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Cluster Computing and the Grid, 2002. 2nd IEEE/ACM International Symposium on

Date 21-24 May 2002

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Displaying Results 1 - 25 of 94
  • Message from the General Chairs

    Publication Year: 2002 , Page(s): xiv
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  • Message from the Program Committee Chair

    Publication Year: 2002 , Page(s): xvi
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  • Message from the Workshop Chair

    Publication Year: 2002 , Page(s): xvii
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  • Symposium Chairs and Committees

    Publication Year: 2002 , Page(s): xviii
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  • Symposium reviewers

    Publication Year: 2002 , Page(s): xx
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  • Workshop reviewers

    Publication Year: 2002 , Page(s): xxi
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  • Jini and the Grid

    Publication Year: 2002 , Page(s): 2
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  • Three Tools to Help with Cluster and Grid Computing: SANS-Effort, PAPI, and NetSolve

    Publication Year: 2002 , Page(s): 3
    Cited by:  Patents (3)
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  • LDAP and the Grid

    Publication Year: 2002 , Page(s): 4
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  • Cluster Tools

    Publication Year: 2002 , Page(s): 5
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  • The Philosophy of TeraGrid: Building an Open, Extensible, Distributed TeraScale Facility

    Publication Year: 2002 , Page(s): 8
    Cited by:  Papers (18)
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  • Distributed Computing Technologies and Their Application to Drug Discovery

    Publication Year: 2002 , Page(s): 9
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  • From the "Higgs Particle" to Technology, From the Web to the Grid: Fundamental Science, Technology, and International Cooperation

    Publication Year: 2002 , Page(s): 10
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  • Drug Discovery on Cluster Farms

    Publication Year: 2002 , Page(s): 12
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  • Visualization and VR for the Grid

    Publication Year: 2002 , Page(s): 13
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  • A Report from the U.S. National Science Foundation Blue Ribbon Panel on Cyberinfrastructure

    Publication Year: 2002 , Page(s): 16
    Cited by:  Papers (3)
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  • Grids Deployment at the Crossroads - An Update on the EU-Funded Research Efforts

    Publication Year: 2002 , Page(s): 18
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  • Adaptive Scheduling under Memory Pressure on Multiprogrammed Clusters

    Publication Year: 2002 , Page(s): 22
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (152 KB) |  | HTML iconHTML  

    This paper presents scheduling techniques that enable the adaptation of parallel programs to clustered computational farms with limited memory capacity. The purpose of the techniques is to coschedule communicating processes and prevent paging, using two cooperating extensions to the kernel scheduler. A paging prevention module enables memory-bound programs to adapt to memory short-age, by suspending their threads at well-defined execution points. The associated operating system interface provides a generic mechanism that enables programs to adapt in different ways, including application-specific forms of adaptation. At the same time, a dynamic coscheduling heuristic implemented in the kernel scheduler increases periodically the priority of communicating processes so that parallel jobs are eased through communication points. We show that when a parallel job competes with randomized sequential load running in the nodes of the cluster, the combination of coscheduling and paging prevention reduces drastically the slowdown of the job at high levels of memory utilization. We also show that if memory resources are ample, coscheduling should take priority over paging prevention, whereas if memory resources are scarce, preventing paging should take priority over coscheduling. View full abstract»

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  • User-Centric Performance Analysis of Market-Based Cluster Batch Schedulers

    Publication Year: 2002 , Page(s): 30
    Cited by:  Papers (33)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (120 KB) |  | HTML iconHTML  

    This paper presents a performance analysis of market-based batch schedulers for clusters of workstations. In contrast to previous work, we use user-centric performance metrics as the basis for system evaluation. Each user is modeled as having a utility function for each job which measures value delivered to the user as function of execution time. Summing over all utility functions in the workload, we use aggregate utility as a measure of overall value delivered to users. With aggregate utility as the performance metric, simulations are used to quantify the performance of both market-based and traditional batch scheduling algorithms under a variety of synthetic work-loads. Results show that an auction-based batch scheduling algorithm improves performance by a factor of up to 2-5x for sequential workloads and up to 14x for highly parallel workloads compared to traditional scheduling algorithms. View full abstract»

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  • On Advantages of Grid Computing for Parallel Job Scheduling

    Publication Year: 2002 , Page(s): 39
    Cited by:  Papers (35)  |  Patents (5)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (152 KB) |  | HTML iconHTML  

    This paper addresses the potential benefit of sharing jobs between independent sites in a grid computing environment. Also the aspect of parallel multi-site job execution on different sites is discussed. To this end, various scheduling algorithms have been simulated for several machine configurations with different workloads which have been derived from real traces. The results showed that a significant improvement in terms of a smaller average response time is achievable. The usage of multi-site applications can additionally improve the results as long as the increase of the execution time due to communication overhead is limited to about 25%. View full abstract»

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  • Representing Dynamic Performance Information in Grid Environments with the Network Weather Service

