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4th International Conference/Exhibition on High Performance computing in the Asia-Pacific Region, HPC-Asia 2000

作者： Shen, X. Thiruvathukal, G. Liao, W. Choudhary, A. Singh, A. Center for Parallel and Distributed Computing Department of Electrical and Computer Engineering Northwestern University EvanstonIL60208 United States School of Computing Telecommunications and Information Sciences JHPC Laboratory DePaul University United States

ISBN: (纸本)0769505902

Large-scale scientific applications present great challenges to computational scientists in terms of obtaining high performance and in managing large datasets. These applications (most of which are simulations) may employ multiple techniques and resources in a heterogeneously distributed environment. Effective working in such an environment is crucial for modern large-scale simulations. In this paper, we present an integrated Java graphical user interface (IJ-GUI) that provides a control platform for managing complex programs and their large datasets easily. As far as performance is concerned, we present and evaluate our initial implementation of two optimization schemes: data replication and data prediction. Data replication can take advantage of 'temporal locality' by caching the remote datasets on local disks;data prediction, on the other hand, provides prefetch hints based on the datasets' past activities that are kept in databases. We first introduce the data contiguity concept in such an environment that guides data prediction. The relationship between the two approaches is discussed. © 2000 IEEE.

关键词： Forecasting

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An approach to support a single service provider address image for wide area networks environment

An approach to support a single service provider address ima...

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International Conference on parallel computing in Electrical Engineering (PARLEC)

作者： J.H. Abawajy Centre for Parallel and Distributed Computing School of Computer Science Carleton University Ottawa ONT Canada

Request dispatching mechanism is at the heart of any cluster-computing environment. The goal is to support a single service provider address image for a given cluster of workstations. That is to say a given cluster publicises a single IP address and client requests are addressed to that IP address. This means, from the client's viewpoint, there are no nodes in the cluster, only services and the network names through which they are accessible. As a result, the cluster becomes a single virtual node. We propose a simple and elegant scheme for making the cluster transparent to clients outside the cluster such that the clients can interact with the cluster as if it were a single high-performance and highly available resource.

关键词： Wide area networks Workstations computer architecture Network servers Dispatching Local area networks distributed computing computer science Heart Buildings

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Performance evaluation of nested-loop join processing on networks of workstations

Performance evaluation of nested-loop join processing on net...

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International Conference on parallel and distributed Systems (ICPADS)

作者： K. Imasaki S. Dandamudi Centre for Parallel and Distributed Computing School of Computer Science Carleton University Ottawa ONT Canada

Networks of workstations (NOWs) are attractive for parallel processing due to their cost advantage. This paper investigates the performance issues in processing join operations and the inherent tradeoff in the networked workstation environment. Specifically, we look at the performance of the nested-loop join algorithm. Since NOWs are heterogeneous in nature, load sharing is important for their performance. We evaluated the performance of three load sharing methods: static equal, static proportional and dynamic scheduling with fixed-chunk size. The three scheduling methods are evaluated on an experimental heterogeneous network of workstations with non-query background loads. Our experimental result suggest that, when there is no background load, dynamic scheduling outperforms static equal scheduling (up to 40%) and marginally better (about 10% better speedup) than the static proportional scheduling. When there is dynamic background load on nodes, dynamic scheduling provides substantial performance improvement over the static proportional scheduling (up to 50%) and static equal scheduling (up to about 100%). In all cases, selection of an appropriate chunk size is important in dynamic scheduling.

关键词： Workstations Dynamic scheduling Concurrent computing Databases parallel processing Master-slave Processor scheduling Application software Throughput distributed computing

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Time/space sharing distributed job scheduling policy in a workstation cluster environment

Time/space sharing distributed job scheduling policy in a wo...

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International Conference on parallel computing in Electrical Engineering (PARLEC)

作者： J.H. Abawajy S.P. Dandamudi Centre for Parallel and Distributed Computing School of Computer Science Carleton University Ottawa ONT Canada

This paper presents an algorithm for scheduling communication-intensive parallel applications in workstation clusters environment. The proposed scheduling policy combines the best attributes of both space-sharing and time-sharing principles and coexists with local schedulers (e.g., the Windows NT scheduler), which both provides coordinated scheduling and can generalise to provide a wide range of resource abstractions.

关键词： Workstations Processor scheduling Time sharing computer systems Operating systems distributed computing Delay computer science Clustering algorithms Scheduling algorithm Application software

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distributed hierarchical workstation cluster co-ordination scheme

Distributed hierarchical workstation cluster co-ordination s...

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International Conference on parallel computing in Electrical Engineering (PARLEC)

作者： J.H. Abawajy S.P. Dandamudi Centre for Parallel and Distributed Computing School of Computer Science Carleton University Ottawa ONT Canada

When a set of geographically distributed autonomous clusters of workstations are combined into a single large-scale virtual distributed system, a control mechanism for coordinating the activities of the combined system for effective utilisation of the resources is indispensable. This paper presents a co-ordination mechanism suitable for scheduling and distributing services across the host of such large-scale virtual distributed systems. The proposed scheme is scalable and reliable. Also, it combines both centralised and decentralised co-ordination mechanisms while eliminating/minimising their drawbacks.

