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Provisioning OpenCL Capable Infrastructure with Infiniband Verbs

Provisioning OpenCL Capable Infrastructure with Infiniband V...

引用

International Symposium on parallel and distributed computing

作者： Christopher J. Reynolds Zsolt Lichtenberger Stephen Winter Centre for Parallel Computing School of Electronics and Computer Science University of Westminster London UK

The availability of low cost high performance hardware such as graphical processing units (GPUs) has been the driving force for considerable change in both traditional high performance computing (HPC), and more recently the data centre. Vendor independent methods of accessing such hardware include the recently standardised OpenCL framework. However, using GPUs as accelerators for certain computational algorithms requires careful provisioning of infrastructure in order to balance cost, power consumption, and device utilization. In this paper we describe vOpenCL, an architecture for provisioning OpenCL capable hardware. vOpenCL works by transparently offloading processing from traditional cluster nodes, to a remotely located farm of OpenCL capable processors such as GPUs. vOpenCL differs from existing provisioning solutions since it provides mechanisms to optimize the data transfers between components. This is achieved through the use of a module/plug in which fully exploits the Infiniband interconnect architecture. We provide full analysis of vOpenCL and all of its plugins, in a range of scenarios including from within virtualized environments. For certain algorithms, we demonstrate that the Infiniband plug in can provide significant performance benefits.

关键词： Graphics processing unit Servers Sockets IP networks Kernel Libraries Time measurement

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GEMLCA: grid execution management for legacy code architecture design

GEMLCA: grid execution management for legacy code architectu...

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EUROMICRO Conference

作者： T. Delaitre A. Goyeneche P. Kacsuk T. Kiss G.Z. Terstyanszky S.C. Winter Centre for Parallel Computing Cavendish School of Computer Science University of Westminster London UK

The grid execution management for legacy code architecture (GEMLCA) describes a solution for exposing and executing legacy applications through an OGSI grid service. This architecture has been introduced in a previous paper by the same authors where the general concept was demonstrated by creating an OGSI/GT3 version of the MadCity traffic simulator. The class structure of the architecture is described presenting each component and describing the relationships between them. Also, the current architecture implementation is evaluated through test results gained by running the MadCity traffic simulator as a C/PVM legacy application.

关键词： computer architecture Grid computing Java Wrapping Testing Traffic control Computational modeling Application software Service oriented architecture parallel processing

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Multi-label Classification with Clustering for Image and Text Categorization

Multi-label Classification with Clustering for Image and Tex...

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International Congress on Image and Signal Processing

作者： Gulisong Nasierding Atul Sajjanhar School of Computer Science and Technology Xinjiang Normal University Parallel and Distributed Computing Lab School of Information Technology Deakin University

ISBN: (纸本)9781479927654

This paper explores effective multi-label classification methods for multi-semantic image and text categorization. We perform an experimental study of clustering based multi-label classification (CBMLC) for the target problem. Experimental evaluation is conducted for identifying the impact of different clustering algorithms and base classifiers on the predictive performance and efficiency of CBMLC. In the experimental setting, three widely used clustering algorithms and six popular multi-label classification algorithms are used and evaluated on multi-label image and text datasets. A multi-label classification evaluation metrics, micro F1-measure, is used for presenting predictive performances of the classifications. Experimental evaluation results reveal that clustering based multi-label learning algorithms are more effective compared to their non-clustering counterparts.

关键词： Multi-label classification Clustering Image and text categorization

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A cots simulation package emulator (CSPE) for investigating cots simulation package interoperability

A cots simulation package emulator (CSPE) for investigating ...

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2005 Winter Simulation Conference

作者： Wang, Xiaoguang Turner, Stephen John Taylor, Simon J. E. Low, Malcolm Yoke Hean Gan, Boon Ping Parallel and Distributed Computing Centre School of Computer Engineering Nanyang Technological University 639798 Singapore Singapore Centre for Applied Simulation Modeling School of Information Systems Computing and Mathematics Brunel University Uxbridge UB8 3PH United Kingdom D-SIMLAB Programme Singapore Institute of Manufacturing Technology 71 Nanyang Drive 638075 Singapore Singapore

ISBN: (纸本)0780395204

Commercial Off-The-Shelf (COTS) Simulation Packages (CSPs) are widely used to facilitate the creation of simulation models using some kind of visual interactive interface. CSPs have "evolved" over the years and are well used to support modeling demands in different market niches and domains. However, in terms of distributed simulation, there is almost a complete lack of support for interoperability. The advent of the High Level Architecture (HLA) standard makes it possible to connect distributed model components together. The model components can be developed using specific CSPs best suited to the application area. In this paper, a CSP Emulator (CSPE) is proposed to investigate the interfaces between the CSPs and the HLA Runtime Infrastructure. In addition to support for standalone models as provided by current CSPs, the CSPE has some new features needed for building distributed models. An evaluation is conducted between CSPE and Simul8, one of the popular CSPs.

