2013 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum最新文献_第4页

Reducing the Environmental Impact of Optical Networks 减少光网络对环境的影响

2013 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum Pub Date : 2013-05-20 DOI: 10.1109/IPDPSW.2013.46

Thilo Schondienst, V. Vokkarane

引用次数: 2

Tabulated Equations of State with a Many-tasking Execution Model 具有多任务执行模型的状态表方程

2013 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum Pub Date : 2013-05-20 DOI: 10.1109/IPDPSW.2013.162

Matthew Anderson, M. Brodowicz, T. Sterling, Hartmut Kaiser, Bryce Adelstein-Lelbach

引用次数: 1

Minimizing Remote Accesses in MapReduce Clusters 最小化MapReduce集群中的远程访问

2013 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum Pub Date : 2013-05-20 DOI: 10.1109/IPDPSW.2013.195

Prateek Tandon, Michael J. Cafarella, T. Wenisch

{"title":"Minimizing Remote Accesses in MapReduce Clusters","authors":"Prateek Tandon, Michael J. Cafarella, T. Wenisch","doi":"10.1109/IPDPSW.2013.195","DOIUrl":"https://doi.org/10.1109/IPDPSW.2013.195","url":null,"abstract":"MapReduce, in particular Hadoop, is a popular framework for the distributed processing of large datasets on clusters of relatively inexpensive servers. Although Hadoop clusters are highly scalable and ensure data availability in the face of server failures, their efficiency is poor. We study data placement as a potential source of inefficiency. Despite networking improvements that have narrowed the performance gap between map tasks that access local or remote data, we find that nodes servicing remote HDFS requests see significant slowdowns of collocated map tasks due to interference effects, whereas nodes making these requests do not experience proportionate slowdowns. To reduce remote accesses, and thus avoid their destructive performance interference, we investigate an intelligent data placement policy we call 'partitioned data placement'. We find that, in an unconstrained cluster where a job's map tasks may be scheduled dynamically on any node over time, Hadoop's default random data placement is effective in avoiding remote accesses. However, when task placement is restricted by long-running jobs or other reservations, partitioned data placement substantially reduces remote access rates (e.g., by as much as 86% over random placement for a job allocated only one-third of a cluster).","PeriodicalId":234552,"journal":{"name":"2013 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128852544","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 10

Toward Flexible and Fast Routing Strategies for Dynamic Network Provisioning 面向动态网络供应的灵活快速路由策略研究

2013 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum Pub Date : 2013-05-20 DOI: 10.1109/IPDPSW.2013.50

Liudong Zuo, Mengxia Zhu

{"title":"Toward Flexible and Fast Routing Strategies for Dynamic Network Provisioning","authors":"Liudong Zuo, Mengxia Zhu","doi":"10.1109/IPDPSW.2013.50","DOIUrl":"https://doi.org/10.1109/IPDPSW.2013.50","url":null,"abstract":"Reserving bandwidth as needed in high-performance networks makes the fast and reliable data transfer with guaranteed performance possible in large-scale collaborative e-science. Besides the notification of acceptance or rejection for a particular reservation request, users normally want to know the earliest possible finish time or the minimum total transfer duration for the data transfer. Several routing algorithms have been proposed to achieve such desired goals given the data size, the data available time, and the deadline to finish the data transfer. Instead of directly processing the bandwidth reservation request (BRR) from users, our approach analyses various parameters to strategically narrow down the solution search space for fast system response. Adapted from some previous works, two algorithms are proposed to compute the reservation options with the earliest completion time (ECT) and with the shortest duration (SD) for multiple BRRs accumulated during a certain period. Extensive simulation results demonstrate the superiority of the proposed algorithms in terms of reduced execution time and improved success ratio of BRRs in comparison with existing scheduling algorithms.","PeriodicalId":234552,"journal":{"name":"2013 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum","volume":"117 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124142371","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

An Efficient Scheduling Model for Broadcasting in Wireless Sensor Networks 无线传感器网络中一种高效的广播调度模型

2013 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum Pub Date : 2013-05-20 DOI: 10.1109/IPDPSW.2013.88

Hongju Cheng, N. Xiong, Xingbo Huang, L. Yang

引用次数: 2

AzureBOT: A Framework for Bag-of-Tasks Applications on the Azure Cloud Platform AzureBOT: Azure云平台上的任务包应用程序框架

2013 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum Pub Date : 2013-05-20 DOI: 10.1109/IPDPSW.2013.261

