Seventh IEEE International Symposium on Cluster Computing and the Grid (CCGrid '07)最新文献_第5页

A Model for Automatic On-Line Process Behavior Extraction, Classification and Prediction in Heterogeneous Distributed Systems 异构分布式系统在线过程行为自动提取、分类与预测模型

Seventh IEEE International Symposium on Cluster Computing and the Grid (CCGrid '07) Pub Date : 2007-05-14 DOI: 10.1109/CCGRID.2007.6

E. Dodonov, R. Mello

引用次数: 7

Transparent Symmetric Active/Active Replication for Service-Level High Availability 用于服务级高可用性的透明对称活动/活动复制

Seventh IEEE International Symposium on Cluster Computing and the Grid (CCGrid '07) Pub Date : 2007-05-14 DOI: 10.1109/CCGRID.2007.116

C. Engelmann, S. Scott, C. Leangsuksun, Xubin He

引用次数: 18

A Simulation Study of Data Partitioning Algorithms for Multiple Clusters 多簇数据划分算法的仿真研究

Seventh IEEE International Symposium on Cluster Computing and the Grid (CCGrid '07) Pub Date : 2007-05-14 DOI: 10.1109/CCGRID.2007.13

Chen Yu, D. Marinescu, H. Siegel, J. Morrison

引用次数: 3

Understanding the Impact of Multi-Core Architecture in Cluster Computing: A Case Study with Intel Dual-Core System 理解多核架构对集群计算的影响:以Intel双核系统为例

Seventh IEEE International Symposium on Cluster Computing and the Grid (CCGrid '07) Pub Date : 2007-05-14 DOI: 10.1109/CCGRID.2007.119

Lei Chai, Qi Gao, D. Panda

{"title":"Understanding the Impact of Multi-Core Architecture in Cluster Computing: A Case Study with Intel Dual-Core System","authors":"Lei Chai, Qi Gao, D. Panda","doi":"10.1109/CCGRID.2007.119","DOIUrl":"https://doi.org/10.1109/CCGRID.2007.119","url":null,"abstract":"Multi-core processors are growing as a new industry trend as single core processors rapidly reach the physical limits of possible complexity and speed. In the new Top500 supercomputer list, more than 20% processors belong to the multi-core processor family. However, without an in-depth study on application behaviors and trends on multi-core clusters, we might not be able to understand the characteristics of multi-core cluster in a comprehensive manner and hence not be able to get optimal performance. In this paper, we take on these challenges and design a set of experiments to study the impact of multi-core architecture on cluster computing. We choose to use one of the most advanced multi-core servers, Intel Bensley system with Woodcrest processors, as our evaluation platform, and use benchmarks including HPL, NAMD, and NAS as the applications to study. From our message distribution experiments, we find that on an average about 50% messages are transferred through intra-node communication, which is much higher than intuition. This trend indicates that optimizing intra- node communication is as important as optimizing inter- node communication in a multi-core cluster. We also observe that cache and memory contention may be a potential bottleneck in multi-core clusters, and communication middleware and applications should be multi-core aware to alleviate this problem. We demonstrate that multi-core aware algorithm, e.g. data tiling, improves benchmark execution time by up to 70%. We also compare the scalability of a multi-core cluster with that of a single-core cluster and find that the scalability of the multi-core cluster is promising.","PeriodicalId":278535,"journal":{"name":"Seventh IEEE International Symposium on Cluster Computing and the Grid (CCGrid '07)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124921119","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: 190

Redundancy Management for P2P Storage P2P存储冗余管理

Seventh IEEE International Symposium on Cluster Computing and the Grid (CCGrid '07) Pub Date : 2007-05-14 DOI: 10.1109/CCGRID.2007.93

C. Williams, Philippe Huibonhoa, J. Holliday, A. Hospodor, T. Schwarz

引用次数: 18

Exploiting Heterogeneity for Collective Data Downloading in Volunteer-based Networks 基于志愿者网络的集体数据下载的异质性研究

Seventh IEEE International Symposium on Cluster Computing and the Grid (CCGrid '07) Pub Date : 2007-05-14 DOI: 10.1109/CCGRID.2007.50

Jinoh Kim, A. Chandra, J. Weissman

{"title":"Exploiting Heterogeneity for Collective Data Downloading in Volunteer-based Networks","authors":"Jinoh Kim, A. Chandra, J. Weissman","doi":"10.1109/CCGRID.2007.50","DOIUrl":"https://doi.org/10.1109/CCGRID.2007.50","url":null,"abstract":"Scientific computing is being increasingly deployed over volunteer-based distributed computing environments consisting of idle resources on donated user machines. A fundamental challenge in these environments is the dissemination of data to the computation nodes, with the successful completion of jobs being driven by the efficiency of collective data download across compute nodes, and not only the individual download times. This paper considers the use of a data network consisting of data distributed across a set of data servers, and focuses on the server selection problem: how do individual nodes select a server for downloading data to minimize the communication makespan - the maximal download time for a data file. Through experiments conducted on a pastry network running on PlanetLab, we demonstrate that nodes in a volunteer-based network are heterogeneous in terms of several metrics, such as bandwidth, load, and capacity, which impact their download behavior. We propose new server selection heuristics that incorporate these metrics, and demonstrate that these heuristics outperform traditional proximity-based server selection, reducing average makespans by at least 30%. We further show that incorporating information about download concurrency avoids overloading servers, and improves performance by about 17-43% over heuristics considering only proximity and bandwidth.","PeriodicalId":278535,"journal":{"name":"Seventh IEEE International Symposium on Cluster Computing and the Grid (CCGrid '07)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129164727","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: 4

