Advanced Search
MyIDEAS: Login

Algorithmic Design and Beowulf Cluster Implementation of Stochastic Simulation Code of Stochastic Simulation Code for Large Scale Non Linear Models

Contents:

Author Info

  • gary anderson and raymond board

Abstract

Anderson & Moore describe a powerful method for solving linear saddle point models. The algorithm has proved useful in a wide array of applications including analyzing linear perfect foresight models, providing initial solutions and asymptotic constraints for nonlinear models. However, many algorithmic design choices remain in selecting components of a nonlinear certainty equivalence equation solver. This paper describes the present state of development of this set of tools. The paper descibes the results of simulation experiments using the FRBUS quarterly econometric model and the Canada Model. The paper provides data characterizing the impact of solution path length, initial path guess, terminal constraint strategy and strategies for exploiting sparsity on computation time, solution accuracy and memory requirements. The paper compares algorithm performance on traditional unix platform with our recent Beowulf Cluster Parallel Computation Implementation.

Download Info

To our knowledge, this item is not available for download. To find whether it is available, there are three options:
1. Check below under "Related research" whether another version of this item is available online.
2. Check on the provider's web page whether it is in fact available.
3. Perform a search for a similarly titled item that would be available.

Bibliographic Info

Paper provided by Society for Computational Economics in its series Computing in Economics and Finance 2001 with number 128.

as in new window
Length:
Date of creation: 01 Apr 2001
Date of revision:
Handle: RePEc:sce:scecf1:128

Contact details of provider:
Email:
Web page: http://www.econometricsociety.org/conference/SCE2001/SCE2001.html
More information through EDIRC

Related research

Keywords: beowulf; parallel; stack algorithm; anderson-moore algortithm;

Find related papers by JEL classification:

References

No references listed on IDEAS
You can help add them by filling out this form.

Citations

Lists

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

Statistics

Access and download statistics

Corrections

When requesting a correction, please mention this item's handle: RePEc:sce:scecf1:128. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Christopher F. Baum).

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.