technology Ilmenau Germany

distributed computing has many opportunities for Modeling and Simulation (M&S). Grid computing approaches have been developed that can use multiple computers to reduce the processing time of an application. In terms of M&S this means simulations can be run very quickly by distributing individual runs over locally or remotely available computing resources. distributed simulation techniques allow us to link together models over a network enabling the creation of large models and/or models that could not be developed due to data sharing or model reuse problems. Using real-world examples, this advanced tutorial discusses how both approaches can be used to benefit M&S researchers and practitioners alike.

关键词： Computational modeling Biological system modeling Data models Educational institutions computers Grid computing Software

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Deep Isolation Forest for Anomaly Detection

arXiv

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arXiv 2022年

作者： Xu, Hongzuo Pang, Guansong Wang, Yijie Wang, Yongjun The College of Computer National University of Defense Technology Changsha410073 China The Science and Technology on Parallel and Distributed Processing Laboratory China The School of Computing and Information Systems Singapore Management University 178902 Singapore

Isolation forest (iForest) has been emerging as arguably the most popular anomaly detector in recent years due to its general effectiveness across different benchmarks and strong scalability. Nevertheless, its linear axis-parallel isolation method often leads to (i) failure in detecting hard anomalies that are difficult to isolate in high-dimensional/non-linear-separable data space, and (ii) notorious algorithmic bias that assigns unexpectedly lower anomaly scores to artefact regions. These issues contribute to high false negative errors. Several iForest extensions are introduced, but they essentially still employ shallow, linear data partition, restricting their power in isolating true anomalies. Therefore, this paper proposes deep isolation forest. We introduce a new representation scheme that utilises casually initialised neural networks to map original data into random representation ensembles, where random axis-parallel cuts are subsequently applied to perform the data partition. This representation scheme facilitates high freedom of the partition in the original data space (equivalent to non-linear partition on subspaces of varying sizes), encouraging a unique synergy between random representations and random partition-based isolation. Extensive experiments show that our model achieves significant improvement over state-of-the-art isolation-based methods and deep detectors on tabular, graph and time series datasets;our model also inherits desired scalability from iForest. © 2022, CC BY.

关键词： Anomaly detection

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Fault-intolerance of reconfigurable systolic arrays

Fault-intolerance of reconfigurable systolic arrays

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International Symposium on Fault-Tolerant computing (FTCS)

作者： A. Nayak N. Santoro R. Tan Center for Parallel & Distributed Computing School of Computer Science Carleton University Ottawa Canada Istituto di Scienze dell Informasione Universite di Bari Bari Italy Department of Computer Sciences University of Utrecht Utrecht Netherlands

Identification, characterization, and construction of fault patterns that are catastrophic for linear systolic arrays are discussed. It is shown that for a given link configuration in the array, it is possible to identify all PE (processing element) catastrophic fault patterns. The requirement on the minimum number of faults in a fault pattern and its spectrum (spread out) for it to be catastrophic is shown to be a function of the length of the longest bypass link available, and not of the total number of bypass links. The paper also gives bounds on the width of a catastrophic fault spectrum.< >

关键词： Systolic arrays Circuit faults Redundancy Fault tolerance computer science Fault diagnosis distributed computing Concurrent computing parallel processing Pipeline processing

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Synchronizing the timestamps of concurrent events in traces of hybrid MPI/OpenMP applications

Synchronizing the timestamps of concurrent events in traces ...

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作者： Becker, Daniel Geimer, Markus Rabenseifner, Rolf Wolf, Felix German Research School for Simulation Sciences Laboratory for Parallel Programming 52062 Aachen Germany RWTH Aachen University Department of Computer Science 52056 Aachen Germany Forschungszentrum Jülich Jülich Supercomputing Centre 52428 Jülich Germany University of Stuttgart High Performance Computing-Center 70550 Stuttgart Germany

ISBN: (纸本)9780769542201

Event traces are helpful in understanding the performance behavior of parallel applications since they allow the indepth analysis of communication and synchronization patterns. However, the absence of synchronized clocks on most cluster systems may render the analysis ineffective because inaccurate relative event timings may misrepresent the logical event order and lead to errors when quantifying the impact of certain behaviors or confuse the users of time-line visualization tools by showing messages flowing backward in time. In our earlier work, we have developed a scalable algorithm that eliminates inconsistent inter-process timings postmortem in traces of pure MPI applications. Since hybrid programming, the combination of MPI and OpenMP in a single application, is becoming more popular on clusters in response to rising numbers of cores per chip and widening shared-memory nodes, we present an extended version of the algorithm that in addition to message-passing event semantics also preserves and restores shared-memory event semantics. © 2010 IEEE.

