Pub Date : 2000-08-01DOI: 10.1109/HPDC.2000.868671
Mary P. Thomas, S. Mock, J. Boisseau
The NPACI (National Partnership for Advanced Computational Infrastructure) HotPage is a user portal that provides views of a distributed set of high-performance computing (HPC) resources as either an integrated meta-system or as individual machines. These Web pages run on any Web browser, regardless of the system or geographical location, and are supported by secure, encrypted log-in sessions where authenticated users can access their HPC system accounts and perform basic computational tasks. We describe the development of the Grid Portals Toolkit (GridPort), which is based on the architecture developed for the HotPage, and provide computational scientists and application developers with a set of simple, modular services and tools that allow application-level, customized science portal development and that facilitate seamless Web-based access to distributed computational resources and Grid services.
{"title":"Development of Web toolkits for computational science portals: the NPACI HotPage","authors":"Mary P. Thomas, S. Mock, J. Boisseau","doi":"10.1109/HPDC.2000.868671","DOIUrl":"https://doi.org/10.1109/HPDC.2000.868671","url":null,"abstract":"The NPACI (National Partnership for Advanced Computational Infrastructure) HotPage is a user portal that provides views of a distributed set of high-performance computing (HPC) resources as either an integrated meta-system or as individual machines. These Web pages run on any Web browser, regardless of the system or geographical location, and are supported by secure, encrypted log-in sessions where authenticated users can access their HPC system accounts and perform basic computational tasks. We describe the development of the Grid Portals Toolkit (GridPort), which is based on the architecture developed for the HotPage, and provide computational scientists and application developers with a set of simple, modular services and tools that allow application-level, customized science portal development and that facilitate seamless Web-based access to distributed computational resources and Grid services.","PeriodicalId":400728,"journal":{"name":"Proceedings the Ninth International Symposium on High-Performance Distributed Computing","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127653486","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}
Pub Date : 2000-08-01DOI: 10.1109/HPDC.2000.868654
A. Turgeon, Q. Snell, M. Clement
Heterogeneous parallel clusters of workstations are being used to solve many important computational problems. Scheduling parallel applications on the best collection of machines in a heterogeneous computing environment is a complex problem. Performance prediction is vital to good application performance in this environment since utilization of an ill-suited machine can slow the computation down significantly. The heterogeneity of the different pieces composing the parallel platform (network links, CPU, memory, and OS) makes it incredibly difficult to accurately predict performance. This paper addresses the problem of network performance prediction. Since communication speed is often the bottleneck for parallel application perfomance, network performance prediction is important to the overall performance prediction problem. A new methodology for characterizing network links and application's need for network resources is developed which makes use of performance surfaces (Clement et al., 1998). Mathematical operations on the performance surfaces are introduced that calculate an application's affinity for a network configuration. These affinity measures can be used for the scheduling of parallel applications.
异构并行工作站集群正被用于解决许多重要的计算问题。在异构计算环境中，在最佳机器集合上调度并行应用程序是一个复杂的问题。在这种环境中，性能预测对于良好的应用程序性能至关重要，因为使用不合适的机器会大大降低计算速度。组成并行平台的不同部分(网络链接、CPU、内存和操作系统)的异构性使得准确预测性能变得异常困难。本文主要研究网络性能预测问题。由于通信速度通常是并行应用程序性能的瓶颈，因此网络性能预测对于整体性能预测问题非常重要。一种利用性能面来描述网络链接和应用程序对网络资源需求的新方法被开发出来(Clement et al.， 1998)。介绍了性能面上的数学运算，用于计算应用程序对网络配置的亲和力。这些关联度量可用于并行应用程序的调度。
{"title":"Application placement using performance surfaces","authors":"A. Turgeon, Q. Snell, M. Clement","doi":"10.1109/HPDC.2000.868654","DOIUrl":"https://doi.org/10.1109/HPDC.2000.868654","url":null,"abstract":"Heterogeneous parallel clusters of workstations are being used to solve many important computational problems. Scheduling parallel applications on the best collection of machines in a heterogeneous computing environment is a complex problem. Performance prediction is vital to good application performance in this environment since utilization of an ill-suited machine can slow the computation down significantly. The heterogeneity of the different pieces composing the parallel platform (network links, CPU, memory, and OS) makes it incredibly difficult to accurately predict performance. This paper addresses the problem of network performance prediction. Since communication speed is often the bottleneck for parallel application perfomance, network performance prediction is important to the overall performance prediction problem. A new methodology for characterizing network links and application's need for network resources is developed which makes use of performance surfaces (Clement et al., 1998). Mathematical operations on the performance surfaces are introduced that calculate an application's affinity for a network configuration. These affinity measures can be used for the scheduling of parallel applications.","PeriodicalId":400728,"journal":{"name":"Proceedings the Ninth International Symposium on High-Performance Distributed Computing","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131926755","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}
