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20th International Conference on Parallel and distributed computing, Applications and Technologies, PDCAT 2019

作者： Hoseinyfarahabady, M. Reza Tari, Zahir Zomaya, Albert Y. University of Sydney Center for Distributed and High Performance Computing School of Computer Science NSW Australia RMIT University School of Science MelbourneVIC Australia

ISBN: (纸本)9781728126166

With the increasing popularity of virtual machine monitoring (VMM) technologies, performance variability among collocated virtual machines (VMs) can easily become a severe scalability issue. Particularly, it becomes a necessary for administrative team to control the performance degradation level in a shared environment when multiple I/O-intensive applications simultaneously request their I/O operations [1]. Nevertheless, adding several logical layers between the running applications and the physical storage system, as seen in contemporary virtualized storage devices, makes it considerably difficult to build a low overhead controlling mechanism for such systems (while each VM may running a separate operating system instance) [2]. In this paper, we propose a strategy based on control theory for managing the performance of several I/O requests, such as mean response times and read/write throughput in a consolidated environment where multiple virtual services can share access to a storage system. This scheme uses an approach for measuring the characterization of read/write performance attributes of each virtual services and also takes into account the run-time quality of service enforcement levels requested by them. This is formulated as an optimization problem where a reward function is defined to reduce the overall QoS violation incidents among all consolidated virtual services. performance evaluation is carried out by comparing the proposed solution with the default embedded Linux controller across a range of emulated application workloads in scenarios with multiple consolidated virtual containers. The results confirm that the proposed solution can reduce the overall QoS violation incident rates in scenarios in which the platform operates at a significant traffic load comparing to the default policy in LXC engine. © 2019 IEEE.

关键词： Controllers

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A mathematical model for empowerment of Beowulf clusters for exascale computing

A mathematical model for empowerment of Beowulf clusters for...

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2013 11th International Conference on high performance computing and Simulation, HPCS 2013

作者： Mirtaheri, Seyedeh Leili Khaneghah, Ehsan Mousavi Grandinetti, Lucio Sharifi, Mohsen Center of High Performance Computing for Parallel and Distributed Processing University of Calabria Rende Italy School of Computer Engineering Iran University of Science and Technology Tehran Iran

ISBN: (纸本)9781479908363

high-performance computing (HPC) clusters are currently faced with two major challenges - namely, the dynamic nature of new generation of applications and the heterogeneity of platforms - if they are going to be useful for exascale computing. Processes running these applications may well demand unpredictable requirements and changes to system configuration and capabilities at runtime, thereby requiring fast system response without sacrificing the transparency and integrity of the reconfigured empowered system that is running on a heterogeneous platform. While a challenge in and of itself, platform heterogeneity is both useful and instrumental in the handling of unpredictable requests. The realization of such a dynamically reconfigurable and heterogeneous HPC cluster system for exascale computing requires a model to guide running processes to determine if they need empowerment of the current cluster, and if yes, by how much. To show the feasibility of empowerment of traditional HPC clusters for exascale computing, we have selected Beowulf as a noble candidate cluster and present a mathematical model for the empowerment of Beowulf clusters for exascale computing (EBEC). We have developed the model in line with Beowulf's cluster approach and by using vector space algebra. In contrast to traditional hardware-oriented approaches to improvise the performance of clusters, we use a software approach to the development of the proposed model by emphasizing processes, which act as the creators of the cluster and thus should decide on system (re)configuration, as the principal building blocks of the system. We have also adopted a new approach to heterogeneity by considering heterogeneity at different levels including hardware, system software, application software, and system functionality. In addition to support for heterogeneity and dynamic reconfiguration, the proposed model includes support for scalability that is crucial to exascale computing too. © 2013 IEEE.

关键词： Vector spaces

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Linear combinations of DVFS-enabled processor frequencies to modify the energy-aware scheduling algorithms 10

Linear combinations of DVFS-enabled processor frequencies to...