关键词： Workstations Scheduling Resource management Large-scale systems distributed control Control systems Local area networks Wide area networks distributed computing computer science

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Data management for large‐scale scientific computations in high performance distributed systems

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Cluster computing 2000年第1期3卷 45-60页

作者： Choudhary, A. Kandemir, M. No, J. Memik, G. Shen, X. Liao, W. Nagesh, H. More, S. Taylor, V. Thakur, R. Stevens, R. Center for Parallel and Distributed Computing Department of Electrical and Computer Engineering Northwestern University Evanston USA Department of Computer Science and Engineering The Pennsylvania State University University Park USA Mathematics and Computer Science Division Argonne National Laboratory Argonne USA

With the increasing number of scientific applications manipulating huge amounts of data, effective high-level data management is an increasingly important problem. Unfortunately, so far the solutions to the high‐level data management problem either require deep understanding of specific storage architectures and file layouts (as in high-performance file storage systems) or produce unsatisfactory I/O performance in exchange for ease-of-use and portability (as in relational DBMSs). In this paper we present a novel application development environment which is built around an active meta-data management system (MDMS) to handle high-level data in an effective manner. The key components of our three-tiered architecture are user application, the MDMS, and a hierarchical storage system (HSS). Our environment overcomes the performance problems of pure database-oriented solutions, while maintaining their advantages in terms of ease-of-use and portability. The high levels of performance are achieved by the MDMS, with the aid of user-specified, performance-oriented directives. Our environment supports a simple, easy-to-use yet powerful user interface, leaving the task of choosing appropriate I/O techniques for the application at hand to the MDMS. We discuss the importance of an active MDMS and show how the three components of our environment, namely the application, the MDMS, and the HSS, fit together. We also report performance numbers from our ongoing implementation and illustrate that significant improvements are made possible without undue programming effort.

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A novel application development environment for large-scale scientific computations 00

A novel application development environment for large-scale ...

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Proceedings of the 14th international conference on Supercomputing

作者： X. Shen W. Liao A. Choudhary G. Memik M. Kandemir S. More G. Thiruvathukal A. Singh Center for Parallel and Distributed Computing Department of Electrical and Computer Engineering Northwestern University Evanston IL Department of Computer Science and Engineering The Pennsylvania State University University Park PA School of Computing Telecommunications and Information Sciences JHPC Laboratory Depaul University

Our results demonstrate that our novel application development environment provides both ease-of-use and high performance for large-scale, I/O-intensive scientific applications.

ISBN: (纸本)9781581132700

Our results demonstrate that our novel application development environment provides both ease-of-use and high performance for large-scale, I/O-intensive scientific applications.

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Buffer management in wormhole-routed torus multicomputer networks 7th

Buffer management in wormhole-routed torus multicomputer net...

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7th International Conference on High-Performance computing and Networking, HPCN Europe 1999

作者： Kotapati, Kamala Dandamudi, Sivarama P. Newbridge Networks Kanata Canada Center for Parallel and Distributed Computing School of Computer Science Carleton University Ottawa Canada

ISBN: (纸本)3540658211

This paper focuses on buffer management issues in wormhole-routed torus multicomputer networks. The commonly used buffer organizations are the centralized and dedicated buffer organizations. The results presented in this paper indicate that the dedicated buffer organization provides better performance than the centralized organization under uniform traffic. Under high hot-spot traffic, the centralized organization outperforms the dedicated. The hybrid buffer organization proposed in this paper inherits the merits of the centralized and distributed organizations. The results presented suggest that the hybrid buffer organization can be designed to configure dynamically from the dedicated to centralized depending on the traffic conditions. © Springer-Verlag Berlin Heidelberg 1999.

关键词： computers

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Centralized architecture for parallel query processing on networks of workstations 7th

Centralized architecture for parallel query processing on ne...

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7th International Conference on High-Performance computing and Networking, HPCN Europe 1999

作者： Zeng, Sijun Dandamudi, Sivarama P. CrossKeys System Corporation Kanata Canada Center for Parallel and Distributed Computing School of Computer Science Carleton University Ottawa Canada

ISBN: (纸本)3540658211

Network of workstations (NOW) is a cost-effective alternative to a multiprocessor system. Here we propose a centralized architecture for parallel query processing on network of workstations. We describe a three-level processing strategy and evaluate its performance. The top two levels use a space-sharing technique to assign a partition to a query. The third-level uses a chunk-based load sharing policy to accommodate dynamic local load present on the workstations. To evaluate the performance of this three-level strategy, we have implemented it using PVM on a Pentium-based NOW. © Springer-Verlag Berlin Heidelberg 1999.

关键词： Cost effectiveness

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Data management for large-scale scientific computations in high performance distributed systems

Data management for large-scale scientific computations in h...

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International Symposium on High Performance distributed computing

作者： A. Choudhary M. Kandemir H. Nagesh J. No X. Shen V. Taylor S. More R. Thakur Center for Parallel and Distributed Computing Department of Electrical and Computer Engineering Northwestern University Evanston IL USA Mathematics and Computer Science Division Argonne National Laboratory Argonne IL USA

With the increasing number of scientific applications manipulating huge amounts of data, effective data management is an increasingly important problem. Unfortunately, so far the solutions to this data management problem either require deep understanding of specific storage architectures and file layouts (as in high-performance file systems) or produce unsatisfactory I/O performance in exchange for ease-of-use and portability (as in relational DBMSs). In this paper we present a new environment which is built around an active meta-data management system (MDMS). The key components of our three-tiered architecture are user application, the MDMS, and a hierarchical storage system (HSS). Our environment overcomes the performance problems of pure database-oriented solutions, while maintaining their advantages in terms of ease-of-use and portability. The high levels of performance are achieved by the MDMS, with the aid of user-specified directives. Our environment supports a simple, easy-to-use yet powerful user interface, leaving the task of choosing appropriate I/O techniques to the MDMS. We discuss the importance of an active MDMS and show how the three components, namely application, the MDMS, and the HSS, fit together. We also report performance numbers from our initial implementation and illustrate that significant improvements are made possible without undue programming effort.

关键词： Large-scale systems distributed computing High performance computing Data visualization Engineering management Concurrent computing Relational databases Art Data analysis Image analysis

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