Mapping abstract complex workflows onto grid environments

被引:32
作者
Ewa Deelman
James Blythe
Yolanda Gil
Carl Kesselman
Gaurang Mehta
Karan Vahi
Kent Blackburn
Albert Lazzarini
Adam Arbree
Richard Cavanaugh
Scott Koranda
机构
[1] Information Sciences Institute, University of Southern California, Marina Del Rey
[2] California Institute of Technology, Pasadena, CA 9112
[3] Department of Physics, University of Florida, Gainesville
[4] Department of Physics, University of Wisconsin, Milwaukee, WI 53211, Milwaukee 1900, East Kenwood Blvd
基金
美国国家科学基金会;
关键词
Complex applications; Planning; Reliability; Workflow management;
D O I
10.1023/A:1024000426962
中图分类号
学科分类号
摘要
In this paper we address the problem of automatically generating job workflows for the Grid. These workflows describe the execution of a complex application built from individual application components. In our work we have developed two workflow generators: the first (the Concrete Workflow Generator CWG) maps an abstract workflow defined in terms of application-level components to the set of available Grid resources. The second generator (Abstract and Concrete Workflow Generator, ACWG) takes a wider perspective and not only performs the abstract to concrete mapping but also enables the construction of the abstract workflow based on the available components. This system operates in the application domain and chooses application components based on the application metadata attributes. We describe our current ACWG based on AI planning technologies and outline how these technologies can play a crucial role in developing complex application workflows in Grid environments. Although our work is preliminary, CWG has already been used to map high energy physics applications onto the Grid. In one particular experiment, a set of production runs lasted 7 days and resulted in the generation of 167,500 events by 678 jobs. Additionally, ACWG was used to map gravitational physics workflows, with hundreds of nodes onto the available resources, resulting in 975 tasks, 1365 data transfers and 975 output files produced. © 2003 Kluwer Academic Publishers.
引用
收藏
页码:25 / 39
页数:14
相关论文
共 46 条
  • [1] Abramovici A., Althouse W.E., Et al., LIGO: The Laser Interferometer Gravitational-Wave Observatory (in Large Scale Measurements), Science, 256, pp. 325-333, (1992)
  • [2] Allcock W., Bester J., Et al., Secure, Efficient Data Transport and Replica Management for High-Performance Data- Intensive Computing, Presented At Mass Storage Conference, (2001)
  • [3] Ambite J.E.L., Knoblock C.A., Planning by Rewriting: Efficiently Generating High-Quality Plans, Proc. 14th National Conf. On Artificial Intelligence, (1997)
  • [4] Annis J., Zhao Y., Et al., Applying Chimera Virtual Data Concepts to Cluster Finding In the Sloan Sky Survey, (2002)
  • [5] Barish B.C., Weiss R., LIGO and the Detection of Gravitational Waves, Physics Today, 52, (1999)
  • [6] Berman F., Wolski R., Scheduling from the Perspective of the Application, Presented At High Performance Distributed Computing Conference, (1996)
  • [7] Blythe J., Decision-Theoretic Planning, AI Magazine, (1999)
  • [8] Blythe J., Deelman E., Gil Y., Kesselman C., Agarwal A., Mehta G., The Role of Planning in Grid Computing, 13th International Conference On Automated Planning & Scheduling, (2003)
  • [9] Boutlier C., Dean T., Hanks S., Planning under Uncertainty: Structural Assumptions and Computational Leverage, Journal of Artificial Intelligence, 11, (1999)
  • [10] Buyya R., Abramson D., Et al., Nimrod-G: An Architecture for a Resource Management and Scheduling System in a Global Computational Grid, Presented At HPC ASIA'2000, (2000)