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10th IEEE/ACM International Symposium on Cluster, Cloud, and Grid computing, CCGrid 2010

作者： Rizvandi, Nikzad Babaii Taheri, Javid Zomaya, Albert Y. Lee, Young Choon Center for Distributed and High Performance Computing School of Information Technologies University of Sydney NSW 2006 Australia Australian Technology Park Sydney NSW 1430 Australia

ISBN: (纸本)9781424469871

The energy consumption issue in distributed computing systems has become quite critical due to environmental concerns. In response to this, many energy-aware scheduling algorithms have been developed primarily by using the dynamic voltage-frequency scaling (DVFS) capability incorporated in recent commodity processors. The majority of these algorithms involve two passes: schedule generation and slack reclamation. The latter is typically achieved by lowering processor frequency for tasks with slacks. In this paper, we revisit this energy reduction technique from a different perspective and propose a new slack reclamation algorithm which uses a linear combination of the maximum and minimum processor frequencies to decrease energy consumption. This algorithm has been evaluated based on results obtained from experiments with three different sets of task graphs: 1,500 randomly generated task graphs, and 300 task graphs of each of two real-world applications (Gauss-Jordan and LU decomposition). The results show that the amount of energy saved in the proposed algorithm is 13.5%, 25.5% and 0.11% for random, LU decomposition and Gauss-Jordan task graphs, respectively;these percentages for the reference DVFS-based algorithm are 12.4%, 24.6% and 0.1%, respectively. © 2010 IEEE.

关键词： Energy utilization

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Galaxyfly: A novel family of flexible-radix low-diameter topologies for large-scales interconnection networks 16

Galaxyfly: A novel family of flexible-radix low-diameter top...

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30th International Conference on Supercomputing, ICS 2016

作者： Lei, Fei Dong, Dezun Liao, Xiangke Su, Xing Li, Cunlu National Laboratory for Parallel and Distributed Processing Collaborative Innovation Center of High Performance Computing College of Computer National University of Defense Technology Changsha410073 China

ISBN: (纸本)9781450343619

Interconnection network plays an essential role in the architecture of large-scale high performance computing (HPC) systems. In the paper, we construct a novel family of lowdiameter topologies, Galaxyfly, using techniques of algebraic graphs over finite fields. Galaxyfly is guaranteed to retain a small constant diameter while achieving a flexible tradeoff between network scale and bisection bandwidth. Galaxyfly lowers the demands for high radix of network routers and is able to utilize routers with merely moderate radix to build exascale interconnection networks. We present effective congestion-aware routing algorithms for Galaxyfly by exploring its algebraic property. We conduct extensive simulations and analysis to evaluate the performance, cost and power consumption of Galaxyfly against state-of-the-art topologies. The results show that our design achieves better performance than most existing topologies under various routing algorithms and traffic patterns, and is cost-effective to deploy for exascale HPC systems. © 2016 ACM.

关键词： Topology

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Secure high-throughput computing using UNICORE XML spaces

Secure high-throughput computing using UNICORE XML spaces

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6th UNICORE Summit 2010

作者： Grunzke, Richard Schuller, Bernd Center for Information Services High Performance Computing Department of Distributed Data Intensive Computing Dresden University of Technology 01062 Dresden Germany Jülich Supercomputing Centre Distributed Systems and Grid Computing Division Forschungszentrum Jülich GmbH 52425 Jülich Germany

ISBN: (纸本)9783893366613

In this work we are concerned with running a large compute cluster in "farming" mode, i.e. when the typical job uses one core and the number of jobs running at the same time ideally is equal to the number of cores. The number of cores is of the order of 100000. Using Grid middleware, specifically UNICORE, to efficiently run large numbers of jobs on such a compute clusters brings a number of challenges. Currently, UNICORE 6 is well suited for highly parallel HPC jobs, but does not scale well to very high numbers of jobs. In the space-based approach that has been already described in a previous paper3, an XML document repository (the Space) is used as a central job queue. Clients submit jobs into the space, and the execution server(s) pull jobs from the space for processing. Since no further interaction of the client is required, the job throughput is improved. Since the execution server controls the number of concurrent jobs, its efficiency is also improved. The prototype described in3 has recently been extended to include trust delegation, making the system capable of multi-user operation. In this paper, we explore the performance characteristics of the space-based approach and compare it with the standard batch mode of the UNICORE commandline client. Issues such as throughput, scalability, stability and efficiency (including client side CPU usage) are investigated, and the suitability of the different approaches for various usage scenarios is evaluated. The aim of this work is to help bring UNICORE 6 to the next level of high throughput computing.

