2006 IEEE Challenges of Large Applications in Distributed Environments最新文献

Distribution and partitioning techniques for NVEs: the case of EVE nve的分布和划分技术:以EVE为例

2006 IEEE Challenges of Large Applications in Distributed Environments Pub Date : 2006-07-10 DOI: 10.1109/CLADE.2006.1652058

C. Bouras, E. Giannaka, Alexandros Panagopoulos, T. Tsiatsos

{"title":"Distribution and partitioning techniques for NVEs: the case of EVE","authors":"C. Bouras, E. Giannaka, Alexandros Panagopoulos, T. Tsiatsos","doi":"10.1109/CLADE.2006.1652058","DOIUrl":"https://doi.org/10.1109/CLADE.2006.1652058","url":null,"abstract":"The majority of the systems and platforms developed for supporting distributed virtual environments are based on the concept of distribution from the early beginning of their development. In this paper we present the migration to a distributed virtual environment from a traditional client-server architecture. In particular, this paper describes the case of EVE, a networked virtual environment originally aimed to support small-scale applications. EVE started as a standard client-multi server architecture, which could support multiple concurrent virtual worlds with a maximum number of seventeen simultaneous participants in each of these worlds. However, the need to support larger-scale applications revealed that the traditional architecture, upon which EVE was based, is insufficient to meet the needs of these applications, which are large both in the sense of virtual space and graphics and in regard to the number of concurrent participants. This paper discusses the migration of EVE to a distributed platform, which is able to support large-scale networked virtual environments. In particular, the paper describes the modifications realized in the architectural model of the initial platform for supporting effectively large-scale applications. The basic entities of the distributed model are presented, their operations, as well as the interconnection among them. In addition, the paper presents an initial approach of the algorithm that is adopted for the efficient partitioning of the virtual world and the assignment of the clients to the entities and resources of the distributed platform. The approach presented is space-object driven, in the sense that both the actual size of the virtual space along with the number of objects with which the user can interact is taken into account during the partitioning","PeriodicalId":299480,"journal":{"name":"2006 IEEE Challenges of Large Applications in Distributed Environments","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124684854","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

Exploring the hyper-grid idea with grand challenge applications: the DEISA-TeraGrid interoperability demonstration 探索具有重大挑战应用的超电网理念:DEISA-TeraGrid互操作性演示

2006 IEEE Challenges of Large Applications in Distributed Environments Pub Date : 2006-07-10 DOI: 10.1109/CLADE.2006.1652053

P. Andrews, M. Büchli, R. Harkness, R. Hatzky, C. Jordan, H. Lederer, R. Niederberger, T. Rimovsky, Andreas Schott, T. Soddemann, V. Springel

{"title":"Exploring the hyper-grid idea with grand challenge applications: the DEISA-TeraGrid interoperability demonstration","authors":"P. Andrews, M. Büchli, R. Harkness, R. Hatzky, C. Jordan, H. Lederer, R. Niederberger, T. Rimovsky, Andreas Schott, T. Soddemann, V. Springel","doi":"10.1109/CLADE.2006.1652053","DOIUrl":"https://doi.org/10.1109/CLADE.2006.1652053","url":null,"abstract":"A supercomputing hyper-grid spanning two continents was created to move a step towards interoperability of leading grids. A dedicated network connection was established between DEISA, the leading European supercomputing grid, and TeraGrid, the leading American supercomputing grid. Both grids have adopted the approach of establishing a common, high performance global file system, the wide-area version of IBM's GPFS. Teragrid's approach is based on a single site server solution under Linux, hosted by San Diego Supercomputer Centre, DEISA's approach is a multi-site server solution, with currently servers in France, Germany and Italy. These two grid-internal global file systems were interconnected over a dedicated, trusted network connection. During the Supercomputing Conference 2005, grand challenge applications were carried out both within DEISA and within TeraGrid, and results were written transparently to the combined global file system with physically distributed locations of the involved disk systems. Simulations were carried out in Europe and in America, and results were directly written to the respective remote continent, accessible for all participating scientists in both continents, and were then directly further processed for visualization in a third location, the SC05 exhibition hall in Seattle. Grand challenge applications used for the demo included a protein structure prediction and a cosmological simulation carried out at San Diego Supercomputer Center (SDSC), US (www.sdsc.edu) and a Gyrokinetic turbulence simulation and also a cosmological simulation carried out at Garching Computing Centre of the Max Planck Society (RZG), Germany (www.rzg.mpg.de)","PeriodicalId":299480,"journal":{"name":"2006 IEEE Challenges of Large Applications in Distributed Environments","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128068835","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

