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共 281 条记录，以下是91-100 订阅

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Proceedings - 2011 17th IEEE international conference on parallel and distributed systems, ICPADS 2011

Proceedings - 2011 17th IEEE International Conference on Par...

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2011 17th IEEE international conference on parallel and distributed systems, ICPADS 2011

ISBN: (纸本)9780769545769

the proceedings contain 153 papers. the topics discussed include: scheduling mixed real-time and non-real-time applications in MapReduce environment;hypervisor support for efficient memory de-duplication;a hierarchical memory service mechanism in server consolidation environment;a method for improving concurrent write performance by dynamic mapping virtual storage system combined with cache management;fair and efficient online adaptive scheduling for multiple sets of parallel applications;combining multiple metrics to control BSP process rescheduling in response to resource and application dynamics;broadcasting on large scale heterogeneous platforms with connectivity artifacts under the bounded multi-port model;architecture-aware mapping and optimization on a 1600-Core GPU;simulation-based performance analysis and tuning for a two-level directly connected system;and ANEPROF: energy profiling for android java virtual machine and applications.

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parallel computing for large-scale author name disambiguation in medline 21

Parallel computing for large-scale author name disambiguatio...

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21st IEEE international conference on High Performance computing and Communications, 17th IEEE international conference on Smart City and 5th IEEE international conference on Data Science and systems, HPCC/SmartCity/DSS 2019

作者： Tang, Anyao Wu, Chengkun Liu, Jie Wang, Wei Yang, Xi Xing, Yuting Science and Technology on Parallel and Distributed Processing Laboratory Laboratory of Software Engineering for Complex Systems National University of Defense Technology Changsha410073 China State Key Laboratory of High Performance Computing College of Computer National University of Defense Technology Changsha410073 China College of Computer National University of Defense Technology Changsha 410073 China

ISBN: (纸本)9781728120584

Author name disambiguation (AND) is an important task in the field of scientific data mining. It has become a great challenge with the rapid growth of academic digital libraries. the task of AND for a large number of authors is computationally intensive. In particular, an author's name in MEDLINE is represented by full last name and initials, like 'Zhang S', which leads to a lot of identical strings that actually represent different names. In this paper, we proposed an efficient algorithm for parallel AND computation. the proposed algorithm mainly addresses the load balancing issue across many computing nodes. It involves the following strategies:(1) Author-based load balancing, which splits the computation load for each core by author name labels. (2) Matrix-based strategy, which calculates the pairwise similarity between publications and saves them in a matrix globally shared by all processes. then group them by width-first search. We combine the above two strategies, the second of which is used to calculate authors with a large number of documents, and the other authors apply the first. We constructed a publications database written by Chinese authors from MEDLINE, the biggest public database for biomedical literature (abstracts). For benchmark testing, we experimented our algorithm with a dataset of 1 million publications on the Tianhe-2A supercomputer. Firstly, we trained an AND classifier that can achieve 98.1% of F1. the serial computation time is estimated to be approximately 246 hours, while the parallel execution time is approximately 66 hours in the case of four cores on a single node (with a speedup of 3.7x). Finally, we reduced the total parallel computing time of 1 million documents to about 2 hours and achieved 65.8% of parallelism efficiency using 200 cores on 90 nodes. © 2019 IEEE.

关键词： Matrix algebra

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Dynamic Load Balancing for Ordered Data-parallel Regions in distributed Streaming systems 16

Dynamic Load Balancing for Ordered Data-Parallel Regions in ...