关键词： XML

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Exploiting contention and congestion aware switch allocation in network-on-chips 17

Exploiting contention and congestion aware switch allocation...

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50th ACM Turing Conference - China, ACM TUR-C 2017

作者： Li, Cunlu Dongy, Dezun Liao, Xiangke National Laboratory for Parallel and Distributed Processing Collaborative Innovation Center of High Performance Computing College of Computer National University of Defense Technology Changsha Hunan410073 China

ISBN: (纸本)9781450348737

Network-on-chip system plays an important role to improve the performance of chip multiprocessor systems. As the complexity of the network increases, congestion problem has become the major performance bottleneck and seriously influence the performance of NoCs. Prior works have focused on designing effective routing algorithm based on collecting congestion and contention information to load balance the traffic. However, most prior works do not consider balancing the traffic load during switch allocation. Due to the lack of congestion information in switch allocation stage, switch allocator performs allocation only based on packet requests and thus aggravates the congestion in the ports of switch. In this paper, we propose to add the congestion and contention information into the switch allocation process and design an efficient on-chip switching strategy which utilizes the contention and congestion information to load balance the traffic and achieve efficient switch allocation. To further enhance the performance of our design, we carefully design our switch allocation strategy to balance the trade-off between traffic load balance and the matching efficiency in switch allocation. We evaluate our design under synthetic traffic and trace of parsec benchmarks. Our evaluations show this mechanism achieves optimal latency compared to best previous switch allocation strategies. © 2017 ACM.

关键词： Network-on-chip

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Demystifying Ethereum account diversity:observations,models and analysis

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Frontiers of Computer Science 2022年第4期16卷 119-130页

作者： Chaofan Wang Xiaohai Dai Jiang Xiao Chenchen Li Ming Wen Bingbing Zhou Hai Jin Clusters and Grid Computing Lab National Engineering Research Center for Big Data Technology and System Services Computing Technology and System LabWuhan430074China School of Computer Science and Technology Huazhong University of Science and TechnologyWuhan430074China School of Cyber Science and Engineering Huazhong University of Science and TechnologyWuhan430074China Centre for Distributed and High Performance Computing School of Information TechnologiesThe University of SydneyCamperdownNew South Wales2006Australia

Blockchain platform Ethereum has involved millions of accounts due to its strong potential for providing numerous services based on smart *** massive accounts can be divided into diverse categories,such as miners,tokens,and exchanges,which is termed as account diversity in this *** benefit of investigating diversity are multi-fold,including understanding the Ethereum ecosystem deeper and opening the possibility of tracking certain abnormal ***,the exploration of blockchain account diversity remains *** the most relevant studies,which focus on the deanonymization of the accounts on Bitcoin,can hardly be applied on Ethereum since their underlying protocols and user idioms are *** this end,we present the first attempt to demystify the account diversity on *** key observation is that different accounts exhibit diverse behavior patterns,leading us to propose the heuristics for classification as the *** then raise the coverage rate of classification by the statistical learning model Maximum Likelihood Estimation(MLE).We collect real-world data through extensive efforts to evaluate our proposed method and show its ***,we make an in-depth analysis of the dynamic evolution of the Ethereum ecosystem and uncover the abnormal arbitrage *** for the former,we validate two sweeping statements reliably:(1)standalone miners are gradually replaced by the mining pools and cooperative miners;(2)transactions related to the mining pool and exchanges take up a large share of the total *** latter analysis shows that there are a large number of arbitrage transactions transferring the coins from one exchange to another to make a price difference.

