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A decoupled scheduling approach for the GrADS program development environment
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Source Conference on High Performance Networking and Computing archive
Proceedings of the 2002 ACM/IEEE conference on Supercomputing table of contents
Baltimore, Maryland
Pages: 1 - 14  
Year of Publication: 2002
Authors
Holly Dail  University of California at San Diego and San Diego Supercomputer Center, University of California at San Diego
Henri Casanova  University of California at San Diego and San Diego Supercomputer Center, University of California at San Diego
Fran Berman  University of California at San Diego and San Diego Supercomputer Center, University of California at San Diego
Sponsors
IEEE-CS\DATC : IEEE Computer Society
ACM: Association for Computing Machinery
SIGARCH: ACM Special Interest Group on Computer Architecture
Publisher
IEEE Computer Society Press  Los Alamitos, CA, USA
Bibliometrics
Downloads (6 Weeks): 1,   Downloads (12 Months): 24,   Citation Count: 12
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ABSTRACT

Program development environments are instrumental in providing users with easy and efficient access to parallel computing platforms. While a number of such environments have been widely accepted and used for traditional HPC systems, there are currently no widely used environments for Grid programming. The goal of the Grid Application Development Software (GrADS) project is to develop a coordinated set of tools, libraries and run-time execution facilities for Grid program development.In this paper, we describe a Grid scheduler component that is integrated as part of the GrADS software system. Traditionally, application-level schedulers (e.g. AppLeS) have been tightly integrated with the application itself and were not easily applied to other applications. Our design is generic: we decouple the scheduler core (the search procedure) from the application-specific (e.g. application performance models) and platform-specific (e.g. collection of resource information) components used by the search procedure. We provide experimental validation of our approach for two representative regular, iterative parallel programs in a variety of real-world Grid testbeds. Our scheduler consistently outperforms static and user-driven scheduling methods.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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CITED BY  12

Collaborative Colleagues:
Holly Dail: colleagues
Henri Casanova: colleagues
Fran Berman: colleagues