关键词： Electronics packaging

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Online Demand Peak Shaving with Machine-Learned Advice in Cyber-Physical Energy Systems

Online Demand Peak Shaving with Machine-Learned Advice in Cy...

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2023 IEEE International Conference on Dependable, Autonomic and Secure computing, 2023 International Conference on Pervasive Intelligence and computing, 2023 International Conference on Cloud and Big Data computing, 2023 International Conference on Cyber science and Technology Congress, DASC/PiCom/CBDCom/CyberSciTech 2023

作者： Fengl, Minxi Li, Wei Qin, Boyu Zomaya, Albert Y. Centre for Distributed and High Performance Computing School of Computer Science The University of Sydney Australia Xi'an Jiaotong University State Key Laboratory of Electrical Insulation and Power Equipment Department of Electrical Engineering China

ISBN: (纸本)9798350304602

With the deep integration of cyber tools, control algorithms are increasingly employed in cyber-physical energy systems to enhance management, cost efficiency, and robustness. Effective demand load management is crucial in cyber-physical energy systems as it directly impacts operational costs. Failure to adequately manage spiky or seasonal demand loads can lead to significant expenses on monthly utility bills. In this study, we propose AMPAMOD, a randomized online algorithm with machine-learned advice, to optimize battery operations and mitigate highly dynamic peak loads. AMPAMOD utilizes limited advice from machine learning algorithms to guide our online algorithm and ensure cost-effective peak load management. The theoretical analysis shows that our solution has minimal advice complexity, a linear computational cost, and an improved competitive ratio. Finally, we conduct extensive trace-driven experiments on real-world datasets. AMPAMOD achieves a peak shaving success rate of over 90%, outperforming baselines by at least 50%. These experimental results confirm theoretical findings and demonstrate the potential of AMPAMOD. © 2023 IEEE.

关键词： Cyber Physical System

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AsT: An Asymmetric-Sensitive Transformer for Osteonecrosis of the Femoral Head Detection 37

AsT: An Asymmetric-Sensitive Transformer for Osteonecrosis o...

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37th AAAI Conference on Artificial Intelligence, AAAI 2023

作者： Chen, Haoyang Liu, Shuai Lu, Feng Li, Wei Sheng, Bin Li, Mi Jin, Hai Zomaya, Albert Y. National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology China Centre for Distributed and High Performance Computing School of Computer Science The University of Sydney Australia Department of Computer Science and Engineering Shanghai Jiao Tong University China Tongji Hospital Tongji Medical College Huazhong University of Science and Technology China

ISBN: (纸本)9781577358800

Early diagnosis of osteonecrosis of the femoral head (ONFH) can inhibit the progression and improve femoral head preservation. The radiograph difference between early ONFH and healthy ones is not apparent to the naked eye. It is also hard to produce a large dataset to train the classification model. In this paper, we propose Asymmetric-Sensitive Transformer (AsT) to capture the uneven development of the bilateral femoral head to enable robust ONFH detection. Our ONFH detection is realized using the self-attention mechanism to femoral head regions while conferring sensitivity to the uneven development by the attention-shared transformer. The real-world experiment studies show that AsT achieves the best performance of AUC 0.9313 in the early diagnosis of ONFH and can find out misdiagnosis cases firmly. Copyright © 2023, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Large dataset

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A NOTE ON THE LOAD BALANCING PROBLEM FOR COARSE-GRAINED HYPERCUBE DICTIONARY MACHINES

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JOINT INTERNATIONAL CONF ON VECTOR AND parallel PROCESSING ( CONPAR 90 - VAPP IV )

作者： DEHNE, F GASTALDO, M Center for Parallel and Distributed Computing School of Computer Science Carleton University Ottawa K1S 5B6 Canada Laboratoire de I'lnformatique du Parallelisms - IMAG Ecole Normale Superieure de Lyon Lyon cedex 07 69364 France

ISBN: (纸本)3540530657

The main problem for the design of dictionary machines on coarse grained hypercube multiprocessors, in comparison to the widely studied dictionary problem for fine grained hypercube multiprocessors, is that due to unequal distribution of the inserted and deleted records, the sizes of the sets stored at the individual processors may vary considerably. This problem, which is usually referred to as the load balancing problem, may lead to considerable degradation of the dictionary machine's performance. In this note we show that the load balancing problem for coarse grained hypercube dictionary machines can be solved with provable bounds on the sizes of the data sets, and with only little computational overhead. © Springer-Verlag Berlin Heidelberg 1990.