关键词： blockchain Ethereum classification account diversity network analysis

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Energy efficient resource controller for Apache Storm

Energy efficient resource controller for Apache Storm

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作者： HoseinyFarahabady, MohammadReza Taheri, Javid Zomaya, Albert Y. Tari, Zahir Center for Distributed and High Performance Computing School of Computer Science The University of Sydney CamperdownNSW Australia Department of Computer Science Karlstad University Karlstad Sweden School of Computing Technologies RMIT University MelbourneVIC Australia

Apache Storm is a distributed processing engine that can reliably process unbounded streams of data for real-time applications. While recent research activities mostly focused on devising a resource allocation and task scheduling algorithm to satisfy high performance or low latency requirements of Storm applications across a distributed and multi-core system, finding a solution that can optimize the energy consumption of running applications remains an important research question to be further explored. In this article, we present a controlling strategy for CPU throttling that continuously optimize the level of consumed energy of a Storm platform by adjusting the voltage and frequency of the CPU cores while running the assigned tasks under latency constraints defined by the end-users. The experimental results running over a Storm cluster with 4 physical nodes (total 24 cores) validates the effectiveness of proposed solution when running multiple compute-intensive operations. In particular, the proposed controller can keep the latency of analytic tasks, in terms of 99th latency percentile, within the quality of service requirement specified by the end-user while reducing the total energy consumption by 18% on average across the entire Storm platform. © 2021 John Wiley & Sons, Ltd.

关键词： Storms

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Profit-driven service request scheduling in clouds 10

Profit-driven service request scheduling in clouds

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10th IEEE/ACM International Symposium on Cluster, Cloud, and Grid computing, CCGrid 2010

作者： Lee, Young Choon Wang, Chen Zomaya, Albert Y. Zhou, Bing Bing Centre for Distributed and High Performance Computing School of Information Technologies University of Sydney NSW 2006 Australia 2CSIRO ICT Center PO Box 76 Epping NSW 1710 Australia

ISBN: (纸本)9781424469871

A primary driving force of the recent cloud computing paradigm is its inherent cost effectiveness. As in many basic utilities, such as electricity and water, consumers/clients in cloud computing environments are charged based on their service usage;hence the term 'pay-peruse'. While this pricing model is very appealing for both service providers and consumers, fluctuating service request volume and conflicting objectives (e.g., profit vs. response time) between providers and consumers hinder its effective application to cloud computing environments. In this paper, we address the problem of service request scheduling in cloud computing systems. We consider a three-tier cloud structure, which consists of infrastructure vendors, service providers and consumers, the latter two parties are particular interest to us. Clearly, scheduling strategies in this scenario should satisfy the objectives of both parties. Our contributions include the development of a pricing model-using processor-sharing-for clouds, the application of this pricing model to composite services with dependency consideration (to the best of our knowledge, the work in this study is the first attempt), and the development of two sets of profit-driven scheduling algorithms. © 2010 IEEE.

关键词： Profitability

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The p-index: Ranking Scientists Using Network Dynamics

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Procedia Computer Science 2014年 29卷 465-477页

作者： U. Senanayake M. Piraveenan A.Y. Zomaya Center for Complex Systems Research The University of Sydney Australia Centre for Distributed and High Performance Computing The University of Sydney Australia

The indices currently used by scholarly databases, such as Google scholar, to rank scientists, do not attach weights to the citations. Neither is the underlying network structure of citations considered in computing these metrics. This results in scientists cited by well-recognized journals not being rewarded, and may lead to potential misuse if documents are created purely to cite others. In this paper we introduce a new ranking metric, the p-index (pagerank-index), which is computed from the underlying citation network of papers, and uses the pagerank algorithm in its computation. The index is a percentile score, and can potentially be implemented in public databases such as Google scholar, and can be applied at many levels of abstraction. We demonstrate that the metric aids in fairer ranking of scientists compared to h-index and its variants. We do this by simulating a realistic model of the evolution of citation and collaboration networks in a particular field, and comparing h-index and p-index of scientists under a number of scenarios. Our results show that the p-index is immune to author behaviors that can result in artificially bloated h-index values.

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