Enabling parallel scientific applications with workflow tools 使用工作流工具启用并行科学应用程序

2006 IEEE Challenges of Large Applications in Distributed Environments Pub Date : 2006-07-10 DOI: 10.1109/CLADE.2006.1652055

Adam Lathers, Mei-Hui Su, A. Kulungowski, A. Lin, Gaurang Mehta, S. Peltier, E. Deelman, Mark Ellisman

{"title":"Enabling parallel scientific applications with workflow tools","authors":"Adam Lathers, Mei-Hui Su, A. Kulungowski, A. Lin, Gaurang Mehta, S. Peltier, E. Deelman, Mark Ellisman","doi":"10.1109/CLADE.2006.1652055","DOIUrl":"https://doi.org/10.1109/CLADE.2006.1652055","url":null,"abstract":"Electron tomography is a powerful tool for deriving three-dimensional (3D) structural information about biological systems within the spatial scale spanning 1 nm3 and 10 mm3. With this technique, it is possible to derive detailed models of sub-cellular components such as organelles and synaptic complexes and to resolve the 3D distribution of their protein constituents in situ. Due in part to exponentially growing raw data-sizes, there continues to be a need for the increased integration of high-performance computing (HPC) and grid technologies with traditional electron tomography processes to provide faster data processing throughput. This is increasingly relevant because emerging mathematical algorithms that provide better data fidelity are more computationally intensive for larger raw data sizes. Progress has been made towards the transparent use of HPC and grid tools for launching scientific applications without passing on the necessary administrative overhead and complexity (resource administration, authentication, scheduling, data delivery) to the non-computer scientist end-user. There is still a need, however, to simplify the use of these tools for applications developers who are developing novel algorithms for computation. Here we describe the architecture of the Telescience project (http://telescience.ucsd.edu), specifically the use of layered workflow technologies to parallelize and execute scientific codes across a distributed and heterogeneous computational resource pool (including resources from the TeraGrid and OptlPuter projects) without the need for the application developer to understand the intricacies of the grid","PeriodicalId":299480,"journal":{"name":"2006 IEEE Challenges of Large Applications in Distributed Environments","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131608965","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: 25

A new paradigm in data intensive computing: Stork and the data-aware schedulers 数据密集型计算的新范式:Stork和数据感知调度器

2006 IEEE Challenges of Large Applications in Distributed Environments Pub Date : 2006-07-10 DOI: 10.1109/CLADE.2006.1652048