Pub Date : 2000-08-01DOI: 10.1109/HPDC.2000.868641
G. Eisenhauer, F. Bustamante, K. Schwan
The Internet and the Grid are changing the face of high-performance computing. Rather than tightly-coupled SPMD-style components running in a single cluster, on a parallel machine, or even on the Internet programmed in MPI, applications are evolving into sets of collaborating components scattered across diverse computational elements. These collaborating components may run on different operating systems and hardware platforms and may be written by different organizations in different languages. Complete "applications" are constructed by assembling these components in a plug-and-play fashion. This new vision for high-performance computing demands features and characteristics which are not easily provided by traditional high-performance communications middleware. In response to these needs, we have developed ECho, a high-performance event-delivery middleware that meets the new demands of the Grid environment. ECho provides efficient binary transmission of event data with unique features that support data-type discovery and enterprise-scale application evolution. We present measurements detailing ECho's performance to show that ECho significantly outperforms other systems intended to provide this functionality, and that it provides throughput and latency comparable to the most efficient middleware infrastructures available.
{"title":"Event services for high performance computing","authors":"G. Eisenhauer, F. Bustamante, K. Schwan","doi":"10.1109/HPDC.2000.868641","DOIUrl":"https://doi.org/10.1109/HPDC.2000.868641","url":null,"abstract":"The Internet and the Grid are changing the face of high-performance computing. Rather than tightly-coupled SPMD-style components running in a single cluster, on a parallel machine, or even on the Internet programmed in MPI, applications are evolving into sets of collaborating components scattered across diverse computational elements. These collaborating components may run on different operating systems and hardware platforms and may be written by different organizations in different languages. Complete \"applications\" are constructed by assembling these components in a plug-and-play fashion. This new vision for high-performance computing demands features and characteristics which are not easily provided by traditional high-performance communications middleware. In response to these needs, we have developed ECho, a high-performance event-delivery middleware that meets the new demands of the Grid environment. ECho provides efficient binary transmission of event data with unique features that support data-type discovery and enterprise-scale application evolution. We present measurements detailing ECho's performance to show that ECho significantly outperforms other systems intended to provide this functionality, and that it provides throughput and latency comparable to the most efficient middleware infrastructures available.","PeriodicalId":400728,"journal":{"name":"Proceedings the Ninth International Symposium on High-Performance Distributed Computing","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114150779","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}
Pub Date : 2000-08-01DOI: 10.1109/HPDC.2000.868667
Daniel Andresen, R. Novotny
A fundamental problem in today's research environment, particularly in the biological and environmental sciences, is the inability of researchers to perform even simple investigations due to the inaccessibility and essential difficulty in acquiring and utilizing the necessary data. Often the data and simulation models are available via the Internet, but through a combination of obscurity, incompatibility and inefficiency, they are essentially unusable. Our system - the Modeler's Workbench - aims to address these fundamental problems. Novel aspects of our system include the use of XML as both a resource description language and a machine-independent data transfer mechanism. We build on top of existing metacomputing tools, while providing an infrastructure based on Java wrappers around existing simulations, to provide compatibility with our infrastructure while retaining legacy code and allowing for machine-dependent optimizations. We have developed a prototype of our system, for which we present the design and experimental data. We also discuss our future plans.