    Publication Year: 2002 , Page(s): 48
    Cited by:  Papers (9)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (224 KB) |  | HTML iconHTML  

    In this paper, we discuss requirements for integrating dynamic performance information from the Network Weather Service (NWS) into the Grid Information Service infrastructure (GIS). We describe the object model that NWS uses internally and provide some rationale for its structure. Finally, we present the NWS 's implementation of a caching LDAP daemon that integrates NWS information into the reference GIS -the Glob s MDS. View full abstract»

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  • Neptune: A Dynamic Resource Allocation and Planning System for a Cluster Computing Utility

    Publication Year: 2002 , Page(s): 57
    Cited by:  Papers (5)  |  Patents (8)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (272 KB) |  | HTML iconHTML  

    We present Neptune - the resource director of Océano, a policy driven fabric management system that dynamically reconfigures resources in a computing utility cluster. Neptune implements an on-line control mechanism subject to policy-based performance and resource configuration objectives. Neptune reassigns servers and bandwidth among a set of service domains, based on pre-defined policy, in response to workload changes. It builds and executes a reconfiguration plan through a planning framework, breaking reconfiguration objectives into individual tasks delegated to set of lower level resource managers. We describe an example decision policy algorithm that we implemented and demonstrated in an 80 server multi-domain computing utility. View full abstract»

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  • Tracing a Large-Scale Peer to Peer System: An Hour in the Life of Gnutella

    Publication Year: 2002 , Page(s): 65
    Cited by:  Papers (23)  |  Patents (11)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (368 KB) |  | HTML iconHTML  

    Peer-to-peer computing and networking, an emerging model of communication and computation, has recently started to gain significant acceptance. This model not only enables clients to take a more active role in the information dissemination process, but also may significantly increase the performance and reliability of the overall system, by eliminating the traditional notion of the "server" which could be a single point of failure, and a potential bottleneck. Although peer-to-peer systems enjoy significant and continually increasing popularity, we still do not have a clear understanding of the magnitude, the traffic patterns, and the potential performance bottlenecks of the recent peer-to-peer networks. In this paper we study the traffic patterns of Gnutella, a popular large-scale peer-to-peer system, and show that traffic patterns are very bursty even over several time scales. We especially focus on the types of the queries submitted by Gnutella peers, and their associated replies. We show that the queries submitted exhibit significant amounts of locality, that is, queries tend to be frequently and repeatedly submitted. To capitalize on this locality, we propose simple Gnutella caching mechanisms that cache query responses. Using trace-driven simulation we evaluate the effectiveness of Gnutella caching and show that it improves performance by as much as a factor of two. View full abstract»

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  • RVision: An Open and High Configurable Tool for Cluster Monitoring

    Publication Year: 2002 , Page(s): 75
    Cited by:  Papers (9)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (176 KB) |  | HTML iconHTML  

    In this paper we present the design and implementation of RVision (Remote Vision), an open architecture, high configurable tool for cluster monitoring. We focus on the description of it's modular architecture, emphasizing the new concepts we are introducing for cluster monitoring, such as monitoring sessions and the support for dynamic linking of monitoring libraries. In addition, we measure intrusion with several benchmarks and applications under different scenarios. RVision distinguishes itself from other available tools for cluster monitoring because of its open architecture, high configurability, and low intrusion. It is being used in production mode, in our research center, and has proven itself as a powerful alternative for cluster monitoring, especially in heterogeneous clusters and cluster of clusters. View full abstract»

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  • Implementing Data Cube Construction using a Cluster Middleware: Algorithms, Implementation Experience, and Performance Evaluation

    Publication Year: 2002 , Page(s): 84
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (136 KB) |  | HTML iconHTML  

    With increases in the amount of data available for analysis in commercial settings, On Line Analytical Processing (OLAP) and decision support have become important applications for high performance computing. Implementing such applications on clusters requires a lot of expertise and effort, particularly because of the sizes of input and outputdatasets. In this paper, we describe our experiences in developing one such application using a cluster middleware, called ADR. We focus on the problem of data cube construction, which commonly arises in multi-dimensional OLAP. We show how ADR, originally developed for scientific data intensive applications, can be used for carrying out an efficient and scalable data cube construction implementation. A particular issue with the use of ADR is tiling of output datasets. We present new algorithms that combine inter-processor communication and tiling within each processor. These algorithms preserve the important properties that are desirable from any parallel data cube construction algorithm. We have carried out a detailed evaluation of our implementation. The main results from our experiments are as follows: 1) High speedups are achieved on both dense and sparse datasets, even though we have used simple algorithms that sequentialize a part of the computation, 2) The execution time depends only upon the amount of computation, and does not increase in a super-linear fashion as the dataset size or the number of tiles increases, and 3) As the datasets become more sparse, sequential performance degrades, but the parallel speedups are still quite good. View full abstract»

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