关键词： Message passing

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Energy-aware data processing techniques for wireless sensor networks: A review

Energy-aware data processing techniques for wireless sensor ...

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3rd International Conference on Data Management in Grid and Peer-to-Peer Systems, Globe 2010

作者： Chong, Suan Khai Gaber, Mohamed Medhat Krishnaswamy, Shonali Loke, Seng Wai Centre for Distributed Systems and Software Engineering Monash University 900 Dandenong Rd Caulfield EastVIC3145 Australia School of Computing University of Portsmouth Portsmouth HampshirePO1 3HE United Kingdom Department of Computer Science and Computer Engineering La Trobe University VIC3086 Australia

ISBN: (纸本)9783642230738

Extensive data generated by peers of nodes in wireless sensor networks (WSNs) needs to be analysed and processed in order to extract information that is meaningful to the user. Data processing techniques that achieve this goal on sensor nodes are required to operate while meeting resource constraints such as memory and power to prolong a sensor network’s lifetime. This survey serves to provide a comprehensive examination of such techniques, enabling developers of WSN applications to select and implement data processing techniques that perform efficiently for their intended WSN application. It presents a general analysis of the issue of energy conservation in sensor networks and an up-to-date classification and evaluation of data processing techniques that have factored in energy constraints of sensors. © Springer-Verlag Berlin Heidelberg 2011.

关键词： Sensor nodes

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GIRAFFE: A scalable distributed coordination service for large-scale systems

GIRAFFE: A scalable distributed coordination service for lar...

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IEEE International Conference on Cluster computing

作者： Xuanhua Shi Haohong Lin Hai Jin Bing Bing Zhou Zuoning Yin Sheng Di Song Wu Services Computing Technology and System Lab School of Computer Science and Technology Huazhong University of Science and Technology Centre for Distributed and High Performance Computing School of Information Technologies University of Sydney GraphSQL Inc. INRIA and Argonne National Laboratory

ISBN: (纸本)9781479955497

The scale of cloud services keeps increasing over time, significantly introducing huge challenges in system manageability and reliability. Designing coordination services in cloud is the right track to solve the above problems. However, existing coordination services (e.g., Chubby and ZooKeeper) only perform well in read-intensive scenario and small ensemble scales. To this end, we propose Giraffe, a scalable distributed coordination service. There are three important contributions in our design. (1) Giraffe organizes coordination servers using interior-node-disjoint trees for better scalability. (2) Giraffe employs a novel Paxos protocol for strong consistency and fault-tolerance. (3) Giraffe supports hierarchical data organization and in-memory storage for high throughput and low latency. We evaluate Giraffe on a high performance computing test-bed. The experimental results show that Giraffe gains much better write performance than ZooKeeper when server ensemble is large. Giraffe is nearly 300% faster than ZooKeeper on update operations when ensemble size is 50 servers. Experiments also show that Giraffe reacts and recovers more quickly than ZooKeeper against node failures.

关键词： cloud computing fault tolerant computing large-scale systems protocols public domain software reliability Giraffe Paxos protocol ZooKeeper cloud services fault-tolerance hierarchical data organization memory storage scalable distributed coordination service Color Proposals Protocols Scalability Servers Topology Vegetation Consistency Coordination Service distributed Cloud System Fault Tolerance

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Developing Interoperability Standards for distributed Simulaton and Cots Simulation Packages with the CSPI PDG 06

Developing Interoperability Standards for Distributed Simula...