{"title":"The Modeler's Workbench: a system for dynamically distributed simulation and data collection","authors":"Daniel Andresen, R. Novotny","doi":"10.1109/HPDC.2000.868667","DOIUrl":"https://doi.org/10.1109/HPDC.2000.868667","url":null,"abstract":"A fundamental problem in today's research environment, particularly in the biological and environmental sciences, is the inability of researchers to perform even simple investigations due to the inaccessibility and essential difficulty in acquiring and utilizing the necessary data. Often the data and simulation models are available via the Internet, but through a combination of obscurity, incompatibility and inefficiency, they are essentially unusable. Our system - the Modeler's Workbench - aims to address these fundamental problems. Novel aspects of our system include the use of XML as both a resource description language and a machine-independent data transfer mechanism. We build on top of existing metacomputing tools, while providing an infrastructure based on Java wrappers around existing simulations, to provide compatibility with our infrastructure while retaining legacy code and allowing for machine-dependent optimizations. We have developed a prototype of our system, for which we present the design and experimental data. We also discuss our future plans.","PeriodicalId":400728,"journal":{"name":"Proceedings the Ninth International Symposium on High-Performance Distributed Computing","volume":"196 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114174589","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}
Pub Date : 2000-08-01DOI: 10.1109/HPDC.2000.868659
J. Becla, A. Hanushevsky
The BaBar experiment at the Stanford Linear Accelerator Center (SLAC) is designed to perform a high precision investigation of the decays of B-meson produced from electron-positron interactions. The experiment, started in May 1999, will generate approximately 300 TB/year of data for 10 years. All of the data will reside in objectivity databases (object oriented databases), accessible via the Advanced Multi-threaded Server (AMS). To date, over 70 TB of data have been placed in Objectivity/DB, making it one of the largest databases in the world. Providing access to such a large quantity of data through a database server is a daunting task. A full-scale testbed environment had to be developed to tune various software parameters and a fundamental change had to occur in the AMS architecture to allow it to scale past several hundred terabytes of data. Additionally, several protocol extensions had to be implemented to provide practical access to large quantities of data. The paper describes the design of the database and the changes that we needed to make in the AMS for scalability reasons and how the lessons we learned would be applicable to virtually any kind of database server seeking to operate in the Petabyte region.
{"title":"Creating large scale database servers","authors":"J. Becla, A. Hanushevsky","doi":"10.1109/HPDC.2000.868659","DOIUrl":"https://doi.org/10.1109/HPDC.2000.868659","url":null,"abstract":"The BaBar experiment at the Stanford Linear Accelerator Center (SLAC) is designed to perform a high precision investigation of the decays of B-meson produced from electron-positron interactions. The experiment, started in May 1999, will generate approximately 300 TB/year of data for 10 years. All of the data will reside in objectivity databases (object oriented databases), accessible via the Advanced Multi-threaded Server (AMS). To date, over 70 TB of data have been placed in Objectivity/DB, making it one of the largest databases in the world. Providing access to such a large quantity of data through a database server is a daunting task. A full-scale testbed environment had to be developed to tune various software parameters and a fundamental change had to occur in the AMS architecture to allow it to scale past several hundred terabytes of data. Additionally, several protocol extensions had to be implemented to provide practical access to large quantities of data. The paper describes the design of the database and the changes that we needed to make in the AMS for scalability reasons and how the lessons we learned would be applicable to virtually any kind of database server seeking to operate in the Petabyte region.","PeriodicalId":400728,"journal":{"name":"Proceedings the Ninth International Symposium on High-Performance Distributed Computing","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114618299","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}
Pub Date : 2000-08-01DOI: 10.1109/HPDC.2000.868636
Li Xiao, Xiaodong Zhang, Stefan A. Kubricht
Job migrations and network RAM are two approaches for effectively using global memory resources in a workstation cluster, aimed at reducing page faults in each local workstation and improving the overall performance of cluster computing. Using either remote executions or pre-emptive migrations, a load-sharing system is able to migrate a job from a workstation without sufficient memory space to a lightly loaded workstation with a large idle memory space for the migrated job. In a network RAM system, if a job cannot find sufficient memory space for its working sets, it utilizes idle memory space from other workstations in the cluster through remote paging. Conducting trace-driven simulations, we have compared the performance and tradeoffs of the two approaches and their impacts on job execution time and cluster scalability. Job migration-based load-sharing schemes are able to balance executions of jobs in a cluster well, while network RAM is able to satisfy data-intensive jobs which may not be migratable by sharing all the idle memory resources in a cluster. A network RAM cluster of workstations is scalable only if the network is sufficiently fast. We propose an improved load-sharing scheme by combining job migrations with network RAM for cluster computing. This scheme uses remote execution to initially allocate a job to the most lightly loaded workstation and, if necessary, network RAM to provide a larger memory space for the job than would be available otherwise. The improved scheme has the merits of both job migrations and network RAM. Our experiments show its effectiveness and scalability for cluster computing.