An Integrated Approach for Managing Peer-to-Peer Desktop Grid Systems 管理点对点桌面网格系统的集成方法

Seventh IEEE International Symposium on Cluster Computing and the Grid (CCGrid '07) Pub Date : 2007-05-14 DOI: 10.1109/CCGRID.2007.21

S. Schulz, W. Blochinger

引用次数: 6

Dynamic Condor-based Services for Distributed Image Analysis 基于动态秃鹰的分布式图像分析服务

Seventh IEEE International Symposium on Cluster Computing and the Grid (CCGrid '07) Pub Date : 2007-05-14 DOI: 10.1109/CCGRID.2007.44

Simon Caton, O. Rana, B. Batchelor

{"title":"Dynamic Condor-based Services for Distributed Image Analysis","authors":"Simon Caton, O. Rana, B. Batchelor","doi":"10.1109/CCGRID.2007.44","DOIUrl":"https://doi.org/10.1109/CCGRID.2007.44","url":null,"abstract":"Interactive image processing is an important requirement in many industrial applications, such as the inspection of industrial parts within a manufacturing environment, or the processing of images from surveillance cameras. Being able to achieve this quickly and accurately is often essential for the success of such industrial applications. A service-based approach that autonomously launches Image Analysis Services (accessible through a Central Service Manager) onto spare network resources through a Condor system is presented. This allows high throughput analysis of these images in a dynamic resource pool. The Central Service Manager reacts to new tasks submitted to the Image Analysis Services and is able to add new service instances to manage these tasks dynamically. Each service instance here corresponds to a computational resource that is able to execute image processing algorithms. New service instances may be requested by the Central Service Manager from the Condor system, based on the number of tasks that need to be processed. This enables entire image repositories to be acted upon interactively and in parallel, as opposed to the analysis of single images individually. The approach is demonstrated through a campus-wide test bed utilising a Condor system with 90 machines.","PeriodicalId":278535,"journal":{"name":"Seventh IEEE International Symposium on Cluster Computing and the Grid (CCGrid '07)","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124598739","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

Access Control Policy Combinations for the Grid Using the Policy Machine 使用策略机的网格访问控制策略组合

Seventh IEEE International Symposium on Cluster Computing and the Grid (CCGrid '07) Pub Date : 2007-05-14 DOI: 10.1109/CCGRID.2007.15

Vincent C. Hu, David F. Ferraiolo, K. Scarfone

引用次数: 13

Integrated Data Reorganization and Disk Mapping for Reducing Disk Energy Consumption 集成数据重组和磁盘映射，降低磁盘能耗

Seventh IEEE International Symposium on Cluster Computing and the Grid (CCGrid '07) Pub Date : 2007-05-14 DOI: 10.1109/CCGRID.2007.64

S. Son, M. Kandemir

{"title":"Integrated Data Reorganization and Disk Mapping for Reducing Disk Energy Consumption","authors":"S. Son, M. Kandemir","doi":"10.1109/CCGRID.2007.64","DOIUrl":"https://doi.org/10.1109/CCGRID.2007.64","url":null,"abstract":"Increasing power consumption of high-performance systems leads to reliability, survivability, and cooling related problems. Motivated by this observation, several recent efforts focused on reducing disk power consumption through hardware, OS and compiler based techniques. This paper presents a novel approach to reducing disk power consumption of large-scale, array-intensive scientific applications. It proposes and evaluates a compiler-based approach that employs two complementary techniques: data reorganization and disk mapping. The first of these, data reorganization, determines a suitable layout for data in the array space, whereas the second technique, disk mapping, decides the corresponding layout in the disk space. The goal of data reorganization and disk mapping is to ensure that data (from the different disk-resident arrays) that are accessed within the same loop iteration are colocated in the same set of disks. In this way, we can increase disk inter-access times (idle periods of disks) and this in turn allows better exploitation of the underlying hardware mechanisms used for reducing power. Our experiments with eight disk I/O-intensive scientific applications indicate that the proposed approach brings significant reductions in energy consumption, whether the underlying disk system uses spin-down disks or speed-reduced disks, two previously- proposed hardware-based disk power reduction schemes. The results also show that both the components of our scheme (data reorganization and disk mapping) are very important since applying any of these components alone does not generate large savings for most of our applica tions.","PeriodicalId":278535,"journal":{"name":"Seventh IEEE International Symposium on Cluster Computing and the Grid (CCGrid '07)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117147084","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