关键词： Geometry

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Recognition of catastrophic faults

Recognition of catastrophic faults

引用

1992 IEEE International Workshop on Defect and Fault Tolerance in VLSI Systems, DFT 1992

作者： Nayak, Amiya Pagli, Linda Santoro, Nicola Center for Parallel and Distributed Computing School of Computer Science Carleton University OttawaONK1S 5B6 Canada Dipartimento di Scienze dell'Informazione University of Pisa Corso Italia 40 Pisa56100 Italy

ISBN: (纸本)0818628375

Fault tolerance through the incorporation of redundancy and reconfiguration is quite common. Regular systems are being designed with massive redundancy built into them [5,6,12], These systems also make use of the redundancy to reconfigure in the event of failure in one or more components;normally, a reconfiguration process is triggered as soon as a fault is detected. Many different reconfiguration schemes [1-4,6,7,10-13] have been proposed in the literature which reconfigure regular systems in the presence of faulty components. The distribution of faults can have severe impact on the effectiveness of any reconfiguration scheme;in fact, patterns of faults occurring at strategic locations may render an entire system unusable regardless of its component redundancy and of its reconfiguration capabilities. For a given design, it is not difficult to identify a set of elements whose failure will have catastrophic consequence. There exist many patterns (random distribution) of faults, not in a block, which can be fatal for the system [9]. Therefore, the characterization of such fault patterns is crucial for the identification, testing and detection of such catastrophic events. © 1992 IEEE.

关键词： Redundancy

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parallel branch and bound on fine-grained hypercube multiprocessors

Parallel branch and bound on fine-grained hypercube multipro...

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International Conference on Tools for Artificial Intelligence (ICTAI)

作者： F. Dehne A.G. Ferreira A. Rau-Chaplin Center for Parallel and Distributed Computing School of Computer Science Carleton University Ottawa Canada Laboratoire de I'lnformatique du Parallelisme-IMAG Ecole Normale Superieure Lyon France Center for Parallel and Distributed Computing. School of Computer Science Carleton University Ottawa Canada

An efficient branch and bound algorithm for fine-grained hypercube multiprocessors is presented. The method uses a global storage allocation scheme where all processors collectively store all back-up paths such that each processor needs to store only a constant amount of information. At each iteration of the algorithm, all nodes of the current back-up tree may decide whether they need to create new children, be pruned, or remain unchanged. An algorithm that, on the basis of these decisions, updates the current back-up tree and distributes global information in O(log m) steps, where m is the current number of nodes, is described. This method also provides a dynamic allocation mechanism that obtains optimal load balancing. Another important property of the method is that, even if very drastic changes in the current back-up tree occur, the performance of the load balancing mechanism remains constant. The method is currently being implemented on the Connection Machine.< >

关键词： Hypercubes Load management distributed computing computer science Search methods Linear programming Artificial intelligence Operations research High definition video Concurrent computing

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HCW 2020 Keynote Speaker Edge Intelligence Empowering IoT Data Analytics

HCW 2020 Keynote Speaker Edge Intelligence Empowering IoT Da...

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IEEE International Symposium on parallel and distributed Processing Workshops and Phd Forum (IPDPSW)

作者： Albert Y. Zomaya Centre for Distributed & High Performance Computing School of Computer Science University of Sydney Australia

ISBN: (数字)9781728174457

ISBN: (纸本)9781728174570

Along with the many developments in computing and communication technologies and the surge of mobile devices, a brand new paradigm, Edge computing (EC), has gained a lot of momentum in recent times. In parallel, Artificial Intelligence (AI) applications have been thriving fuelled by breakthroughs in deep learning and the emergence of new hardware architectures. Billions of bytes of data, generated at the network edge which is composed of a multitude of heterogeneous devices, put great demands on data processing and structural optimization which led to a genuine demand for the integration of EC and AI leading to what is known today as Edge Intelligence (EI). n this talk, I will discuss how EI is rapidly increasing the convergence between humans, things, and Al. I will briefly review some of our designs for the development of EI and present how to rethink decisions that are made by "black box" Al approaches when implementing analytics on data generated by the Internet of Things (IoT). This does not provide a clear explanation of how a method works and why it behaves in a certain way. Lack of explanation might not be an issue for those IoT applications which have less privacy constraints, but it can be a barrier to the adoption of such systems in highly regulated domains. I will argue that explainable Edge Al is the key to social acceptance of an even wider deployment of IoT applications.

关键词： Artificial intelligence High performance computing computer science Internet of Things distributed processing Conferences Data analysis

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