{"title":"Incorporating job migration and network RAM to share cluster memory resources","authors":"Li Xiao, Xiaodong Zhang, Stefan A. Kubricht","doi":"10.1109/HPDC.2000.868636","DOIUrl":"https://doi.org/10.1109/HPDC.2000.868636","url":null,"abstract":"Job migrations and network RAM are two approaches for effectively using global memory resources in a workstation cluster, aimed at reducing page faults in each local workstation and improving the overall performance of cluster computing. Using either remote executions or pre-emptive migrations, a load-sharing system is able to migrate a job from a workstation without sufficient memory space to a lightly loaded workstation with a large idle memory space for the migrated job. In a network RAM system, if a job cannot find sufficient memory space for its working sets, it utilizes idle memory space from other workstations in the cluster through remote paging. Conducting trace-driven simulations, we have compared the performance and tradeoffs of the two approaches and their impacts on job execution time and cluster scalability. Job migration-based load-sharing schemes are able to balance executions of jobs in a cluster well, while network RAM is able to satisfy data-intensive jobs which may not be migratable by sharing all the idle memory resources in a cluster. A network RAM cluster of workstations is scalable only if the network is sufficiently fast. We propose an improved load-sharing scheme by combining job migrations with network RAM for cluster computing. This scheme uses remote execution to initially allocate a job to the most lightly loaded workstation and, if necessary, network RAM to provide a larger memory space for the job than would be available otherwise. The improved scheme has the merits of both job migrations and network RAM. Our experiments show its effectiveness and scalability for cluster computing.","PeriodicalId":400728,"journal":{"name":"Proceedings the Ninth International Symposium on High-Performance Distributed Computing","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129134690","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}
Pub Date : 2000-08-01DOI: 10.1109/HPDC.2000.868634
R. Bramley, K. Chiu, S. Diwan, Dennis Gannon, M. Govindaraju, N. Mukhi, B. Temko, Madhuri Yechuri
Describes an approach to building a distributed software component system for scientific and engineering applications that is based on representing Computational Grid services as application-level software components. These Grid services provide tools such as registry and directory services, event services and remote component creation. While a service-based architecture for grids and other distributed systems is not new, this framework provides several unique features. First, the public interfaces to each software component are described as XML documents. This allows many adaptors and user interfaces to be generated from the specification dynamically. Second, this system is designed to exploit the resources of existing Grid infrastructures like Globus and Legion, and commercial Internet frameworks like e-speak. Third, and most important, the component-based design extends throughout the system. Hence, tools such as application builders, which allow users to select components, start them on remote resources, and connect and execute them, are also interchangeable software components. Consequently, it is possible to build distributed applications using a graphical "drag-and-drop" interface, a Web-based interface, a scripting language like Python, or an existing tool such as Matlab.
{"title":"A component based services architecture for building distributed applications","authors":"R. Bramley, K. Chiu, S. Diwan, Dennis Gannon, M. Govindaraju, N. Mukhi, B. Temko, Madhuri Yechuri","doi":"10.1109/HPDC.2000.868634","DOIUrl":"https://doi.org/10.1109/HPDC.2000.868634","url":null,"abstract":"Describes an approach to building a distributed software component system for scientific and engineering applications that is based on representing Computational Grid services as application-level software components. These Grid services provide tools such as registry and directory services, event services and remote component creation. While a service-based architecture for grids and other distributed systems is not new, this framework provides several unique features. First, the public interfaces to each software component are described as XML documents. This allows many adaptors and user interfaces to be generated from the specification dynamically. Second, this system is designed to exploit the resources of existing Grid infrastructures like Globus and Legion, and commercial Internet frameworks like e-speak. Third, and most important, the component-based design extends throughout the system. Hence, tools such as application builders, which allow users to select components, start them on remote resources, and connect and execute them, are also interchangeable software components. Consequently, it is possible to build distributed applications using a graphical \"drag-and-drop\" interface, a Web-based interface, a scripting language like Python, or an existing tool such as Matlab.","PeriodicalId":400728,"journal":{"name":"Proceedings the Ninth International Symposium on High-Performance Distributed Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129241157","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}
Pub Date : 2000-08-01DOI: 10.1109/HPDC.2000.868646
Darrell C. Anderson, J. Chase
Presents a recovery protocol for block I/O operations in Slice, a storage system architecture for high-speed LANs incorporating network-attached block storage. The goal of the Slice architecture is to provide a network file service with scalable bandwidth and capacity while preserving compatibility with off-the-shelf clients and file server appliances. The Slice prototype "virtualizes" the Network File System (NFS) protocol by interposing a request switching filter at the client's interface to the network storage system (e.g. in a network adapter or switch). The distributed Slice architecture separates functions that are typically combined in central file servers, introducing new challenges for failure atomicity. This paper presents a protocol for atomic file operations and recovery in the Slice architecture, and related support for reliable file storage using mirrored striping. Experimental results from the Slice prototype show that the protocol has low cost in the common case, allowing the system to deliver client file access bandwidths approaching Gbit/s network speeds.