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Simulation Winter Conference

作者： Simon J. E. Taylor Steffen Strassburger Stephen J. Turner Malcolm Y.h. Low Xiaoguang Wang John Ladbrook Centre for Applied Simulation Modelling School of Information Systems Computing & Maths Brunei University Middlesex UK Operation and Automation IFF Fraunhofer Institute for Factory Automation Magdeburg Germany Parallel & Distributed Computing Centre School of Computer Engineering Nanyang Technological University Singapore Dunton Engineering Centre Ford Motor Company Limited Basildon UK

ISBN: (纸本)9781424405015

For many years discrete-event simulation has been used to analyze production and logistics problems in manufacturing and defense. In the early 1980s, visual interactive modelling environments were created that supported the development, experimentation and visualization of simulation models. Today these environments are termed commercial-off-the-shelf simulation packages (CSPs). With the advent of distributed simulation and, later, the high level architecture, the possibility existed to link together these CSPs and their models to simulate larger problems within enterprises (e.g. multiple production lines) and across supply chains. However, the problem of standardizing the use of the HLA and its constituent parts in this domain exists. The solution of this problem is the work of the CSP interoperability product development group (CSPI PDG). The purpose of this paper is to introduce the CSPI PDG and to review the suite of standards proposed by the group and current progress

关键词： Standards development Packaging Computational modeling distributed computing Discrete event simulation Production facilities Communication standards computer aided manufacturing Manufacturing automation Logistics

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Transformative effects of ChatGPT on modern education: Emerging Era of AI Chatbots

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Internet of Things and Cyber-Physical Systems 2024年第1期4卷 19-23页

作者： Gill, Sukhpal Singh Xu, Minxian Patros, Panos Wu, Huaming Kaur, Rupinder Kaur, Kamalpreet Fuller, Stephanie Singh, Manmeet Arora, Priyansh Parlikad, Ajith Kumar Stankovski, Vlado Abraham, Ajith Ghosh, Soumya K. Lutfiyya, Hanan Kanhere, Salil S. Bahsoon, Rami Rana, Omer Dustdar, Schahram Sakellariou, Rizos Uhlig, Steve Buyya, Rajkumar School of Electronic Engineering and Computer Science Queen Mary University of London London United Kingdom Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China Raygun Performance Monitoring Wellington New Zealand Center for Applied Mathematics Tianjin University Tianjin China Department of Science Kings Education London United Kingdom Cymax Group Technologies BC Canada QM Academy Queen Mary University of London London United Kingdom Jackson School of Geosciences University of Texas at Austin AustinTX United States Centre for Climate Change Research Indian Institute of Tropical Meteorology Pune India Microsoft Hyderabad India Institute for Manufacturing Department of Engineering University of Cambridge Cambridge United Kingdom Faculty of Computer and Information Science University of Ljubljana Ljubljana Slovenia Machine Intelligence Research Labs AuburnWA United States Faculty of Computing and Data Science FLAME University Maharashtra Pune India Department of Computer Science and Engineering Indian Institute of Technology Kharagpur India Department of Computer Science University of Western Ontario London Canada Sydney Australia School of Computer Science University of Birmingham United Kingdom School of Computer Science and Informatics Cardiff University Cardiff United Kingdom Distributed Systems Group Vienna University of Technology Vienna Austria Department of Computer Science University of Manchester Oxford Road Manchester United Kingdom Laboratory School of Computing and Information Systems The University of Melbourne Australia

ChatGPT, an AI-based chatbot, offers coherent and useful replies based on analysis of large volumes of data. In this article, leading academics, scientists, distinguish researchers and engineers discuss the transformative effects of ChatGPT on modern education. This research discusses ChatGPT capabilities and its use in the education sector, identifies potential concerns and challenges. Our preliminary evaluation shows that ChatGPT perform differently in different subject areas including finance, coding, maths, and general public queries. While ChatGPT has the ability to help educators by creating instructional content, offering suggestions and acting as an online educator to learners by answering questions, transforming education through smartphones and IoT gadgets, and promoting group work, there are clear drawbacks in its use, such as the possibility of producing inaccurate or false data and circumventing duplicate content (plagiarism) detectors where originality is essential. The often reported "hallucinations" within GenerativeAI in general, and also relevant for ChatGPT, can render its use of limited benefit where accuracy is essential. What ChatGPT lacks is a stochastic measure to help provide sincere and sensitive communication with its users. Academic regulations and evaluation practices used in educational institutions need to be updated, should ChatGPT be used as a tool in education. To address the transformative effects of ChatGPT on the learning environment, educating teachers and students alike about its capabilities and limitations will be crucial. © 2023 The Authors

关键词： Machine learning

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