Abstract
Realistic computer systems are hard to model using state-based methods because of the large spaces they require and the likely stiffness of the resulting models (because activities occur at many time scales). One way to address this problem is to decompose a model into submodels, which are solved separately but exchange results. We call modeling formalisms that support such techniques "connection formalisms." In this paper, we describe a new set of connection of formalisms that reduce state-space size and solution time by identifying submodels that are not affected by the rest of a model, and solving them separately. A result from each solved submodel is then used in the solution of the rest of the model. We demonstrate the use of two of these connection formalisms by modeling a real-world file server in the Möbius modeling framework. The connected models were solved one to two orders of magnitude faster than the original model, with one of these decomposition techniques introducing an error of less than 11%.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 258-265 |
| Number of pages | 8 |
| Journal | Proceedings of the IEEE Annual Simulation Symposium |
| State | Published - Jan 1 2001 |
| Event | 34th Annual Simulation Symposium (SS 2001) - Seattle, WA, United States Duration: Apr 22 2000 → Apr 26 2000 |
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ASJC Scopus subject areas
- Software
- Modeling and Simulation
Cite this
A connection formalism for the solution of large and stiff models. / Daly, D.; Sanders, William H.
In: Proceedings of the IEEE Annual Simulation Symposium, 01.01.2001, p. 258-265.Research output: Contribution to journal › Conference article
}
TY - JOUR
T1 - A connection formalism for the solution of large and stiff models
AU - Daly, D.
AU - Sanders, William H
PY - 2001/1/1
Y1 - 2001/1/1
N2 - Realistic computer systems are hard to model using state-based methods because of the large spaces they require and the likely stiffness of the resulting models (because activities occur at many time scales). One way to address this problem is to decompose a model into submodels, which are solved separately but exchange results. We call modeling formalisms that support such techniques "connection formalisms." In this paper, we describe a new set of connection of formalisms that reduce state-space size and solution time by identifying submodels that are not affected by the rest of a model, and solving them separately. A result from each solved submodel is then used in the solution of the rest of the model. We demonstrate the use of two of these connection formalisms by modeling a real-world file server in the Möbius modeling framework. The connected models were solved one to two orders of magnitude faster than the original model, with one of these decomposition techniques introducing an error of less than 11%.
AB - Realistic computer systems are hard to model using state-based methods because of the large spaces they require and the likely stiffness of the resulting models (because activities occur at many time scales). One way to address this problem is to decompose a model into submodels, which are solved separately but exchange results. We call modeling formalisms that support such techniques "connection formalisms." In this paper, we describe a new set of connection of formalisms that reduce state-space size and solution time by identifying submodels that are not affected by the rest of a model, and solving them separately. A result from each solved submodel is then used in the solution of the rest of the model. We demonstrate the use of two of these connection formalisms by modeling a real-world file server in the Möbius modeling framework. The connected models were solved one to two orders of magnitude faster than the original model, with one of these decomposition techniques introducing an error of less than 11%.
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UR - http://www.scopus.com/inward/citedby.url?scp=0034994984&partnerID=8YFLogxK
M3 - Conference article
AN - SCOPUS:0034994984
SP - 258
EP - 265
JO - Proceedings of the IEEE Annual Simulation Symposium
JF - Proceedings of the IEEE Annual Simulation Symposium
SN - 0272-4715
ER -