T. Kosar

{"title":"A new paradigm in data intensive computing: Stork and the data-aware schedulers","authors":"T. Kosar","doi":"10.1109/CLADE.2006.1652048","DOIUrl":"https://doi.org/10.1109/CLADE.2006.1652048","url":null,"abstract":"The unbounded increase in the computation and data requirements of scientific applications has necessitated the use of widely distributed compute and storage resources to meet the demand. In a widely distributed environment, data is no more locally accessible and has thus to be remotely retrieved and stored. Efficient and reliable access to data sources and archiving destinations in such an environment brings new challenges. Placing data on temporary local storage devices offers many advantages, but such \"data placements\" also require careful management of storage resources and data movement, i.e. allocating storage space, staging-in of input data, staging-out of generated data, and de-allocation of local storage after the data is safely stored at the destination. Traditional systems closely couple data placement and computation, and consider data placement as a side effect of computation. Data placement is either embedded in the computation and causes the computation to delay, or performed as simple scripts which do not have the privileges of a job. The insufficiency of the traditional systems and existing CPU-oriented schedulers in dealing with the complex data handling problem has yielded a new emerging era: the data-aware schedulers. One of the first examples of such schedulers is the Stork data placement scheduler. In this paper, we discuss the limitations of the traditional schedulers in handling the challenging data scheduling problem of large scale distributed applications; give our vision for the new paradigm in data-intensive scheduling; and elaborate on our case study: the Stork data placement scheduler","PeriodicalId":299480,"journal":{"name":"2006 IEEE Challenges of Large Applications in Distributed Environments","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117221061","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: 28

Managing grid messaging middleware 管理网格消息传递中间件

2006 IEEE Challenges of Large Applications in Distributed Environments Pub Date : 2006-07-10 DOI: 10.1109/CLADE.2006.1652059

H. Gadgil, G. Fox, S. Pallickara, M. Pierce

引用次数: 10

Implementation of a distributed rendering environment for the TeraGrid TeraGrid的分布式渲染环境的实现

2006 IEEE Challenges of Large Applications in Distributed Environments Pub Date : 2006-07-10 DOI: 10.1109/CLADE.2006.1652049

S. L. Gooding, Laura L. Arns, Preston Smith, Jenett Tillotson

{"title":"Implementation of a distributed rendering environment for the TeraGrid","authors":"S. L. Gooding, Laura L. Arns, Preston Smith, Jenett Tillotson","doi":"10.1109/CLADE.2006.1652049","DOIUrl":"https://doi.org/10.1109/CLADE.2006.1652049","url":null,"abstract":"This paper discusses the implementation of a distributed rendering environment (DRE) utilizing the TeraGrid. Using the new system, researchers and students across the TeraGrid have access to available resources for distributed rendering. Previously, researchers at universities and national labs, using high end rendering software such as Renderman Compliant Pixie were often limited by the amount of time that it takes to calculate (render) their final images. The amount of time required to render introduces several potential complications in a research setting. In contrast, a typical animation studio has a render farm, consisting of a cluster of computers (nodes) used to render 3D images, known as a distributed rendering environment. By spreading the rendering across hundreds of machines, the overall render time is reduced significantly. Unfortunately, most researchers do not have access to a distributed rendering environment. Our university has been developing a DRE for local use. However, because we are a TeraGrid site, we recently modified our DRE implementation to make use of open source rendering tools and grid tools such as Condor, in order to make the DRE available to other TeraGrid users","PeriodicalId":299480,"journal":{"name":"2006 IEEE Challenges of Large Applications in Distributed Environments","volume":"256 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114364188","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: 41

Distributed dynamic event tree generation for reliability and risk assessment 用于可靠性和风险评估的分布式动态事件树生成

2006 IEEE Challenges of Large Applications in Distributed Environments Pub Date : 2006-07-10 DOI: 10.1109/CLADE.2006.1652056

B. Rutt, Ümit V. Çatalyürek, A. Hakobyan, K. Metzroth, T. Aldemir, R. Denning, S. Dunagan, D. Kunsman

引用次数: 34

Creating personal adaptive clusters for managing scientific jobs in a distributed computing environment 创建个人自适应集群，用于管理分布式计算环境中的科学作业

2006 IEEE Challenges of Large Applications in Distributed Environments Pub Date : 2006-07-10 DOI: 10.1109/CLADE.2006.1652061

E. Walker, J. Gardner, V. Litvin, Evan L. Turner

引用次数: 78

Cross-Grid Applications Cross-Grid应用程序

2006 IEEE Challenges of Large Applications in Distributed Environments Pub Date : 1900-01-01 DOI: 10.1109/clade.2006.1652050

引用次数: 0