Dinesh Agarwal, S. Prasad

{"title":"AzureBOT: A Framework for Bag-of-Tasks Applications on the Azure Cloud Platform","authors":"Dinesh Agarwal, S. Prasad","doi":"10.1109/IPDPSW.2013.261","DOIUrl":"https://doi.org/10.1109/IPDPSW.2013.261","url":null,"abstract":"Windows Azure is an emerging cloud platform that provides application developers with APIs to write scientific and commercial applications. However, the steep learning curve to understand the unique architecture of the cloud platforms in general and continuously changing Azure APIs specifically, make it difficult for the application developers to write cloud based applications. During our extensive experience with Azure cloud platform over the past few years, we have identified the need of a framework to abstract the complexities of working with the Azure cloud platform. Such a framework is essential for adoption of cloud technologies. Therefore, we have created AzureBOT-a framework for the Azure cloud platform to write bag-of-tasks class of distributed applications. Azure provides a straightforward and general interface that permits developers to concentrate on their application logic rather than cloud interaction. While we have implemented AzureBOT on Azure cloud platform, our framework design is generic to most of the cloud platforms. In this paper, we present the detailed design of our framework's internal architecture, the APIs in brief, and the usability of our framework. We also discuss the implementation of two different applications and their scalability results over 100Azure worker processors.","PeriodicalId":234552,"journal":{"name":"2013 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114832591","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 15

RTL Simulation of High Performance Dynamic Reconfiguration: A Video Processing Case Study 高性能动态重构的RTL仿真:一个视频处理案例研究

2013 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum Pub Date : 2013-05-20 DOI: 10.1109/IPDPSW.2013.79

Lingkan Gong, O. Diessel, Johny Paul, W. Stechele

引用次数: 3

Enhancing Accuracy and Performance of Collaborative Filtering Algorithm by Stochastic SVD and Its MapReduce Implementation 基于随机奇异值分解的协同滤波算法及其MapReduce实现

2013 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum Pub Date : 2013-05-20 DOI: 10.1109/IPDPSW.2013.120

Che-Rung Lee, Ya-Fang Chang

{"title":"Enhancing Accuracy and Performance of Collaborative Filtering Algorithm by Stochastic SVD and Its MapReduce Implementation","authors":"Che-Rung Lee, Ya-Fang Chang","doi":"10.1109/IPDPSW.2013.120","DOIUrl":"https://doi.org/10.1109/IPDPSW.2013.120","url":null,"abstract":"Collaborative filtering algorithms that extract desired information from records have been widely used in data mining and information retrieval, such as recommendation systems. However, the rapidly increased data size demands more efficient and scalable algorithms and implementations. In this paper, we present a novel algorithm that utilizes stochastic singular value decomposition (SSVD) in the calculation of item-based collaborative filtering. The use of SSVD does not only provide more accurate results in terms of precision and recall, but also reduces the computational cost. The proposed algorithm was implemented using Hadoop MapReduce, which allows distributed processing of massive data stored in a distributed file system. The implementation was evaluated and compared with the recommendation systems provided in the Apache Mahout project, and a 2.53 speedup can be obtained for processing millions records. The accuracy of our algorithm is also 3 times better than the non-SVD algorithm in terms of the F1 metric, a combinative measurement of precision and recall.","PeriodicalId":234552,"journal":{"name":"2013 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117208109","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 14

Accelerating Distributed Workflows with Edge Resources 利用边缘资源加速分布式工作流

2013 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum Pub Date : 2013-05-20 DOI: 10.1109/IPDPSW.2013.240

S. Ramakrishnan, Robert Reutiman, A. Chandra, J. Weissman

{"title":"Accelerating Distributed Workflows with Edge Resources","authors":"S. Ramakrishnan, Robert Reutiman, A. Chandra, J. Weissman","doi":"10.1109/IPDPSW.2013.240","DOIUrl":"https://doi.org/10.1109/IPDPSW.2013.240","url":null,"abstract":"Distributed data-intensive workflow applications are increasingly relying on and integrating remote resources including community data sources, services, and computational platforms. Increasingly, these are made available as data, SAAS, and IAAS clouds. The execution of distributed data-intensive workflow applications can exposé network bottlenecks between clouds that compromise performance. In this paper, we focus on alleviating network bottlenecks by using a proxy network. In particular, we show how proxies can eliminate network bottlenecks by smart routing and perform in-network computations to boost workflow application performance. A novel aspect of our work is the inclusion of multiple proxies to accelerate different workflow stages optimizing different performance metrics. We show that the approach is effective for workflow applications and broadly applicable. Using Montage as an exemplar workflow application, results obtained through experiments on Planet Lab showed how different proxies acting in a variety of roles can accelerate distinct stages of Montage. Our microbenchmarks also show that routing data through select proxies can accelerate network transfer for TCP/UDP bandwidth, delay, and jitter, in general.","PeriodicalId":234552,"journal":{"name":"2013 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117284077","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

Toward a Scalable Heterogeneous Runtime System for the Convey MX Architecture 面向传输MX体系结构的可伸缩异构运行时系统

2013 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum Pub Date : 2013-05-20 DOI: 10.1109/IPDPSW.2013.18

John D. Leidel, J. Bolding, Geoffrey Rogers

引用次数: 6