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17th ACM/IFIP/USENIX international Middleware conference

作者： Schneider, Scott Wolf, Joel Hildrum, Kirsten Khandekar, Rohit Wu, Kun-Lung IBM Corp TJ Watson Res Ctr Yorktown Hts NY 10598 USA IBM Res Yorktown Hts NY USA

ISBN: (纸本)9781450343008

distributed stream computing has emerged as a technology that can satisfy the low latency, high throughput demands of big data. Stream computing naturally exposes pipeline, task and data parallelism. Meeting the throughput and latency demands of online big data requires exploiting such parallelism across heterogeneous clusters. When a single job is running on a homogeneous cluster, load balancing is important. When multiple jobs are running across a heterogeneous cluster, load balancing becomes critical. the data parallel regions of distributed streaming applications are particularly sensitive to load imbalance, as their overall speed is gated by the slowest performer. We propose a dynamic load balancing technique based on a system artifact: the TCP blocking rate per connection. We build a function for each connection based on this blocking rate, and obtain a balanced load distribution by modeling the problem as a minimax separable resource allocation problem. In other words, we minimize the maximum value of these functions. Our model achieves local load balancing that does not require any global information. We test our model in a real streaming system, and demonstrate that it is able to detect differences in node capacities, determine the correct load distribution for those capacities and dynamically adapt to changes in the system.

关键词： stream processing automatic parallelization dynamic load balancing

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distributed analysis with PROOF in ATLAS collaboration

Distributed analysis with PROOF in ATLAS collaboration

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17th international conference on computing in High Energy and Nuclear Physics (CHEP)

作者： Panitkin, S. Y. Benjamin, D. Montoya, G. Carillo Cranmer, K. Ernst, M. Guan, W. Ito, H. Maeno, T. Majewski, S. Mellado, B. Rind, O. Shibata, A. Tarrade, F. Wenaus, T. Xu, N. Ye, S. Brookhaven Natl Lab Upton NY 11973 USA Duke Univ Durham NC 27708 USA Univ Wisconsin Madison Madison WI 53706 USA NYU New York NY 10003 USA

the parallel ROOT Facility - PROOF is a distributed analysis system which allows to exploit inherent event level parallelism of high energy physics data. PROOF can be configured to work with centralized storage systems, but it is especially effective together with distributed local storage systems - like Xrootd, when data are distributed over computing nodes. It works efficiently on different types of hardware and scales well from a multi-core laptop to large computing farms. From that point of view it is well suited for both large central analysis facilities and Tier 3 type analysis farms. PROOF can be used in interactive or batch like regimes. the interactive regime allows the user to work with typically distributed data from the ROOT command prompt and get a real time feedback on analysis progress and intermediate results. We will discuss our experience with PROOF in the context of ATLAS Collaboration distributed analysis. In particular we will discuss PROOF performance in various analysis scenarios and in multi-user, multi-session environments. We will also describe PROOF integration with the ATLAS distributed data management system and prospects of running PROOF on geographically distributed analysis farms.

关键词： High energy physics

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the low-cost secure sessions of access control model for distributed applications by public personal smart cards

The low-cost secure sessions of access control model for dis...

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2011 17th IEEE international conference on parallel and distributed systems, ICPADS 2011

作者： Chen, Kuo-Yi Lin, Chin-Yang Hou, Ting-Wei Academia Sinica Institute of Information Science Taipei Taiwan Department of Engineering Science National Cheng Kung University Tainan Taiwan

ISBN: (纸本)9780769545769

the secure requirement of modern information systems is increasing significantly nowadays, especially in cloud computing with distributed applications. Among secure mechanisms of an organization, the access control (AC) is a foundation for modern information systems. In order to reach an effective and flexible approach of access control, the Rolebased Access Control (RBAC) models are widely deployed in organizations. Comparing with traditional discretionary access control (DAC) and mandatory access control (MAC), the userrole- subject mapping of a RBAC model provides effective permissions assignments for access control of an organization. However, the RBAC sessions could be stretched over multiple distributed servers in cloud computing. the traversed sessions between servers could be modified, monitored and attacked by modern hacker techniques, and become secure leaks in RBAC models. In order to ensure secure sessions in cloud computing, various encryption approaches are used. Among these encryption approaches, the use of digital certificates by asymmetric encryption methods could be an appropriate solution to ensure the security of RBAC sessions. However, the cost of public/private keys management and issuing an appropriate certificate tokens for each member in organizations could be very expensive. the high cost might block the deployment of secure RBAC sessions, and then reduce the secure level of organizations. In order to improve this issue, a low-cost approach of secure sessions for RBAC models is proposed in this paper. the personal smart cards can be used as a certificate tokens in RBAC models to reach effective user authentications. Moreover, each session of RBAC models, including user-role-subject assignments and contentbased accesses, can be protected by digital certificates which is generated by user own smart cards. thus the security of RBAC sessions can be improved significantly. It is worth noting that personal smart cards are issued by public departm