{"title":"Failure-atomic file access in an interposed network storage system","authors":"Darrell C. Anderson, J. Chase","doi":"10.1109/HPDC.2000.868646","DOIUrl":"https://doi.org/10.1109/HPDC.2000.868646","url":null,"abstract":"Presents a recovery protocol for block I/O operations in Slice, a storage system architecture for high-speed LANs incorporating network-attached block storage. The goal of the Slice architecture is to provide a network file service with scalable bandwidth and capacity while preserving compatibility with off-the-shelf clients and file server appliances. The Slice prototype \"virtualizes\" the Network File System (NFS) protocol by interposing a request switching filter at the client's interface to the network storage system (e.g. in a network adapter or switch). The distributed Slice architecture separates functions that are typically combined in central file servers, introducing new challenges for failure atomicity. This paper presents a protocol for atomic file operations and recovery in the Slice architecture, and related support for reliable file storage using mirrored striping. Experimental results from the Slice prototype show that the protocol has low cost in the common case, allowing the system to deliver client file access bandwidths approaching Gbit/s network speeds.","PeriodicalId":400728,"journal":{"name":"Proceedings the Ninth International Symposium on High-Performance Distributed Computing","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124336849","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}
Pub Date : 2000-08-01DOI: 10.1109/HPDC.2000.868640
J. Gehring, A. Streit
Presents a robust software infrastructure for metacomputing. The system is intended to be used by others as a building block for large and powerful computational grids. Much effort has been taken to develop a fault-tolerant architecture that does not exhibit a single point of failure. Furthermore, we have designed the system to be modular, lean and portable. It is available as open source code and has been successfully compiled on POSIX- and Microsoft Windows-compliant platforms. The system does not originate from a laboratory environment but has proven its robustness within two large metacomputing installations. It embodies a modular concept which allows easy integration of new or modified components. Hence, it is not necessary to buy into the system as whole. We rather encourage others to use only those components that fit into their specific environments.
{"title":"Robust resource management for metacomputers","authors":"J. Gehring, A. Streit","doi":"10.1109/HPDC.2000.868640","DOIUrl":"https://doi.org/10.1109/HPDC.2000.868640","url":null,"abstract":"Presents a robust software infrastructure for metacomputing. The system is intended to be used by others as a building block for large and powerful computational grids. Much effort has been taken to develop a fault-tolerant architecture that does not exhibit a single point of failure. Furthermore, we have designed the system to be modular, lean and portable. It is available as open source code and has been successfully compiled on POSIX- and Microsoft Windows-compliant platforms. The system does not originate from a laboratory environment but has proven its robustness within two large metacomputing installations. It embodies a modular concept which allows easy integration of new or modified components. Hence, it is not necessary to buy into the system as whole. We rather encourage others to use only those components that fit into their specific environments.","PeriodicalId":400728,"journal":{"name":"Proceedings the Ninth International Symposium on High-Performance Distributed Computing","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125292004","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}
Pub Date : 2000-08-01DOI: 10.1109/HPDC.2000.868663
T. Hinke, Jason Novotny
The paper describes the development of a data mining system that is to operate on NASA's Information Power Grid (IPG). Mining agents will be staged to one or more processors on the IPG. There they will grow using just-in-time acquisition of new operations. They will mine data delivered using just-in-time delivery. Some initial experimental results are presented.
{"title":"Data mining on NASA's Information Power Grid","authors":"T. Hinke, Jason Novotny","doi":"10.1109/HPDC.2000.868663","DOIUrl":"https://doi.org/10.1109/HPDC.2000.868663","url":null,"abstract":"The paper describes the development of a data mining system that is to operate on NASA's Information Power Grid (IPG). Mining agents will be staged to one or more processors on the IPG. There they will grow using just-in-time acquisition of new operations. They will mine data delivered using just-in-time delivery. Some initial experimental results are presented.","PeriodicalId":400728,"journal":{"name":"Proceedings the Ninth International Symposium on High-Performance Distributed Computing","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117040122","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：