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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Yang-Suk Kee Casanova, H. Chien, A.A. |
| Copyright Year | 2004 |
| Description | Author affiliation: University of California at San Diego (Yang-Suk Kee) |
| Abstract | Understanding large Grid platform configurations and generating representative synthetic configurations is critical for Grid computing research. This paper presents an analysis of existing resource configurations and proposes a Grid platform generator that synthesizes realistic configurations of both computing and communication resources. Our key contributions include the development of statistical models for currently deployed resources and using these estimates for modeling the characteristics of future systems. Through the analysis of the configurations of 114 clusters and over 10,000 processors, we identify appropriate distributions for resource configuration parameters in many typical clusters. Using well-established statistical tests, we validate our models against a second resource collection of 191 clusters and over 10,000 processors, and show that our models effectively capture the resource characteristics found in real world resource infrastructures. These models are realized in a resource generator, which can be easily recalibrated by running it on a training sample set. |
| Starting Page | 54 |
| Ending Page | 54 |
| File Size | 4539820 |
| Page Count | 1 |
| File Format | |
| ISBN | 0769521533 |
| DOI | 10.1109/SC.2004.49 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2004-11-06 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Grid computing Computer science Mesh generation Monitoring Resource management Permission Computer networks Supercomputers Network synthesis Testing resource management Computational Grid resource modeling clusters resource discovery resource selection |
| Content Type | Text |
| Resource Type | Article |
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