关键词： Authentication

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Millipedes: distributed and set-based sub-task scheduler of computing engines running on yarn cluster 17

Millipedes: Distributed and set-based sub-task scheduler of ...

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17th IEEE international conference on High Performance computing and Communications, IEEE 7th international Symposium on Cyberspace Safety and Security and IEEE 12th international conference on Embedded Software and systems, HPCC-ICESS-CSS 2015

作者： Wang, Kebing Bian, Zhaojuan Chen, Qian Software and Service Group Intel Corporation Shanghai China

ISBN: (纸本)9781479989362

Hadoop YARN is evolving to become the de-facto standard that allows multiple data processing engines such as interactive SQL, real-time streaming, data science and batch processing to handle data stored in a single platform. And, there are lots of researches about efficiently managing cluster resources and scheduling parallel jobs over YARN clusters. However, the scheduling of sub-tasks derived from one application doesn't receive enough attention, which still managed by independent data processing engines on YARN. In this paper, we analyze the limitation of sub-task scheduling algorithms of popular data processing engines running on YARN, including MapReduce 2.0, Spark then, we propose Millipedes: a distributed & set-based sub-task scheduling framework. In Millipedes, YARN's application master dispatches a set of sub tasks to data nodes, and then the local task scheduler of each data node schedules the execution of these sub tasks according to real-time dynamic resource usage. © 2015 IEEE.

关键词： Scheduling algorithms

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Self-Adaptive Access Control & Delegation in Cloud computing 17

Self-Adaptive Access Control & Delegation in Cloud Computing

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17th IEEE/ACIS international conference on Software Engineering, Artificial Intelligence, Networking and parallel/distributed computing (SNPD)

作者： Malik, Ali Ahmad Anwar, Hirra Shibli, Muhammad Awais Natl Univ Sci & Technol SEECS Dept Comp Islamabad Pakistan

ISBN: (纸本)9781509022397

Cloud computing has seen significant progress in the last decade, and is still on the rise. A big number of companies are shifting their infrastructure to the cloud because of the numerous advantages it offers, such as rapid elasticity and scalability. However, moving to the cloud also presents a number of challenges. In this paper we focus on one of the major challenges, i.e., access control and delegation in a cloud environment. there exist many frameworks and models that solve issues pertinent to this area and allow dynamic delegation of access rights. However, none of them are robust enough to handle unprecedented changes, i.e., situations not handled at the time of requirements engineering. We've presented a risk-based, self-adaptive access control and delegation framework that caters to such situations by continuously monitoring and evaluating the user risk score and environmental factors, and automatically adapting to the changes incurred by reconfiguring the system. the proposed framework is able to adapt to unprecedented change as it can delegate access rights to previously unauthorized users in an emergency situation and revoke users' access rights based on environmental factors, while running in a continuous feedback loop.

关键词： Self-Adaptive systems Access Control & Delegation Continuous Monitoring Adaptation to Unanticipated Events

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Algorithms and Architectures for parallel Processing 1

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丛书名： Lecture Notes in Computer Science

1000年

作者： Shadi Ibrahim Kim-Kwang Raymond Choo Zheng Yan Witold Pedrycz

ISBN: (数字)9783319654829

ISBN: (纸本)9783319654812

this book constitutes the proceedings of the 17th international conference on Algorithms and Architectures for parallel Processing, ICA3PP 2017, held in Helsinki, Finland, in August 2017.;the 25 full papers presented were carefully reviewed and selected from 117 submissions. they cover topics such as parallel and distributed architectures; software systems and programming models; distributed and network-based computing; big data and its applications; parallel and distributed algorithms; applications of parallel and distributed computing; service dependability and security in distributed and parallel systems; service dependability and security in distributed and parallel systems; performance modeling and evaluation.;this volume also includes 41 papers of four workshops, namely: the 4th international Workshop on Data, Text, Web, and Social Network Mining (DTWSM 2017), the 5th international Workshop on parallelism in Bioinformatics (PBio 2017);, the First international Workshop on distributed Autonomous computing in Smart City (DACSC 2017), and the Second international Workshop on Ultrascale computing for Early Researchers (UCER 2017).

关键词： Algorithm Analysis and Problem Complexity Software Engineering Computer Communication Networks Information systems Applications (incl. Internet)

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22nd IFIP WG 6.1 international conference on distributed Applications and Interoperable systems, DAIS 2022 Held as part of the 17th international Federated conference on distributed computing Techniques, DisCoTec 2022

22nd IFIP WG 6.1 International Conference on Distributed App...

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22nd IFIP WG 6.1 international conference on distributed Applications and Interoperable systems, DAIS 2022 Held as part of the 17th international Federated conference on distributed computing Techniques, DisCoTec 2022

ISBN: (纸本)9783031160912

the proceedings contain 12 papers. the special focus in this conference is on distributed Applications and Interoperable systems. the topics include: the HDFS Replica Placement Policies: A Comparative Experimental Investigation;an Elastic and Scalable Topic-Based Pub/Sub System Using Deep Reinforcement Learning;challenges in Automated Measurement of Pedestrian Dynamics;Using SGX for Meta-Transactions Support in Ethereum DApps;understanding Cryptocoins Trends Correlations;rebop: Reputation-Based Incentives in Committee-Based Blockchains;lesser Evil: Embracing Failure to Protect Overall System Availability;failure Root Cause Analysis for Microservices, Explained;attestation Mechanisms for Trusted Execution Environments Demystified;accelerate Model parallel Deep Learning Training Using Effective Graph Traversal Order in Device Placement;analysis of the Impact of Interaction Patterns and IoT Protocols on Energy Consumption of IoT Consumer Applications.

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A Load-distributed Linpack Implementation for Heterogeneous Clusters 17

A Load-distributed Linpack Implementation for Heterogeneous ...

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2015 IEEE 17th international conference on High Performance computing and Communications (HPCC)

作者： Rohr, David Lindenstruth, Volker Frankfurt Inst Adv Studies Ruth Moufang Str 1 D-60438 Frankfurt Germany

ISBN: (纸本)9781479989379

In recent years, heterogeneous HPC systems, which combine traditional processors with accelerator cards such as GPUs, have been shown to deliver superior performance and power efficiency. Since different scientific problems pose different demands on the computer architecture, some general purpose supercomputers consist of different types of nodes, where each type is suited best for certain applications. Such clusters with inter-node heterogeneity (different types of nodes) on top of intra-node heterogeneity (different processors inside one node) consist of compute nodes with different compute performances. the standard implementation of the Linpack benchmark, HPL, distributes the workload evenly among all processes and thus cannot exploit the cluster's full potential if the nodes have unequal performance. this paper presents a new feature of our HPL-GPU implementation which allows a balanced fine-tuned workload distribution among all compute nodes taking into account their individual compute capabilities. We present results on some nodes of different speed-grades on the LOEWE-CSC cluster and demonstrate that our implementation can utilize all nodes of a heterogeneous configuration efficiently showing only about 3% granularity loss.

关键词： computer architecture mainframes parallel machines software libraries HPL-GPU implementation LOEWE-CSC cluster Linpack benchmark accelerator cards balanced fine-tuned workload distribution compute nodes general purpose supercomputers heterogeneous HPC systems heterogeneous clusters internode heterogeneity intranode heterogeneity load-distributed Linpack implementation Benchmark testing Graphics processing units Hardware Niobium Standards Supercomputers GPU HPC HPL HPL-GPU Heterogeneous LOEWE-CSC Linpack

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